040404124p-main thesis paper
TRANSCRIPT
HEALTH IMPACTS OF URBAN WATER SUPPLY ON THE
VULNERABLE COMMUNITIES OF SELECTED AREAS OF
DHAKA CITY
MD. ZAMIL HOSSAIN MUNSHI
DEPARTMENT OF CIVIL ENGINEERING
BANGLADESH UNIVERSITY OF ENGINEERING & TECHNOLOGY
DHAKA, BANGLADESH
DECEMBER 2011
HEALTH IMPACTS OF URBAN WATER SUPPLY ON THE VULNERABLE
COMMUNITIES OF SELECTED AREAS OF DHAKA CITY
by
Md. Zamil Hossain Munshi
A thesis submitted to the Department of Civil Engineering,
Bangladesh University of Engineering & Technology, Dhaka
in partial fulfillment of the requirements for the degree
of
MASTER OF SCIENCE IN CIVIL ENGINEERING
DEPARTMENT OF CIVIL ENGINEERING
BANGLADESH UNIVERSITY OF ENGINEERING & TECHNOLOGY
December 2011
ii
The thesis titled “HEALTH IMPACTS OF URBAN WATER SUPPLY ON THE
VULNERABLE COMMUNITIES OF SELECTED AREAS OF DHAKA CITY”
submitted by Md Zamil Hossain Munshi, Roll No: 040404124 (P), Session: 2004 has
been accepted as satisfactory in partial fulfillment of the requirement for the degree
of Master of Science in Civil Engineering (Environmental) on 03 December 2011.
BOARD OF EXAMINERS
1. ----------------------------------------------------------- Dr. Md. Mafizur Rahman Chairman Professor Department of Civil Engineering BUET, Dhaka
2. ------------------------------------------------------------- Dr. Md. Mujibur Rahman Member Professor and Head (Ex-Officio) Department of Civil Engineering BUET, Dhaka
3. ------------------------------------------------------------- Dr. Md. Delwar Hossain Member Professor Department of Civil Engineering BUET, Dhaka
4. ------------------------------------------------------------- Major Muhammad Sohail-Us-Samad Member Assistant Director (External) Survey of Bangladesh, Dhaka
iii
CANDIDATE’S DECLARATION
It is hereby declared that this thesis or any part of it has not been submitted elsewhere for the award of any degree or diploma.
--------------------------------------------------- Md. Zamil Hossain Munshi
Roll No: 040404124 (P)
iv
TABLE OF CONTENTS
CERTIFICATION ii
CANDIDATE’S DECLARATION iii
TABLE OF CONTENTS iv
LIST OF TABLES ix
LIST OF FIGURES xiii
LIST OF ABBREVIATIONS xviii
ACKNOWLEDGMENTS xix
ABSTRACT xx
CHAPTER 1: INTRODUCTION 1
1.1 General 1
1.2 Rationale of the Study 2
1.3 Objectives of the Study 4
1.4 Scope of the Study 4
1.5 Limitations of the Study 5
1.6 Organization of the Thesis 6
CHAPTER 2: LITERATURE REVIEW 7
2.1 Introduction 7
2.2 The Vulnerable Community 8
2.2.1 Definition 8
2.2.2 Considerations 8
2.2.3 Estimation of Population of a Community 9
2.2.4 Performance of Community Drinking-Water System 9
2.3 Water Pollution and Related Issues 9
2.3.1 Water Pollution 9
2.3.2 Types of Pollutants, Sources and Effects 10
2.3.3 Background Level of Immunity 13
2.4 Water Quality and Standards 13
v
2.4.1 Water Quality 13
2.4.2 Water Quality Standards 13
2.5 Water Supply 15
2.5.1 Objectives of Water Supply 15
2.5.2 Pattern of Urban Water Supply for Vulnerable Group 15
2.6 Domestic Water Supply 16
2.6.1 Domestic Water and its Usage 16
2.6.2 The Links Between Water Supply, Hygiene and Disease 17
2.7 Sanitation 18
2.7.1 Definition and Objectives of Sanitation 18
2.7.2 Relationships Between Water, Sanitation, Hygiene and Diarrhoea 19
2.7.3 Relationships Between Water, Hygiene and Other Infectious Diseases
21
2.7.4 Quantity and Accessibility 21
2.7.5 Hazards of Water Supply 22
2.8 Dhaka and Its Water Supply System 23
2.8.1 Growth of Dhaka 23
2.8.2 Dhaka Water Supply and Sewerage Authority (DWASA) 24
2.8.3 Water Supply Situation 26
2.8.4 Water Quality Monitoring System 27
2.9 Economic Valuation of Diseases 28
2.9.1 General 28
2.9.2 Importance of Monetary Valuation 28
2.9.3 The Major Economic Impacts of Pollution 29
2.9.4 Techniques to Place Monetary Values on Environmental Impacts 29
2.10 Prevalence Rate (PR) 30
2.10.1 Importance 30
2.10.2 Formula Used in PR 31
2.11 Statistical Analysis Tools 31
2.11.1 Arithmetic Mean 31
2.11.2 Grade Point Average (GPA) 32
2.11.3 Standard Deviation 32
vi
2.11.4 Correlation Coefficient (Cr) 32
CHAPTER 2: METHODOLOGIES 33
3.1 Introduction 33
3.2 Methodologies 33
3.3 Design Procedure 35
3.3.1 Selection of Vulnerable Communities 37
3.3.2 Vulnerability Score 37
3.3.3 Identification of Urban Water Supply Options 38
3.3.4 Field Survey 38
3.3.5 Economic Valuation of Diseases 45
3.3.6 Prevalence Rate (PR) 47
3.3.7 Climatic factors 48
CHAPTER 4: ANALYSIS OF DATA 49
4.1 Introduction 49
4.2 Data Availability in Bangladesh 49
4.3 Selection of Data 49
4.3.1 Yearly Records 50
4.3.2 Monthly Records 53
4.3.3 Meteorological Data 53
4.4 Analysis of Field Data 57
4.4.1 Questionnaires Survey- An Overview 57
4.4.2 Qualitative Assessment 58
4.4.3 Quantitative Assessment 69
4.4.4 Economic Valuation of Diseases 77
4.4.5 Analysis of Prevalence Rate 79
4.5 Development of Correlation Between Diarrhoea Patient Reporting Cases and Climatic Factors
81
4.5.1 Identification of Correlation 81
4.5.2 Development of Correlation Equation 84
CHAPTER 5: RESULTS AND DISCUSSIONS 87
5.1 Introduction 87
5.2 Qualitative Assessment
87
vii
5.2.1 Urban Water Supply Options 87
5.2.2 Distance of Water Source and Time Require to Fetch Water
89
5.2.3 Quantity and Accessibility to Water 90
5.2.4 Water Boiling Practices 92
5.2.5 Storage of Water 93
5.2.6 Sanitation Systems 95
5.2.7 Hygiene Practices-Use of Hand Wash Medium 96
5.2.8 Water Quality of Collected Samples 98
5.2.9 Sanitary Inspection (SI) 101
5.3 Quantitative Assessment 104
5.3.1 Overall Evaluation on Health Impacts 107
5.4 Evaluation on Estimated Health Impact Valuation of Waterborne Diseases 117
5.5 Evaluation of Prevalence Rate 118
5.6 Correlation Between Diarrhoea Patient Reporting Cases and Climatic Factors
121
5.7 GIS Representation of Relevant Data in Thematic Maps
123
CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS 124
6.1 Conclusions 124
6.2 Recommendations
130
REFERENCES 131
APPENDICES
Appendix A Questionnaires Survey Form 135
Appendix B Sanitary Inspection Forms 139
Appendix C 15 Years (1996-2010) Averaged Diarroheal Patients Reported
142
Appendix D 11 Years Monthly Average (2000-2010) Diarrhoeal Patients Reported 143
viii
Appendix E Thana wise Estimated Population of Dhaka City for the Year of 2010 144
Appendix F Data of Selected Climatic Factors for Dhaka Station 145
Appendix G Relevant Data From Questionnaires Survey 146
Appendix H Analysis of Sanitary Inspection (SI) Data 148
Appendix I Analysis of Water Quality of Selected Areas 152
Appendix J Overall Grading Based on Vulnerability Scores 155
Appendix K Estimated Health Impact Valuation of Waterborne Diseases of Dhaka City 158
Appendix L Calculation of Prevalence Rate of Waterborne Diseases of Selected Areas of Dhaka City 160
Appendix M Correlation Between Diarrhoeal Incidences and Climatic Factors 164
Appendix N Criteria Wise Health Impacts of the Selected Communities, Areas and Urban Water Supply Options 168
Appendix O Thematic Maps of Dhaka City 192
ix
LIST OF TABLES
Table 2.1 Heavy Metal Concentration in River Water of Dhaka City 11
Table 2.2 Concentration of Water Quality Indicators of Lake Water of
Dhaka City 11
Table 2.3 Bangladesh Water Quality Standards For Surface Water
For Water Supply 14
Table 2.4 Bangladesh Standard For Drinking Water 14
Table 2.5 Volumes of Water Required For Hydration For the Most
Vulnerable in Tropical Climates 19
Table 2.6 Infrastructures and Establishment of DWASA 28
Table 2.7 Source Wise Water Production of DWASA in October 2009 29
Table 3.1 Vulnerability Score and State of Vulnerability 37
Table 3.2 Basic Data for Grading and Representation 38
Table 3.3 The Water Supply Options Found in the Study Areas 38
Table 3.4 Data Filtering Process: Step-1 41
Table 3.5 Data Filtering Process for Diarrhoea: Step-2a 42
Table 3.6 Data Filtering Process for Typhoid: Step-2b 42
Table 3.7 Data Filtering Process for Eye Infections: Step-2c 43
Table 3.8 Final Result of Data Filtering Process 43
Table 3.9 Criteria Used For Grading the SI Risk Scores 44
Table 3.10 List of Laboratory Tests For Collected Water Samples 45
Table 3.11 Calculation of Hourly Average Wage Rate 46
Table 4.1 Generalized Population of Administrative Areas of Dhaka
City Reporting ICDDR, B in 2010 52
Table 4.2 Selected Thana Wise Different Age Groups Patients 52
Table 4.3 At a Glance of Dhaka City Climate 53
Table 4.4 Sample Area Wise Distribution of Interviewed HHs and Exposed Population
58
Table 4.5 Age Group Wise Distribution of Interviewed Communities 58
x
Table 4.6 Distribution of number of HHs to Urban Water Supply
Options As Per Community Type And Connection Sources 59
Table 4.7 Distribution of Selected Area Wise Observed Water Points
To Urban Water Supply Options 61
Table 4.8 Distribution of Community Wise Observed Water Points to
Urban Water Supply Options 61
Table 4.9 Distribution of number of HHs Residing At Different
Distances From Water Sources. 61
Table 4.10 Distribution of Community Wise HHs Against Water Fetch
Time
62
Table 4.11 Distribution of Number of HHs Against Water Demand and
Water Sources' Connections 62
Table 4.12 Distribution of Community Wise Number of HHs Against
Water Demand and Urban Water Supply Options 63
Table 4.13 Sample Area Wise Number of HHs Reporting Occasional
Aesthetic Quality of Water 63
Table 4.14 Distribution of HHs of Different Community Types Against
Water Boiling Practices and Urban Water Supply Options 64
Table 4.15 Distribution of HHs Against Water Boiling Duration and
Urban Water Supply Options 64
Table 4.16 Distribution of HHs of Different Community With Respect to
Water Storage System at HH Level. 65
Table 4.17 Distribution of HHs of Different Selected Areas With
Respect to Water Storage System at HH Level. 65
Table 4.18 Distribution of HHs of Different Urban Water Supply System
With Respect to Water Storage System at HH Level. 65
Table 4.19 Sample Area Wise Distribution of HHs of Different
Communities Having Different Sanitation Systems 65
Table 4.20 Sample Area Wise Distribution of HHs of Different
Communities Showing Hand Washing Practices 66
Table 4.21 Area Wise Number of Samples of Different Faecal Coliform
Concentration 67
Table 4.22 Community Wise Number of Samples of Different Faecal
Coliform Concentration 67
Table 4.23 Urban Water Supply Option Wise Number of Samples of 67
xi
Different Faecal Coliform Concentration
Table 4.24 Area Wise Distribution of Number of Water Points As Per Risk Grade
68
Table 4.25 Community Wise Distribution of Number of Water Points As
Per Risk Grade 68
Table 4.26 Urban Supply Options Wise Distribution of Number of
Water Points As Per Risk Grade 68
Table 4.27 Gender Wise Overall Incidences of Waterborne Diseases
of Different Age Groups 69
Table 4.28 Sample Areas Wise State of Waterborne Diseases’
Incidences of Different Gender 69
Table 4.29 Community Wise State of Waterborne Diseases’
Incidences 70
Table 4.30 Community Wise Waterborne Diseases’ Incidences With
Respect to Water Sources’ Connections 71
Table 4.31 Waterborne Diseases’ Incidences With Respect to Urban
Water Supply Options 71
Table 4.32 Community Wise Waterborne Diseases’ Incidences With
Respect to Urban Water Supply Options 72
Table 4.33 Waterborne Diseases’ Incidences With Respect to Distance
Between HH and Source 73
Table 4.34 Waterborne Diseases’ Incidences With Respect to Time
Taken to Fetch Water From Source 73
Table 4.35 Waterborne Diseases’ Incidences With Respect to Water
Received Against Demand 74
Table 4.36 Waterborne Diseases’ Incidences With Respect to Boiling
of Water. 74
Table 4.37 Waterborne Diseases’ Incidences With Respect to Time
Spent For Boiling of Water. 75
Table 4.38 Waterborne Diseases’ Incidences With Respect to Storage
of Water.
75
Table 4.39 Waterborne Diseases’ Incidences With Respect to Sanitary Practices.
76
Table 4.40 Waterborne Diseases’ Incidences With Respect to Hand
Wash Media. 76
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Table 4.41 Overall Health Impacts Based on Water Quality (FC Concentration)
77
Table 4.42 Waterborne Diseases’ Incidences With Respect to Risk
Grade. 77
Table 4.43 Cost of Waterborne Disease- Diarrhoea 78
Table 4.44 Cost of Waterborne Disease- Typhoid 78
Table 4.45 Cost of Waterborne Disease- Eye infections 79
Table 4.46 Basic Data For Prevalence Rate of Different Age-Groups 79
Table 4.47 Basic Data For Prevalence Rate of Different Community 80
Table 4.48 Basic Data For Prevalence Rate of Different Selected
Areas 80
Table 4.49 Basic Data For Prevalence Rate of Different Urban Water
Supply Options 80
Table 4.50 Correlation Coefficient of Climatic Parameters and
Diarrhoeal Incidences of the Selected Areas 84
Table 4.51 Selection of Correlation Equation Based on Correlation
Coefficients 85
Table 5.1 Number of Likely and Actual Diarrhoeal Incidences With
Respect to Temperature 122
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LIST OF FIGURES
Figure 2.1 Disease Transmission and Sanitation 19
Figure 2.2 Interrelationship between Water, Sanitation and Health Education
20
Figure 2.3 Graph of Travel Time (In Minutes) Versus Consumption 22
Figure 2.4 Generic Flow Diagram of Water Supply System 23
Figure 2.5 DWASA Service Areas in DMPA 25
Figure 2.6 Prediction of Population and Water Demand in Dhaka City 27
Figure 3.1 Methodology Diagram 34
Figure 3.2 Slums of Dhaka Metropolitan Area 36
Figure 4.1 Yearly Trends of Waterborne Disease’s Patients of Dhaka City 50
Figure 4.2 Children Patients Reporting DSH During 2005-06. 51
Figure 4.3 General Trend of Patients of Waterborne Diseases 53
Figure 4.4 Variations of Annual Rainfall of Dhaka city 54
Figure 4.5 Trend of Rainfall of Dhaka City 54
Figure 4.6 Variations of Average Annual Temperature of Dhaka city 55
Figure 4.7 Trend of Temperature of Dhaka city 55
Figure 4.8 Variations of Average Annual Humidity of Dhaka city 56
Figure 4.9 Trend of Average Annual Humidity of Dhaka city 56
Figure 4.10 Distribution of Population by Number of Person per HH 57
Figure 4.11 Sample Areas Wise Different Distance Range Between Households and Water Sources.
62
Figure 4.12 Trend of Diarrhoeal Patients of Sample Area and Dhaka 81
Figure 4.13 Diarrhoeal Patients of Sample Area and Average Rainfall 82
Figure 4.14 Diarrhoeal Patients of Sample Area and Average Temperature 82
Figure 4.15 Diarrhoeal Patients of Sample Area and Average Humidity 82
Figure 4.16 Diarrhoeal Patients-Rainfall Correlation (2000-2010) 83
xiv
Figure 4.17 Diarrhoeal Patients-Temperature Correlation (2000-2010) 83
Figure 4.18 Diarrhoeal Patients-Humidity Correlation (2000-2010) 84
Figure 4.19 Average Diarrhoeal Patients-Temperature Correlation for Study Areas and Dhaka as a Whole (2000-2010)
85
Figure 5.1 Overall State of Different Water Supply Options 88
Figure 5.2 Community wise State of Different Water Supply Options 88
Figure 5.3 Community Wise Different Distance Range Between Households and Water Source.
89
Figure 5.4 Urban Water Supply Options Wise Different Distance Range Between Households and Water Source.
90
Figure 5.5 Overall State of Different Distance Range Between Households
and Water Source. 90
Figure 5.6 State of Different Water Demand Against Community Type 91
Figure 5.7 State of Different Water Demand Against Urban Water Supply Options
91
Figure 5.8 Overall State of Different Water Demand Fulfillment 91
Figure 5.9 Community Wise Percentages of HHs Having Water Boiling Practices
92
Figure 5.10 Sample Area Wise State of Water Boiling Practices by HHs.
93
Figure 5.11 Overall State of Water Boiling Practices Observed in the Study Area
93
Figure 5.12 Overall state of Different Water Storage System 94
Figure 5.13 Community Wise Number of HHs for Different Water Storage System
94
Figure 5.14 Sample Area Wise Number of HHs for Different Water Storage
System 95
Figure 5.15 Distribution of HHs According to Sample Area Based on
Sanitation System in Use. 95
Figure 5.16 Overall State of Sanitary Practices in the Sample Area. 96
Figure 5.17 Overall State of Hygiene Practices 97
Figure 5.18 Community Wise Distribution of HHs Based on Hand Wash Media.
97
Figure 5.19 Sample Area Wise Distribution of HHs Based on Hand Wash Medium.
97
xv
Figure 5.20 Community Wise Percentages Of Households Reporting the
Aesthetic Quality of Water. 98
Figure 5.21 Overall State of Aesthetic Quality of Water of Study Area 99
Figure 5.22 pH Distribution of The Water Sample of Different Communities 99
Figure 5.23 pH Distribution Of The Water Sample Of Different Areas. 100
Figure 5.24 Microbial Water Qualities of Water Supply in Different Communities.
101
Figure 5.25 State of Overall SI Risk Grading of Water points of Study Area 101
Figure 5.26 Comparative State of Communities Based on SI Risk Grading. 102
Figure 5.27 Overall State of Communities Based on SI Risk Grading. 102
Figure 5.28 Comparative State of Vulnerable Areas Based on SI Risk Grading.
102
Figure 5.29 Overall State of Selected Areas based on SI Risk Grading. 103
Figure 5.30 Comparative State of Urban Water Supply Options Based on SI
Risk Grading. 103
Figure 5.31 Overall State of Urban Water Supply Options based on SI Risk Grading.
104
Figure 5.32 Overall State of Waterborne Diseases of Interviewed Households 104
Figure 5.33 Gender Distributions of the Affected Persons 105
Figure 5.34 Comparison between Male and Female Diarrhoeal Incidences 105
Figure 5.35 State of Different Gender Age-Groups for Waterborne diseases 106
Figure 5.36 Overall Vulnerability of Communities 107
Figure 5.37 State of Vulnerability of Communities Based on Diarrhoea Incidences
108
Figure 5.38 Correlation Between Demand And Number of Diarhoea
Incidences. 108
Figure 5.39 Correlation between FC Count and Diarrhoea Incidences in Percentage.
109
Figure 5.40 State of Vulnerability of Communities Based on Typhoid Incidences
109
Figure 5.41 State of Vulnerability of Communities Based on Eye Infections’ Incidences
110
xvi
Figure 5.42 Correlation Between SI Risk Score and Percentage of Eye Infections’ Incidences Against Exposures.
110
Figure 5.43 The Order of Community Based on Cumulative Vulnerability
Scores 111
Figure 5.44 Overall Vulnerability of Selected Areas of Dhaka City 111
Figure 5.45 State of Vulnerability of Selected Areas Based on Diarrhoea
Incidences 112
Figure 5.46 State of Vulnerability of Selected Areas Based on Typhoid
Incidences 113
Figure 5.47 State of Vulnerability of Selected Areas Based on Eye Infections
Incidences 113
Figure 5.48 The Order of Selected Areas Based on Cumulative Vulnerability
Scores 114
Figure 5.49 Overall Vulnerability of Urban Water Supply Options 114
Figure 5.50 State of Vulnerability of Urban Water Supply Options Based on
Diarrhoea Incidences
115
Figure 5.51 State of Vulnerability of Urban Water Supply Options Based on
Typhoid Incidences
115
Figure 5.52 State of Vulnerability of Urban Water Supply Options Based on
Eye Infections Incidences. 116
Figure 5.53 The Order of Urban Water Supply System Options Based on
Cumulative Vulnerability Scores
116
Figure 5.54 Comparison Between the Cost of Non-Reporting Waterborne
Diseases, GDP at Current Price and GDP at Constant Price (2009-10).
118
Figure 5.55 Prevalence Rate of Waterborne Diseases. 118
Figure 5.56 The State of PR Values of Different Genders 119
Figure 5.57 The State of PR Values of Different Age-Groups of Different
Genders Suffering From Diarrhoea. 119
Figure 5.58 The State of PR Values of Different Age-Groups of Different Genders Suffering From Typhoid
120
Figure 5.59 The State of PR Values of Different Age-Groups of Different
Genders Suffering From Eye Infections
120
xvii
Figure 5.60 Projected Average Diarrhoeal Patients of Study Areas Based on Temperature
121
Figure 5.61 Projected Average Diarrhoeal Patients of Dhaka Based on
Temperature
121
Figure 5.62 Average Maximum Temperature Profile at Different Time Range 122
xviii
LIST OF ABBREVIATIONS
BBS Bangladesh Bureau of Statistics
BCAS Bangladesh Centre for Advanced Studies
BMD Bangladesh Meteorological Department
BOD Biochemical Oxygen Demand
CBO Community Based Organization
CUS Centre for Urban Studies
DALY Disability Adjusted Life Year
DCC Dhaka City Corporation
DMA Dhaka Metropolitan Area
DO Dissolved Oxygen
DOE Department of Environment
DSH Dhaka Shishu Hospital
DWASA Dhaka Water Supply and Sewerage Authority
ECA Environmental Conservation Act
ECR Environment Conservation Rules
EPA Environmental Protection Agency (USA)
EQS Environmental Quality Standard
FC Faecal Coliform
GIS Geographical Information System
HH Household
ICDDR,B International Centre for Diarrhoeal Disease Research,
Bangladesh
IPH Institute of Public Health
ITN-BUET International Training Network Centre, BUET
LGED Local Government Engineering Department
MLD Million Litre per Day
STW Shallow Tubewell
TDS Total Dissolved Solid
UNDP United Nations Development Programme
UNICEF United Nations Children's Fund
UNEP United Nations Environment Programme
WHO World Health Organization
WTP Willingness to pay
xix
ACKNOWLEDGMENTS
The author wishes to express sincere gratitude to his Supervisor Dr. Md. Mafizur Rahman for his continued guidance and encouragement throughout the whole period of the thesis work. His careful guidance, constructive suggestions immensely contributed to the improvement of this thesis paper.
The author is indebted to Dr. A.S.G. Faruque, Scientist,CSD and Md. Abdul Malek, Data Manager,CSD of International Centre for Diarrhoeal Research, Bangladesh (ICDDR,B), Dr Mizanur Rahman of Dhaka Shishu Hospital(DSH) for their enormous support in providing necessary data. The author acknowledges the contributions of members of DOE, BMD, DCC, SOB etc for their support in regard to various data.
The author acknowledges the sacrifice of his family members notably his wife, Papia for all her assistance and encouragement.
Last but not the least, the author expresses his gratitude and appreciation to the members of the Examination Board.
xx
ABSTRACT Water plays a vital role to shape up the health quality of dwellers of Dhaka city. Quite a large number of people are usually affected by waterborne diseases in each year and various studies reveal that due to presence of high percentage of low-income and slum communities in the capital, the high rates of diarrhoeal incidences mostly come from these vulnerable communities who lack of adequate water, sanitation and knowledge on personal hygiene. This study identifies the vulnerable community composed of people (73%) mainly from other districts coming for economic reason. A bimodal distribution of diarrhoeal incidences especially before rainy season (March-May) and during rainy season (July-October) has been observed from these communities.
It is seen that maximum number of HHs (65%) of vulnerable communities had their supplied water of DWASA through private connections and the rest 35% had their supplied water of DWASA through public connections. A high percentage of diarrhoeal (74%), typhoid (60%) and eye infections (77%) incidences in case of private connections were reported. Majority of vulnerable communities’ HHs (47%) were having urban water supply options like “Hand pump connected to supply line”, 38% of HHs were having “Piped water supply without reservoir” and rest 15% HHs were having “Piped water supply with reservoir”. So it was about 85% (47%+38%) of the total HHs those were to rely on unsecured water supply. On the other hand, 95% of HHs never had their demand fulfilled out of which only 55% could mitigate their daily need by just half of their demand. Only 5% showed their fulfillment of their demand as per as water availability are concerned. Overall 68% of HHs did not boil water for drinking purpose and slum do not boil water just for economic reason. The slum community had more pit latrine system (64%) where low-income community based on septic tank system (67%).83% of slum HHs did not use any media to wash their hands following defecation, on the contrary 100% low-income HHs were found very much aware about use of media (in this case soap).
Samples of water from WASA pumps showed the quality of water was quite acceptable as per Bangladesh Standard but the water samples from user ends showed high contamination of water with faecal coliform. It was observed that most of the private connections (mainly slum community) were made with leaky pipes drawn over the waste and wet lands. Moreover maximum water points were in very close proximity to latrines or poorly maintained.
About 58%, 23% and 56% of HH members were suffering from diarrhoea, typhoid and eye infections respectively. It was seen that male were more vulnerable to the waterborne diseases than those of female. It was also seen that female children <5 years(10%) suffer from diarrhoea just double than male percentage (5%). Gender differences could be one of the reasons.
Overall vulnerability of communities indicate that slum had higher combined vulnerability scores for diarrhoea (CVSdiarrhoea = 5.86) and eye infections (CVSeye
infections = 6.67) than those of low-income community and overall vulnerability of selected areas indicate that the slum and low-income communities of Gulshan area are the most vulnerable, followed by the slum and low-income communities of Tejgaon, Mirpur and Badda.
xxi
This study found that for each non-reported diarrhoea incidence remained on average for 5.03 days with standard deviation of 2.02 days. The direct, indirect and total costs were Tk. 759, Tk. 762 and Tk. 1522 respectively. Again each typhoid incidence remained on average for 17.4 days with standard deviation of 7.2 days. The direct, indirect and total costs were about Tk. 3621, Tk. 1361 and Tk. 4982.68 respectively. Finally eye infections’ incidence remains on average for 6.3 days with standard deviation of 1.5 days. The direct, indirect and total costs were Tk. 205, Tk. 712 and Tk. 917 respectively. The total cost of diseases for selected areas for one year could be from 87,138,383 Tk. to 149,892,036 Tk. and for slum areas of whole Dhaka city is 5,653,819,098Tk. or 81,726,209 USD. This huge amount of money is generally expended by these groups and might remain unnoticed or not considered during city planning or any national development plan. The prevalence rate (PR) reveals that vulnerable people are more susceptible to the diarrhoea (PRdiarrhoea = 480.95) than those of eye infections PReye infections = 309.52 and typhoid (PRtyphoid = 47.62). This study identifies an exponential correlation between numbers of diarrhoea incidences of reporting cases with temperature of Dhaka city. Moreover it also has identified a negative correlation between the demands of water with the number of non-reporting diarrhoea incidences.
1
CHAPTER 1
INTRODUCTION
1.1. General
Water is one of the five essentials (air, water, food, heat and light) for the human
beings, without which life cannot be sustained for longer period. Over 70% of the
earth's surface is water. However, most of it i.e. 98% is salt water and only 2% of
the earth's water is fresh water that we can drink. Water is the basis of all life forms
even including our body. Our muscles that move our body are 75% water; our blood
that transports nutrients is 82% water; our lungs that provide oxygen are 90% water;
our brain that is the control center of our body is 76% water; even our bones are
25% water (Batmanghelidj, 2008). It is undoubtedly the most precious natural
resource that exists on our planet without this seemingly invaluable compound, life
on earth would not be in existence. It is essential for everything on our planet to
grow and prosper. Although we as human recognize this fact but we disregard it by
polluting our lakes, rivers and oceans by throwing industrial effluents, municipal
waste, agricultural waste, sewage disposal, etc. Subsequently, we are slowly but
surely harming our planet to the point of no return! As we understand that our health
is truly dependent on the quality and quantity of the water we drink. Hence any
deficiency either of it is going to have a negative effect on our health. That is why
safe, adequate and accessible supplies of water, combined with proper sanitation,
are basic needs and essential components of primary health care. The larger the
quantity and the better the quality of water, the more rapid and extensive is the
advancement of the public health (Ahmed and Rahman, 2000). Pollution of
freshwater (drinking water) is a problem for about half of the world's population.
Each year there are about 250 million cases of water-related diseases, with roughly
5 to 10 million deaths (GP, 2005). Contaminated water - contaminated by feces, not
chemicals - remains one of the biggest killers worldwide. According to one recent
estimate, lack of adequate water, sanitation and hygiene is responsible for an
estimated 7 percent of all deaths and disease globally. Diarrhoea alone claims the
lives of some 2.5 million children a year (Murray and Alan, 1996). It has been noted
that the Asian rivers are the most polluted in the world. They have three times as
many bacteria from human waste as the global average and 20 times more lead
than rivers in industrialized countries (GP, 2005). On the contrary Bangladesh has
some of the most polluted groundwater in the world. In this case, the contaminant is
2
arsenic, which occurs naturally in the sediments. Around 85% of the total area of the
country has contaminated groundwater, with at least 1.2 million Bangladeshis
exposed to arsenic poisoning and with millions more at risk (GP, 2005). In
Bangladesh, drinking water supplies, both in urban and rural areas are often found
to contain contaminants (ITN-BUET, 2004). Access to safe drinking-water is
essential to health. It has been seen that investments in water supply and sanitation
can yield a net economic benefit, since the reductions in adverse health effects and
health care costs outweigh the costs of undertaking the interventions. Experience
has also shown that interventions in improving access to safe water favor the poor
in particular, whether in rural or urban areas and can be an effective part of poverty
alleviation strategies.
Dhaka is the capital of Bangladesh. Rapid urbanization and population growth in last
decades have changed the physical environment of Dhaka. Population of Dhaka
metropolitan area has been estimated to be 12 million and the city has grown at a
rate of 4.5 sq. km per year in the recent past (Mahmood, 2008). A recent media
report says that there are about 38% of total population of Dhaka is living in slum
areas. Again homelessness and poverty are international crisis where Bangladesh
is not an exception to this. It is being one of the poorest countries in the world; with
an estimated 3.4 million people live in some 5000 slums of its capital city, Dhaka
(Islam, 2005). But interestingly most of the time, it is the low-income groups and
people of slums are human capital greatly contributing to the economy and work
force of the capital city. The majority of them migrated to Dhaka for economic
reasons (Tiina et al., 2002), but unfortunately these peoples suffer unacceptable
levels of malnutrition, hygiene and health, deprived of essential health services,
financial stability, education and security. Dhaka has become one of the dirtiest city
of the world (Tiffany, 2008). Like other environmental factors water plays a vital role
to shape up the health quality of dwellers of Dhaka city. Quite a large number of
people is usually affected by waterborne diseases in each year and most of them
are from vulnerable groups.
1.2. Rationale of the Study
It is estimated that 88% of diarrhoeal disease is caused by unsafe water supply and
inadequate sanitation and hygiene (WHO, 2004). Lack of access to safe and
adequate water supplies contributes to ongoing poverty both through the economic
3
costs of poor health and in the high proportion of household expenditure on water
supplies in many poor communities, arising from the need to purchase water and/or
time and energy expended in collection. Access to water services forms a key
component in the UNDP Human Poverty Index for developing countries
(UNDP, 1999). Access to safe drinking water has been an important national goal in
Bangladesh. As per the WHO report, Bangladesh has already attained 97% total
water coverage and 53% total sanitation coverage with 99% urban water coverage
and 82% urban sanitation coverage during 2000 (WHO/UNICEF, 2000).
While Bangladesh has almost achieved accepted bacteriological drinking water
standards for water supply, high rates of diarrhoeal disease morbidity indicate that
pathogen transmission continues through water supply chain (and other modes)
(Hoque et al., 2006). In case of Dhaka, various studies reveal that due to presence
of high percentage of low-income and slum communities in the capital, these high
rates of diarrhoeal incidences mostly come from these vulnerable communities who
lack of adequate water, sanitation and knowledge on personal hygiene. Though it is
well understood that the adequacy of water and accessibility to those
services/facilities rest on Dhaka Water Supply and Sewerage Authority (DWASA)
who is principally responsible for the provision, operation and maintenance of water
supply, sanitation and storm water disposal services to the population of Dhaka city
as stipulated in the Water Supply and Sewerage Authority Act, 1996. But today it is
facing various challenges both for quantity and quality of supply and heading for
awkward situation due to the unplanned population growth.
To understand the exact cause of major waterborne diseases morbidity of
vulnerable communities of Dhaka city, this study has examined the quality of water
supplied by urban water supply system and information on waterborne diseases the
vulnerable communities generally suffer round the year. Both the information has
been synthesized to relate health impacts in terms of diseases‟ incidences to water
pollution, poor sanitation and bad hygiene practices. Besides, an evaluation has
also been made to quantify these economic valuations of health effects. Additionally
an attempt has been made to correlate the climatic factors with the number of
waterborne diseases‟ incidences of the selected areas of Dhaka city so as to help
decision makers aware about consequent actions to be taken. Hence this research
will provide appropriate technological and management tools to the urban planners,
4
environmentalists and policy makers to formulate control strategy to preserve water
environment of Dhaka city and take appropriate measures to minimize health
hazards on the most vulnerable group exposed to the water pollution.
1.3. Objectives of the Study
The main objectives of the study are:
Qualitative assessment of water of urban water supply system, sanitation
and hygiene practices of different vulnerable communities of the most
affected areas of Dhaka city as per as waterborne diseases are concerned.
Quantitative assessment of impacts on human health due to water pollution,
sanitation and hygiene practices and economic losses incurred for the
vulnerable communities of Dhaka city.
Evaluation of prevalence rate of specific waterborne diseases due to water
pollution, sanitation and hygiene practices by the population under
observation.
Identification of correlation between selected climatic factors and the worst
waterborne disease‟s incidence of the same selected areas of Dhaka city.
1.4. Scope of the Study
This thesis will focus on how vulnerable communities of selected administrative
areas of Dhaka city are being affected due to poor water quality, inadequate
sanitation and hygiene practices of an individual over a period of time and find out
any probability of correlation of selected climatic factors like rainfall, temperature
and humidity on the diarrhoeal incidences of the population under observation. To
carryout comprehensive study comprising all of the above features and facts require
a considerable amount of time, accessibility, economic and human resources. To
materialize those, “Convenience Sampling Method” was carried out in order to find
out the result. Though this method is non-statistical and also assumes a
homogeneous population which was not true in the practical sense. However it still
provides useful information regarding the population under observation. To augment
the thesis, apart from primary data, a substantial amount of data had also been
taken from secondary and tertiary sources. Again due to time and resource
5
constrain, identification of the most affected areas of Dhaka city as per as
waterborne diseases were concerned would be done from the data collected from
the authenticated secondary sources like International Centre for Diarrhoeal
Disease Research, Bangladesh (ICDDR,B), Dhaka Shishu Hospital(DSH) etc. Here
the four most affected areas have been selected out of twenty one administrative
areas/thanas of earlier setup. Again this paper will assume the low-income and
slums as the vulnerable community affected by desired factors. Efforts will be made
to collect all the relevant information from those areas by conducting questionnaire
survey, sanitary inspection and sample collections. In this regard, “Slums of Dhaka
Metropolitan Area” Map developed by Centre for Urban Studies (CUS) will also be
used as tertiary source in order to pin-point the areas to be explored. Since it has
also been planned to identify the correlation between waterborne diseases‟
incidences of those selected areas and climatic factors prevailing in Dhaka city.
Hence relevant and updated information on climate of Dhaka will also be collected
from Bangladesh Meteorological Department (BMD).
1.5. Limitations of the Study
This study might have following limitations:
Due to non-availability of data on new thanas from the secondary sources,
study areas have been selected based on data of earlier setup i.e. twenty
one administrative thanas of Dhaka city.
In the questionnaire survey, the respondents were found not to maintain any
kind of records at their personal level hence the information provided by
them were more or less from their memories only. They often avoid giving
out their confidential information (e.g. sanitation habit, salary etc.) too.
Since the family members of the households also have food at different
places away from houses; hence it will be difficult to pin point the problem
related with waterborne diseases only.
In questionnaire survey, the most of the respondents had confusions in
identifying cholera, diarrhoea and dysentery diseases and hence all three
have been considered as one i.e. diarrhoea.
Due to paucity of time, limited economic and as well as human resources,
Convenience Sampling Method has been conducted. Moreover it is a non-
probability sampling method and hence statistically is not significant.
6
1.6. Organization of the Thesis
This report presents the analysis, results and findings of the study in six chapters as
shown below:
Chapter 1: Introduction: This chapter contains the general background and present
status of the problem, objectives of the study, scopes of the study and the thesis
organization.
Chapter 2: Literature Review: Compiles all relevant literatures on health impacts
due to lack of adequate water, sanitation, and hygiene practices and climatic
factors.
Chapter 3: Methodologies: It describes the methodologies for this thesis starting
with selection of study areas to the display of information on the thematic map using
GIS, different statistical tools used etc.
Chapter 4: Analysis of Data: Here it provides a description of the analysis process
adopted in this study.
Chapter 5: Results and Discussions: Presents the results of the analysis
accompanied by discussions.
Chapter 6: Conclusions and Recommendations: Summarizes the whole study
and provides some guidelines for further research in this area.
7
CHAPTER 2
LITERATURE REVIEW
2.1 Introduction
Safe, adequate and accessible supplies of water, combined with proper sanitation,
are basic needs and essential components of primary health care. While man has
always recognized the importance of water for internal bodily needs, his recognition
of its importance to health is a more recent development, dating back only about a
century. Health problems related to the inadequacy of water supplies are universal
but generally of greater magnitude and significance in developing countries. While
population under water supply coverage improved significantly during the Water
Supply and Sanitation Decade and after the decade, it has been estimated about
25% of the population in developing countries still does not have access to safe
water (Ahmed and Rahman, 2000). Presently pollution of freshwater (drinking water)
is a problem for about half of the world's population. Each year there are about 250
million cases of water-related diseases, with roughly 5 to 10 million deaths
(GP, 2005). Water pollution causes number of waterborne diseases like diarrhoea,
cholera, typhoid, hepatitis etc.
There has been an extensive debate about the relative importance of water quantity,
water quality, sanitation and hygiene in protecting and improving health (Esrey et
al., 1985; Cairncross, 1990; Esrey et al., 1991). In this regard, children bear the
greatest health burden associated with poor water and sanitation. Diarrhoeal
diseases attributed to poor water supply, sanitation and hygiene account for 1.73
million deaths each year and contribute over 54 million Disability Adjusted Life
Years (DALY), a total equivalent to 3.7% of the global burden of disease (WHO,
2002). This places diarrhoeal disease due to unsafe water, sanitation and hygiene
as the 6th highest burden of disease on a global scale, a health burden that is largely
preventable (WHO, 2002). Other diseases are related to poor water, sanitation and
hygiene such as trachoma, schistosomiasis, ascariasis, trichuriasis, hookworm
disease, malaria and Japanese encephalitis and contribute to an additional burden
of disease. As of 2000 it was estimated that one-sixth of humanity (1.1 billion
people) lacked access to any form of improved water supply within 1 kilometre of
their home (WHO/UNICEF, 2000).
8
In this study, an attempt has been made to assess the health impacts on the most
vulnerable communities of Dhaka city due to limitations in access to adequate pure
water supplied by urban water supply system, sanitation and lack of adequate
knowledge on personal hygiene.
2.2 The Vulnerable Community
2.2.1 Definition
A Community consists of a group of people with common but also conflicting
interests and ideas and different socio-economic and cultural backgrounds
(Ahmed and Rahman, 2000). The identity of the people in the community is shaped
by their history and their socio-economic and environmental conditions. When the
basic services like water supply, improved sanitation, better hygiene education etc.
of a community are less or sometimes even absent- the members of that community
are likely to be vulnerable to various diseases associated with the particular issue.
2.2.2 Considerations
In this study, two socio-economic settings i.e. slum and low-income communities of
selected areas of Dhaka city have been considered:
(a) Slum: CUS (2006) has defined a slum as a neighborhood or residential
area with a minimum of 10 households or a mess unit with at least 25 members with
four of the following five conditions prevailing within it:
Predominantly poor housing.
Very high population density and room crowding.
Very poor environmental services, particularly water and sanitation facilities.
Very low socioeconomic status for the majority of residents. The key
indicator of this is Tk. 5000 per HH income per month based on the urban
poverty line per capita income estimates (Huque, 2008).
Lack of security of tenure.
9
(b) Low-income: A low-income community resides in compact settlements like
tin-shed or tin-roofing with brick walls etc. which generally grow in a cluster on
government and private vacant land having distinct service facilities offered by land
owner and having better socioeconomic condition (above upper poverty line) than
slum as stated by Huque (2008).
2.2.3 Estimation of Population of a Community
In order to analyze the health impacts of a given population of an area, there is a
requirement to calculate the population of that area. Estimation of population of a
community depends on the latest census data of that community. It is customary to
estimate the population of a community between two census periods based on last
census data by applying some conventional methods. In this study, the most widely
used Geometric Progression Method (Ahmed and Rahman, 2000) has been used to
estimate the population of administrative thanas of Dhaka city for the year of 2010
using the population data of 2001 as given in the Table E.1 of Appendix E.
Pf = Pp (1+r)n (2.1)
Where Pf = future population, Pp = present population; r = rate of yearly population
growth and n = number of years to be considered.
2.2.4 Performance of Community Drinking-Water System
If the performance of a community drinking-water system is to be properly
evaluated, a number of factors must be considered. WHO (2008) suggests for usual
practice to include the critical parameters for microbial quality (normally E. coli,
chlorine, turbidity and pH) and for a sanitary inspection to be carried out. In this
thesis, all these factors (Faecal Coliform instead of E. coli ) have been considered in
order to assess water quality of the urban water supply options.
2.3 Water Pollution and Related Issues
2.3.1 Water Pollution
Water pollution occurs when a body of water is adversely affected due to the
addition of large amounts of materials or chemicals to the water in such a way that it
becomes unfit for its intended use. Water pollution is developed by the release of
waste products and contaminants into surface runoff, into river drainage systems,
10
leaching into groundwater, liquid spills, wastewater discharges, eutrophication and
littering.
2.3.2 Types of Pollutants, Sources and Effects
(a) Types of pollutants based on sources: Two types of water pollutants exist:
Point Sources: It occurs when harmful substances are emitted directly into a
body of water. The industries located at Hazaribagh are the best illustrates
point sources water pollution.
Non-point Source: It delivers pollutants indirectly through environmental
changes. Non-point sources are much more difficult to control. Pollution
arising from non-point sources accounts for a majority of the contaminants
in streams and lakes.
(b) Major sources: The major sources of water pollution can be classified as:
Municipal: Municipal water pollution consists of waste water from homes
and commercial establishments.
Industrial: These contaminants include liquid discharges from spent water of
different industrial processes such as manufacturing and food processing.
Agricultural: Agriculture including commercial livestock and poultry farming
is the source of many organic and inorganic pollutants in surface waters and
groundwater.
(c) Causes: There are many causes as identified by DOE for which the Dhaka
city water bodies get polluted everyday (DOE, 2006):
Untreated Sewage Disposal: The existing sewage treatment plant treats
only 40,000 to 50,000 m3 of sewage while the city generates about 1.3
million m3. Most of the rest directly or indirectly reach the surrounding rivers.
The Table 2.1 shows the concentration of heavy metals above the
Environmental Quality Standard (EQS) in the surrounding rivers of Dhaka
city.
11
Table 2.1: Heavy metal concentration in river water of Dhaka city
Sample ID Concentration in mg/l
Al Cd Cr Pb Hg Se Zn
Buriganga River Friendship Bridge 3.27 0.014 0.036 ND1 0.0021 0.001 0.56
Turag River:Amin Bazar 11.884 0.018 0.11 0.394 0.0058 0.0002 1.002
Buriganga River Chandni Ghat 5.396 0.006 0.006 0.25 0.0016 ND 0.984
Lakhya River: Sayedabad WTP Intake point
2.952 0.006 0.028 0.074 0.0032 0.0005 0.246
Balu River Zirani Khal 2.1166 0.006 0.0224 ND 0.0010 ND 1.122
EQS(Drinking water) 0.2 0.005 0.05 0.05 0.001 0.01 5.0
Municipal waste disposal: It is often disposed off into city water bodies. Less
than 50% of generated municipal waste is disposed in the landfill site and a
significant part of the remaining waste goes into the water bodies.
Disposal from water transport vehicles: Disposal of waste, wastewater and
petroleum products from water transport vehicles further pollute the river
water.
Agricultural activities and unsanitary practices: These are like defecating in
the water bodies lead to the contamination of nearby water bodies. The
Table 2.2 shown here is the state of water quality of lake water of Dhaka
city:
Table 2.2: Concentration of water quality indicators of lake water of Dhaka city
Name of the Lake pH
BOD (mg/l)
DO (mg/l)
TS (mg/l)
Coliforms (cfu/100ml)
Dhanmondi lake (near Russell Square)
6.95 1.9 6.1 168 600
Gulshan-Baridhara lake (Near Road No.11 )
7.10 35 0.5 302 1200
Sitadel Lake (East Side ) 6.91 2.6 6.6 92 500
Ramna Lake (beside Ramna Chinese Restaurant)
6.52 25 1.3 87 700
Crescent Lake (East side ) 5.9 2.1 8.3 98 900
EQS2 6.5-8.5 ≤ 3 5 ≥ ≤ 200
Source: DOE (2006)
1 Not detectable 2 Environmental Quality Standard (EQS) of lake water (used as recreation purposes). Five
days BOD at 200C; Coliforms in cfu/100 ml/ (24 hours incubation at 35
0C).
Source: DOE (2006)
12
Unplanned development and encroachment of water bodies: Unplanned
development and encroachment make the water bodies narrower/shorter
and lesser in depth resulting in over flooding the area with polluted water.
(d) Effects of water pollution: Water, sanitation and hygiene have important
impacts on both health and disease. Contamination of food, hands, utensils and
clothing can also play a role, particularly when domestic sanitation and hygiene are
poor. The WHO has made a fact sheet of over 20 water-related-diseases out of
which Cholera, Diarrhoea, Scabies, Schistosomiasis, Trachoma/ eye infections,
Typhoid and Paratyphoid are noteworthy for Dhaka city dwellers.
Cholera: Cholera outbreaks generally occur in any part of the city where
water supplies, sanitation, food safety and hygiene practices are
inadequate. Overcrowded communities like slum areas and other low cost
residential areas with poor sanitation and unsafe drinking-water supplies are
most frequently affected.
Diarrhoea: Water contaminated with human faeces for example from
municipal sewage, septic tanks and latrines is of special concern. Animal
faeces also contain microorganisms that can cause diarrhoea. This
happens to be a regular phenomenon in Dhaka city right after any flood
episode.
Scabies: Scabies is a contagious skin infection that spreads rapidly in
crowded conditions and is very much available in the slums. Personal
hygiene is an important preventive measure and access to adequate water
supply is important in control.
Trachoma: It is an infection of the eyes that may result in blindness after
repeated re-infections. It is the world's leading cause of preventable
blindness and occurs where people live in overcrowded conditions with
limited access to water and health care. Trachoma spreads easily from
person to person and is frequently passed from child to child and from child
to mother within the family.
13
Typhoid and Paratyphoid Enteric Fevers: Typhoid and paratyphoid fevers
are infections caused by bacteria which are transmitted from faeces to
ingestion.
2.3.3 Background Level of Immunity
The effects of exposure to pathogens are not the same for all individuals or, as a
consequence, for all populations. Repeated exposure to a pathogen may be
associated with a lower probability or severity of illness because of the effects of
acquired immunity. For some pathogens (e.g., HAV), immunity is lifelong, whereas
for others (e.g., Campylobacter), the protective effects may be restricted to a few
months to years. On the other hand, sensitive subgroups (e.g., the young, the
elderly, pregnant women and the immuno-compromised) in the population may have
a greater probability of illness or the illness may be more severe, including mortality.
2.4 Water Quality and Standards
2.4.1 Water Quality
Since the quality of water is affected by both man and natural activities, hence pure
water is not available in nature and however nor it is desirable for water supply.
Some of the water quality parameters respond to human senses of sight (turbidity,
color), taste (salty, offensive) and smell (odour) but the presence of pathogens and
poisons in drinking water cannot be identified by human senses. The most important
parameter of drinking water quality is the bacteriological quality, i.e. presence of
pathogenic organisms. The water borne diseases are caused by the ingestion of
pathogens with drinking water. Control of the most water-borne diseases is hinged
upon availability of enough water for domestic and personal cleanliness or sound
hygiene practices. The water-borne diseases can therefore also be described as
water-washed diseases.
2.4.2 Water Quality Standards
Water for public water supplies should be drawn from the best available source for
cost-effective treatment of water. The degree and method of treatment to make
water potable and attractive to the consumers depend on the characteristics of the
raw water. Table 2.4 shows the recommended water quality standards for surface
water sources for development of water supply in Bangladesh.
14
Table 2.4: Bangladesh water quality standards for surface water for water supply.
Water Quality Parameters
Unit
Values for Water Supply by
Disinfection only Conventional
Treatment
pH - 6.5 – 8.5 6.5 – 8.5
BOD mg/l ≤ 2 ≤ 3
DO mg/l ≥ 6 ≥ 6
Total Coliform cfu/ 100 ml ≤ 50 ≤ 5,000
Source: Ahmed and Rahman (2000)
However the list of parameters presented in this table is not comprehensive; it
provides a general guideline for selection of a source for water supply. Bangladesh
developed the first water quality standards in 1976 based on the WHO 1971
International Drinking Water Standards. The Ministry of Environment and Forests,
Government of Bangladesh adopted comprehensive water quality standards for
drinking water by Gazette notification in 1997 as Environmental Conservation Rules
under the Environmental Conservation Act, 1995. Part of the Bangladesh Drinking
Water Standards, 1997 with WHO guideline values, 2004 are presented in Table
2.5.
Table 2.5: Bangladesh standard for drinking water
Aspects Parameters Bangladesh, ECR 1997,
Schedule 3(B)
WHO guideline values, 2004
Physical pH 6.5-8.5 -
TDS (mg/l) 1000 1000
Color (Hazen Unit) 15 15
Turbidity (NTU) 10 5
Odor Odorless Odorless
Chemical Hardness (as CaCO3) (mg/l) 200-500 -
Chlorine (Residual) (mg/l) 0.2 0.2
Nitrate (NO3) (mg/l) 10 50
Ammonia (mg/l) 0.5 1.5
Iron (mg/l) 0.3-1.0 0.3
Arsenic (mg/l) 0.05 0.05
Microbial TTC (cfu/ 100 ml) 0 0
Faecal Coliform (cfu/ 100 ml) 0 0
E.coli (cfu/ 100 ml) 0 0
Source: Ahmed and Rahman (2000)
15
2.5 Water Supply
2.5.1 Objectives of Water Supply
The broad objectives of any water supply system are:
Supply water in adequate quantity: means that the water supplied to the
community should meet all the requirements for water and be available when
required.
Supply safe and wholesome water to the consumers: Here water is safe
when it does not cause any harm upon consumption. Whereas the wholesome
water is unpolluted, significantly free from toxic substances as well as excessive
amounts of mineral and organic matters that may impair its quality.
Make water easily available to consumers: that the water is accessible and
within easy reach of the consumers so as to encourage the use of adequate
water for personal and household cleanliness.
2.5.2 Pattern of Urban Water Supply for Vulnerable Group
Pattern of Urban water supply pattern for vulnerable communities of Dhaka city was
found broadly in two types:
(a) Community Type DWASA Supply: These have some different patterns:
Simple house connection where all communities collect water.
Flexible pipe carrying water from nearest legal water point by illegal method.
Hand pump fitted with WASA main line and
Conventional public stand post with platform and drains. Some of them have
a reservoir to temporarily store water during non-supply hours.
(b) Shallow Tubewell (STW): Most of the time, these are installed by various
NGOs. However, during the field survey it was found that there were some slum
people who borrow water from nearby middle class community having reservoirs of
their own too.
16
2.6 Domestic Water Supply
2.6.1 Domestic Water and Its Usage
As per WHO‟s guidelines for drinking-water quality, domestic water has been
defined as being 'water used for all usual domestic purposes including consumption,
bathing and food preparation' (WHO, 2008). White et al. (1972) suggested that three
types of use could be defined in relation to normal domestic supply:
Consumption (drinking and cooking)
Hygiene (including basic needs for personal and domestic cleanliness)
Amenity use (for instance car washing, lawn watering).
Thompson et al. (2001) suggest a fourth category can be included of 'productive
use' which was of particular relevance to poor households in developing countries.
Productive use of water includes uses such as brewing, animal watering,
construction and small-scale horticulture. The first two categories identified by White
et al. (1972) i.e. „consumption‟ and „hygiene‟ have direct consequences for health
both in relation to physiological needs and in the control of diverse infectious and
non-infectious water-related disease. The third category- „amenity‟ may not directly
affect health in many circumstances. Productive water may be critical among the
urban poor in sustaining livelihoods and avoiding poverty and therefore has
considerable indirect influence on human health (Fass, 1993; Thompson et al.,
2001).
(a) Consumption: Water is a basic nutrient of the human body and is
critical to human life. It supports the digestion of food, adsorption, transportation and
use of nutrients and the elimination of toxins and wastes from the body (Kleiner,
1999). The per capita water consumption is greatly influenced by various factors.
Some major factors can be cited below:
Population Distribution
Climatic Conditions
Quality of Water
Pressure of Water
17
Water Rates and Metering
Nature of Supply
Water Source Distance
Availability of an Alternative Source
Sanitation
The volume of water required for hydration for the most vulnerable in tropical
climates as given in the Table 2.6 and higher in conditions of raised temperature
and/or excessive physical activity.
Table 2.6: Volumes of water required for hydration for the most vulnerable in tropical climates
Individual Type
Volumes (litres/day)
Average conditions
Manual labour in high temperatures
Total needs in pregnancy/lactation
Female adults
2.2 4.5 4.8 (pregnancy) 5.5 (lactation)
Male adults 2.9 4.5 -
Children l.0 4.5 -
Source: Howard and Bartram (2003)
(b) Hygiene: The need for domestic water supplies for basic health
protection exceeds the minimum required for consumption (drinking and cooking).
Additional volumes are required for maintaining food and personal hygiene through
hand and food washing, bathing and laundry. Poor hygiene may in part be caused
by a lack of sufficient quantity of domestic water supply (Cairncross and Feachem,
1993). The diseases linked to poor hygiene include diarrhoeal and other diseases
transmitted through the faecal-oral route; skin and eye diseases, in particular
trachoma and diseases related to infestations, for instance louse and tick-borne
typhus (Bradley, 1977; Cairncross and Feachem, 1993).
2.6.2 The Links Between Water Supply, Hygiene and Disease
An effective way to inform decision-making is to categorize pathogens /diseases in
relation to the broad mode of transmission. Bradley (1977) suggests that there are
four principal categories that relate to water and which are not mutually exclusive:
18
Water-borne caused through consumption of contaminated water (for
instance diarrhoeal diseases, infectious hepatitis, typhoid, guinea worm).
Water-washed caused through the use of inadequate volumes for
personal hygiene (for instance diarrhoeal disease, infectious hepatitis,
typhoid, trachoma, skin and eye infections).
Water-based- Here an intermediate aquatic host is required (for instance
guinea worm, schistosomiasis).
Water-related vector spread through insect vectors associated with water
(for instance malaria, dengue fever).
While a full analysis of improved water and sanitation services would consider
pathogens passed via all these routes, the present study focuses on water-borne
and water-washed diseases. This is partly because, at the household level, it is the
transmission of these diseases that is most closely associated with inadequate
water supply, poor sanitation and lack of hygiene. Moreover, water-borne and water-
washed diseases are responsible for the greatest proportion of the direct-effect
water and sanitation-related disease burden.
2.7 Sanitation
2.7.1 Definition and Objectives of Sanitation
The word sanitation actually refers to all conditions that affect health and according
to WHO may include things as food sanitation, rainwater drainage, solid waste
disposal and atmospheric pollution (Ahmed and Rahman, 2000). The principal
objectives of providing sanitation facilities are:
To have improved public health
To minimize environmental pollution
Sanitation can contribute greatly to preventing the spread of infectious diseases
through transmission of disease causing agents as is the case when pathogenic
organisms from the excreta of an infected person are transmitted to a healthy
person as can be seen in Figure 2.1. It is important to understand that the
improvement of health is not possible without sanitary disposal of human excreta.
However, neither sanitation nor water supply alone is good enough for health
19
improvement. It is now well established that health education or hygiene promotion
must accompany sufficient quantities of safe water and sanitary disposal of excreta
to ensure the control of water and sanitation related diseases. This interrelationship
was shown by Veenstra, (1994) during his lecture on urban sanitation as shown in
the Figure 2.2.
2.7.2 Relationships Between Water, Sanitation, Hygiene and Diarrhoea
Diseases primarily transmitted through the faecal-oral route (Figure 2.1) include
infectious diarrhoea, typhoid, cholera and infectious hepatitis. Transmission may
occur through a variety of mechanisms, including consumption of contaminated
water and food as well as through person-person contact (Bradley, 1977). These
are dealt with together here, in order to emphasize the importance of local disease
patterns rather than applying generic models. The available evidence from health
studies suggests that interventions are likely to be locality-specific and are
determined by timing and the interaction between different factors.
Figure 2.1 Disease transmissions and sanitation (Ahmed and Rahman, 2000)
Excreta
Water
Hands
Insects
Soil
New Host
Milk
Vegetable
Food
San
itatio
n F
acili
ties
Personal Hygiene
Foot wear
Sanitary Latrines
Food Sanitation TW/Water Treatment
Legend
20
Other factors apart from water and sanitation facilities and hygiene behaviors may
significantly influence diarrhoeal disease. For example breast-feeding has been
noted in several studies as being protective against diarrhoeal disease
independently of other interventions (Al-Ali et al., 1997; Vanderslice and Briscoe,
1995).
The timing of hand washing may be important. Experience suggests that the most
critical times are following defecation and before eating. Curtis et al. (2000) suggest
that the critical time is post-defecation rather than before eating, while other studies
suggest that the reverse is true in some situations (Birmingham et al., 1997).
Stanton and Clemens (1987) found reduction in diarrhoea incidence among young
children was influenced by maternal hand washing prior to food preparation. A
number of studies suggest that hand washing with soap is the critical component of
this behavior and that hand washing only with water provides little or no benefit.
Hoque et al. (1995) found that use of mud, ash and soap all achieved the same
level of cleanliness with hand washing and suggested that it is the action of rubbing
of hands that was more important than the agent used.
Health Education Or
Hygiene Promotion
Sanitation
Improvement of
Health
Water Supply
Figure 2.2 Interrelationship between water, sanitation and health education
(Veenstra, 1994)
21
2.7.3 Relationships Between Water, Hygiene and Other Infectious Diseases
Infectious diseases of the skin (a sub-set of water-washed diseases) and trachoma
are amongst the diseases on which water quantity would be expected to exert
significant influence. Trachoma is the most extensively studied disease, given its
relatively high impact on health. One study in southern Morocco that showed a
difference in incidence in trachoma between the use of less than 5 litres per day and
use of more than 10 litres per day. Prüss and Mariotti (2000) also note six studies
that showed a positive relationship between increased access to water and reduced
incidence of trachoma, with a median reduction of 27%, with a range of 11-83%
reduction. In most studies, distance from primary water source to home appears to
be the most significant water supply factor influencing trachoma.
2.7.4 Quantity and Accessibility
The WHO/UNICEF Joint Monitoring Programme has described reasonable access
as being 'the availability of at least 20 litres per person per day from a source within
one kilometre of the users dwelling' (WHO/UNICEF, 2000). However, it should be
noted that this definition relates to primarily to access and should not necessarily be
taken as evidence that 20 litres per capita per day is a recommended quantity of
water for domestic use. It is evident that increased accessibility equates to
increased volumes of water used (Esrey et al., 1991). Reviewing several studies on
water use and collection behavior, that there is a clearly defined general response of
water volumes used by households to accessibility, shown in Figure 2.3. Once the
time taken to collect water source exceeds a few minutes (typically around 5
minutes or 100m from the house), the quantities of water collected decrease
significantly. This graph contains a well-defined „plateau‟ of consumption that
appears to operate within boundaries defined by distances equivalent to around 100
to 1000m or 5 to 30 minutes collection time. There is little change in quantity of
water collected within these boundaries (Cairncross and Feachem, 1993). Beyond
distance of one kilometre or more than 30 minutes total collection time, quantities of
water will be expected to further decrease, in rural areas to a bare minimum where
only consumption needs can be met. In urban areas, where water supplies may be
close but total collection times are very high, greater volumes may be collected that
will support hygiene, although the overall impact on household poverty is significant
(Aiga and Umenai, 2002).
22
Figure 2.3: Graph of travel time (in minutes) versus consumption (WELL,1998)
As noted by WELL (1998), the first priority is to ensure that households reach the
plateau (Figure 2.3), that is to have access to an improved water source within one
kilometre, which corresponds to the current definition of reasonable access used in
assessing progress in global coverage with water supply and sanitation
(WHO/UNICEF, 2000). Beyond this, unless water is provided at a household level,
no significant changes in water quantities collected will be noted.
2.7.5 Hazards of Water Supply
From the generic flow chart of both urban water supply system and domestic water
supply system as given Figure 2.4, it can be seen that there could be number of
steps involved in exposure of pathogens to the community. The following steps
demonstrate such pathways of pathogens from sewage to consumers
(Azam, 2005):
Pathogen concentration in fresh sewage.
Mixing of sewage with drinking water through leakages, especially during low
pressure condition or interruption of supply in case of intermittent supply.
Transportation of pathogens, survival in water against the residual chlorine
level.
Addition of extra pathogens at supply end due to unsanitary condition and
unhygienic practices.
Pathogen concentration in water sources at the point of consumption.
Return trip travel time
Wa
ter
Co
nsum
ption
(lp
cd
)
23
Figure 2.4: Generic flow diagram of water supply system
Volume of un-boiled water consumed by the population, including person-to person
variation in consumption behaviour and especially consumption behaviour of at-risk
groups. Hence a kind of precaution is always taken at domestic level in terms of
treatment (boiling of water, using disinfection tablets etc.) in order to avoid such
contamination.
2.8 Dhaka and Its Water Supply System
2.8.1 Growth of Dhaka
Dhaka is the capital of Bangladesh. The present population of Dhaka city is now
about 12 million and the projected population by 2025 is about 22 million. It is now
the 7th largest city in the world and by 2020 it will be the 2nd largest city in the world
(Paul, 2009). Actually this particular city passes through various era namely pre-
Ground Water (GW) Surface Water (SW)
GW Extraction Abstraction of SW
Treatment
Disinfection
Storage
Distribution
Collection
Treatment
Storage
Usage
Consumption (drinking and cooking)
Hygiene (including basic needs for personal and domestic cleanliness)
Productive use (brewing, animal watering, construction and small-scale horticulture.)
Amenity use (for instance car washing, lawn watering).
Urban Water
Supply System
Domestic Water
Supply System
24
Mughol Era (before 1608), Mughol Era (after 1608 to 1757), under The East India
Company (1757-1858), under the British (1858-1947), as provincial capital of East
Pakistan (1947-1971) and lastly as capital of independent Bangladesh. During these
times the demographic layout of Dhaka city changed in many folds along with its
population. After the independence of Bangladesh, the urbanization activities have
been achieving tremendous growth for the needs of the newly independent
country‟s capital. The city began to expand in all directions.
On the other hand this Metropolitan City with 360 sq. km has to bear 9.3 million
people with about 6% population growth (DCC, 2009) as estimated by DCC. A water
supply Master plan for the Dhaka city was prepared in 1992 for an area of about 360
sq. km, which has now become redundant as the prediction on population and water
demand has been surpassed by huge margin (Al-Mamoon, 2006). According to the
research conducted by Population Science Division of Dhaka University, in every
year, about 7 lacs and 80 thousands of people are newly added to the existing
trends. Unfortunately the other utility services could hardly keep the pace with this
population growth. As a result environmental degradation has taken place.
2.8.2 Dhaka Water Supply and Sewerage Authority (DWASA)
(a) Brief history: Dhaka Water Supply and Sewerage Authority (DWASA) was
established for proving two major emergency services namely potable water supply
and hygienic and modern sewerage system for Dhaka, one of the rapidly expanding
city in November 1963. Under the ordinance XIX of 1963, DWASA started
functioning in Dhaka Municipality with only 8 Lac populations and now its
operational area includes both Dhaka city and Narayanganj Municipality with more
than 12.5 million people. In 1986, another important responsibility for drainage
system of Dhaka city has been shifted to DWASA. Based on the tremendous
geographical expansion and population growth over the last two decades, DWASA
has been reorganized by DWASA Act, 1996 and according to this act, presently it is
being run as a service oriented commercial organization.
(b) Responsibilities: The major responsibilities and functions of DWASA are:
Construction, operation, improvement and maintenance of the necessary
infrastructures for collecting, treating, preserving and supplying potable
water to the public, industries and commercial concerns,
25
Construction, operation, improvement and maintenance of the necessary
infrastructures for collecting, treating and disposing domestic sewerage and
industrial wastes.
Construction, operation, improvement and maintenance of the necessary
infrastructures for drainage facilities of the City.
According to Citizen Charter of DWASA, it provides the water connections to the
slum communities through Community Based Organization (CBO) or through land
owners subject to reception of such applications from them.
(c) Service area: At present the service area of DWASA extends from Mirpur
and Uttara in the North and to Narayanganj in the South. For better operation,
maintenance and customer care, the total service area of DWASA has been divided
into 11 geographic zones, which includes 10 in Dhaka city and 1 in Narayanganj.
Figure 2.5 shows the thematic map by each service zones of Dhaka city.
Figure 2.5 DWASA service areas in DMPA
7
1
6
2
3
5
4 8
9
10
26
(d) Infrastructures and establishment: Table 2.7 shows the data of DWASA till
October 2009:
Table 2.7 Infrastructures and establishment of DWASA
Ser No Description Acct Unit Qty
1. Water Treatment Plant Numbers 4
2. Deep Tubewell Numbers 533
3. Water production capacity MLD 2,177.91
4. Actual Water production MLD 2,032.04
5. Water Line Kilometer 2533.73
6. Water Connections Numbers 2,77,590
7. Sewer Line (2008-09) Kilometer 882
8. Sewer Connections Numbers 61,349
9. Storm Water Drainage Line Kilometer 275
10. Box Culvert Kilometer 9
11. Open Canal Kilometer 65
12. Drainage System (upto July 2004 & including box culvert and open canal)
Kilometer 303.08
Source: DWASA (2009)
2.8.3 Water Supply Situation DWASA serves a total of 14.15 million people of Dhaka Metropolitan Area and
Narayangong. This service area is projected to increase to 17.2 million by year 2025
while another 4.4 million will be staying within Dhaka Metropolitan Area but in areas
presently not served by DWASA. A sizeable number of population (estimates vary
from 10 to 60%) living in the DWASA service area are living in slum
areas (ADB, 2008). To serve such a huge population of Dhaka city is now
becoming a challenge for DWASA. Table 2.8 shows that the DWASA is heavily
dependent on groundwater with more than 87% of total water production coming
from groundwater source.
Table 2.8: Source wise water production of DWASA in October 2009.
Source Production Capacity
Actual Production Source-Wise % of Production MLD % of Capacity
Ground Water 1,878.74 1,782.37 94.87% 87.71%
Surface Water 299.17 249.67 83.45% 12.29%
Total: 2,177.91 2,032.04 93.30% 100.00%
Source: DWASA (2009)
27
But ground water depletion rate is more than 3m/yr which is alarmingly high
(Al-Mamoon, 2006; Paul, 2009). As a result no further abstraction from upper
aquifer (100-200m) is viable. However, DWASA has already started to draw water
from deep aquifer (> 300m) (DWASA, 2010). On the other hand the water quality of
peripheral rivers and lakes of Dhaka city are polluted in the highest order. Figure 2.6
shows the prediction of population and water demand in Dhaka urban areas basing
on the present supply i.e. 1500 mld (Al-Mamoon, 2006).
Figure 2.6 Prediction of population and water demand in Dhaka city.
2.8.4 Water Quality Monitoring System According to DWASA sources, the groundwater and surface water as extracted are
being monitored and tested regularly by its own Quality Control and Research
Division. Saha, (2001) noticed that groundwater supplied by the DWASA is within
the acceptable limit of WHO guidelines. It was also found during testing of water
from WASA groundwater pump points at number of locations in Dhaka city. DWASA
conducts number of tests on important parameters like pH, turbidity, alkalinity,
residual chlorine, faecal coliform etc. of water in the quality control and research
laboratory of the organization. In addition, groundwater samples from Deep
Tubewells (DTW) are also tested for arsenic every three months and river water
samples are tested for chromium and aluminum every six months (Azam, 2005).
Figure O.1 of Appendix O shows the distribution of DTWs and water bodies around
the selected areas of Dhaka city. According to DWASA, necessary mitigation
measures are adopted if there is any change in the quality of water.
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
2005 2010 2015 2020 2025
Year
ML
D
0
5
10
15
20
25
Mill
ion
Water Demand (mld) Shortfall(mld) in comparison with present water supply Population (million)
28
2.9 Economic Valuation of Diseases
2.9.1 General
There is no denying that water pollution lead to serious negative impacts on health
and various economic goods and services. The physical evidence is convincing.
The valuation of these impacts, however, has frequently been ignored because it
was thought that either:
It is too difficult to establish direct cause-effect relationships.
Placing monetary values on those effects, either health or productivity was
not feasible.
Economic valuation of health impacts due to consumption of water of urban water
supply and associated sanitation, hygiene and climatic factors was one of the
objectives of this thesis. Here, field data were used to make the valuation using
standard methods and statistical tools. This valuation can be defined as an attempt
to quantify and express in monetary terms the full value of diseases as affected due
to consumption of water of urban water supply and associated poor sanitation and
hygiene practices.
2.9.2 Importance of Monetary Valuation
To compare benefits and costs- as planning process is influenced by
economic analysis (CBA).
To set priorities. If one can compute the expected benefits of different
actions, and then one compares this to the costs of each action, this information
is a critical aid to setting priorities for action. The benefit of an analysis and the
use of quantitative (and, in some cases, qualitative) results is that it helps
societies to make more rational decisions on allocating scarce financial
resources.
Economic valuation helps to bring the environment into decision-making
process.
29
2.9.3 The Major Economic Impacts of Pollution
There are four most important major economic impacts; these are:
Health impacts are the most important and the ones that receive the most
attention. Also, it is often easier to estimate economic costs of health outcomes;
this information is useful in getting the attention of decision makers.
Productivity impacts are often also very important and can be estimated
fairly easily. If individuals or firms need to install special equipment or take
special measures to protect themselves from pollution, these are measurable
economic costs. If polluted water reduces the productivity of natural systems
(crop or fishery production, for example), these are additional productivity costs.
Also, in some situations, pollution (especially air pollution) may be so critical
that industries are closed or transportation is restricted. Both of these steps
impose important economic and social costs on society.
Ecosystem impacts may also occur when such things as underground
aquifers are contaminated, or vegetative areas die due to pollution. Ecosystem
impacts are harder to measure and value and the true impact may not be felt for
many years. Often they are included in a qualitative manner.
Aesthetic impacts.
2.9.4 Techniques to Place Monetary Values on Environmental Impacts
(a) Market based methods:
Production function approach
Cost of illness approach
Cost-based approaches
(b) Cost of illness approach:
Costs of air/water pollution estimated by looking at costs of human health
impact. Dose-response function identifies relationship between level of pollutant
and degree of health effect (water quality and diarrhoea). Here value health
effect based on cost of illness, including:
30
Direct cost of diseases:
Home treatment cost: These are for extra fooding and/or nursing
costs.
Transportation cost: For availing doctor/clinic/hospital support or/and
purchasing medicine at a long distance etc.
Doctor‟s fee: Single doctor visit charge.
Medical expenses: These are expended after visiting doctors for
purchasing medicines.
Indirect cost of Diseases
Parent‟s work lost (when both/either of them were patient)
Parent‟s work lost due to child disease.
Parent‟s leisure lost due to child disease.
Applicability: Value health costs of water and air pollution.
Limitations:
Dose-response functions not available locally.
Does not measure WTP to avoid illness.
2.10 Prevalence Rate (PR)
2.10.1 Importance
Prevalence Rate (PR) is a kind of tool to identify the severity of any particular issue.
In this study, PR of waterborne diseases of the selected areas of Dhaka city has
been used in order to identify the state of vulnerability of the surveyed population.
The greatest waterborne risk to health in most cases is the transmission of faecal
pathogens, due to inadequate sanitation, hygiene and protection of water sources.
Hence population density, state of water sources including its availability, sanitation
system and hygiene practices are the major concerned. Where the population
density is high and sanitation is inadequate, unprotected water sources in and
around the temporary settlement are highly likely to become contaminated. If there
is a significant prevalence of disease cases and carriers in a population of people
31
with low immunity due to malnutrition or the burden of other diseases, then the risk
of an outbreak of waterborne disease is increased. That is why the higher PR value
signifies the higher vulnerability of population to the waterborne diseases.
2.10.2 Formula Used in PR
In this study Equation 2.2, 2.3, 2.4 and 2.5 were used to identify the PR of different
diseases out of 1000 people.
PR Based on Individual Group (PRIG):
(2.2)
PR Based on Group Total (PRGT):
(2.3)
PR of Particular Group Based on Total Population (PRTP):
(2.4) PR of Total Population (PR):
(2.5)
2.11 Statistical Analysis Tools
During analysis following statistical tools have been used to obtain objectives of this
study:
2.11.1 Arithmetic Mean: If there are n numbers of items x1, x2, x3 . . . . xn then the
average value x is given in the Equation 2.6.
n
xxxxx n
....321
(2.6)
PR=Total Number of Incidences×1000
Total Population Surveyed
PRIG=Total Number of Incidences Based on Individual Group×1000
Total Surveyed Population of That Individual Group
PRTP=Total Number of Incidences Based on Individual Group×1000
Total Population Surveyed
PRGT=Total Number of Incidences Based on Individual Group×1000
Surveyed Group Total Population
32
2.11.2 Grade Point Average (GPA): If there are n numbers of items x1, x2, x3 . . . xn
and having y1, y2, y3 . . . . yn grade points respectively; then the GPA is given in the
Equation 2.7.
n
i
i
n
i
ii
y
yx
GPA
1
1
2.11.3 Standard Deviation: The standard deviation is a measure of how widely
values are dispersed from the average value (the mean). The formula used for
unbiased method can be shown in the Equation 2.8.
)1(
)( 2
n
xx
Where x is the sample means of n number of x data.
2.11.4 Correlation Coefficient (Cr): The correlation coefficient to determine the
relationship between two properties. The formula can be shown in the Equation 2.9.
22),(
)()(
))((
yyxx
yyxxCr yx
Where x and y are the sample means of two data sets.
(2.7)
(2.8)
(2.9)
33
CHAPTER 3
METHODOLOGIES
3.1 Introduction
The objective of this research is to study the health impacts of urban water supply
on the vulnerable communities of selected areas of Dhaka city. Here the data of
twenty one administrative thanas of Dhaka city has been considered and from there
only the four most affected thanas have been selected for this study. To attain the
main objective, effort has been made to carry out qualitative assessment of urban
water supply system, sanitation and hygiene practices of different vulnerable
communities of the most affected areas of Dhaka city. Moreover the impacts of
those factors have been quantified in terms of number of incidences and assess the
economic losses incurred. Since climatic factors play a vital role in case of per
capita consumption of water and other microbiological organisms‟ growth, hence an
effort has also been made to identify the correlation between selected climatic
factors and the worst waterborne disease‟s incidence of the same selected areas of
Dhaka city. These all are used to develop overall grading chart showing prevailing
waterborne diseases‟ profiles and costs of diseases with respect to selected areas,
communities and urban water supply options. These results have also been shown
as thematic maps of Dhaka city using Geographical Information System (GIS)
software.
3.2 Methodologies
Since the causes of waterborne diseases are not limited to urban water supply
system/options alone only, rather cover wide spectrum like food, sanitation,
personal hygiene, climate and other behavioral factors too. Hence, for this thesis
work, health impacts of vulnerable people due to water provided by DWASA and
associated sanitation, hygiene and climatic factors have been considered. The
methodologies for this study have been shown in the Figure: 3.1.
(a) Initially existing secondary data related with waterborne diseases of all the
administrative areas of Dhaka city as preserved and maintained by authenticated
sources has been collected in order to identify the health state of Dhaka dwellers as
per as waterborne diseases are concerned and rank them basing on the severity.
34
(b) Since above data would represent only the number of patients reporting
and/or hospitalized without any reference to baseline data. Hence population of
respective areas of Dhaka city for the year of 2010 has been incorporated to
generalize the data as such. Here population data of 2001 has been used as base
data in order to find out the population for the year of 2010 basing on growth rate of
State of Dhaka city as per waterborne diseases
Collection of waterborne diseases related data from Secondary Sources
Identification of the most affected areas
Selection of locations and time for the top 4 most affected areas
Vulnerable Population
Climatic Data from BMD
Urban water supply
Sanitation Practices
Hygiene practices
Correlation of Climatic factors-
Waterborne diseases
Health impacts in terms of number of patients of different
waterborne diseases
Costs of main waterborne diseases
GIS Representation of relevant data in
thematic maps
Figure: 3.1 Methodology diagram
Prevalence Rate of Non-reporting
Incidences
35
6% as stated by DCC (2009). Due to time and resource constrains only the top 4
most affected administrative areas has been selected.
(c) “Slum-map” developed by CUS (Figure 3.2) has been studied in order to
locate the vulnerable people residing at various places of those selected areas of
Dhaka city as per the considerations described in Section 2.2.2 and to identify urban
water supply options as explained in Section 2.5.2. For sampling of population,
“Convenience Sampling Method” was carried out in order to materialize time, money
and other resources related constrains. Again to select better time frame for primary
data collection, the records of waterborne diseases‟ incidences of those selected
areas of Dhaka city have been studied and hence a general monthly trend has been
developed.
(d) To identify the impacts, the primary data has been composed of all the
relevant questionnaires, sanitary inspection (SI) and water samples collection.
Based on all these data results are shown with respect to sample areas, community
types and urban water supply options and draw overall conditions as a result of a
particular issue and associated health impacts and costs of diseases thereof.
Additionally data on climatic factors have been collected from BMD to formulate
correlation among them. Here the climatic factors selected for this thesis work are
monthly rainfall, humidity and temperature (maximum, minimum and average) for
Dhaka station only. Monthly trends of those meteorological factors and diarrhoeal
incidents have been superimposed and statistical tools have been used to find out
the correlation.
(e) Finally recommendations are made for monitoring, improving water quality,
sanitation and hygiene practices and enforcement programs. Additionally number of
thematic maps has been generated using GIS software like ArcGIS (ArcCatalog and
ArcMap) to show the result on Dhaka city perspective so as to help the decision
maker in identifying areas of improvement.
3.3 Design Procedure
In this study health impacts resulting from urban water supply was assessed for
slum and low-income communities of selected areas of Dhaka city by collecting
relevant information from field. This section provides chronological description of the
36
Figure 3.2 Slums of Dhaka metropolitan area (CUS, 2005)
Mirpur
Uttara
Gulshan
Tejgaon
Mohammadpur
Hazaribagh
Kamrangirchar
Rampura
Banani
Badda
Khilkhet
Shyampur
37
methodologies used in this study. To assess the health impacts and costs valuation
of the diseases, necessary methods/statistical analysis tools have been used.
3.3.1 Selection of Vulnerable Communities
It is one of the most important issues on which the whole study has been based on.
The selection of vulnerable communities started with the evaluation of secondary
information as attained from ICDDR,B and DSH and personal contact with experts
and scientists in this regard. Both the institution referred that most of the time it was
the low-income and slum people who visited them frequently round the year. Hence
in this study, these two communities have been referred as vulnerable communities
and their considerations have been given in the Section 2.2.2.
3.3.2 Vulnerability Score
In order to find the state of vulnerability of the given community, the percentage of
exposure for a particular disease with respect to some predefined factors/sub-
factors have been considered. In this study a total 10 points have been assigned for
each factors/sub-factors for their vulnerability. Each increment of 10% in exposure
accounts for 1 point increment in vulnerability score and intermediate values are
calculated proportionately as such. The Table 3.1 shows such vulnerability score
and state of the vulnerability. As it can be seen in the table that vulnerability of the
community increases with the increase of percentage of exposure. However most of
the case 0% exposure means “No data” was found at the time of survey.
Table 3.1 Vulnerability score and state of vulnerability.
Serial Exposure to Particular Disease (%)
Vulnerability Score
State of Vulnerability
1. 10 1 Low
2. 20 2
3. 30 3
Medium 4. 40 4
5. 50 5
6. 60 6 High
7. 70 7
8. 80 8
Very High 9. 90 9
10. 100 10
38
Again, the basic data of Table 3.2 has been used in order to grade the community,
selected areas and urban water supply options and to represent state of the
selected areas in the thematic maps as per color code.
Table 3.2: Basic data for grading and representation.
Vulnerability Score Range
Grade Point Grade Representation
Color Code Use
≥ 8 to 10 4 Very high In thematic map
≥ 6 to <8 3 High
≥ 3 to <6 2 Medium
≥ 0 to <3 1 Low
3.3.3 Identification of Urban Water Supply Options
The method of selection of water points was primarily based on reconnaissance
survey conducted in Gulshan and Mirpur areas. There were private owned water
points and WASA pump house from where people need to pay for the services.
Urban water supply pattern as identified in slum areas were discussed in Section
2.5.2. The water supply options found in the study areas are given in the Table 3.3.
Table 3.3: The water supply options found in the study areas.
Serial Description of Options Community Using Options
1. Piped water supply with reservoir Low-income
2. Piped water supply without reservoir Low-income/slum
3. Hand pump connected to supply line Low-income/slum
3.3.4 Field Survey
(a) Questionnaires: During questionnaires survey, effort was made to
collect all the relevant information leading to the attainment of the thesis objectives.
A detailed Questionnaire Survey Form (QSF) was made right after the
reconnaissance survey and appended as Appendix A. The form contained as much
as 28 questions of different types in order to acquire following general information
regarding:
Community type i.e. slum or low-income groups.
Economic conditions.
Sanitation and hygiene practices.
Accessibility to urban water supply and their patterns.
Occurrences of various waterborne diseases etc. during last one year.
39
Costs they were to bear as a result of waterborne diseases.
Here each question acted as qualitative aspect of either urban water supply or
sanitation or even hygiene related matter of the vulnerable people and quantitative
aspect i.e. health impacts of the same in terms of number of incidences/occurrences
of waterborne diseases those had taken place last one year. The QSF was also
used for the assessment of prevalence rate of mostly affected waterborne diseases
among the communities for which they were to pay the most. During the survey, the
QSF revealed three such most affected waterborne diseases on which the total
calculation of the thesis has been based on; these are:
Diarrhoea
Typhoid.
Eye Infections
Here overlap of water consumption was not considered in this study because people
especially workers or laborers drink water from their service places, restaurants and
from many other locations which might be hygienically more vulnerable than their
households. It will be very complicated if all the sources of water consumption
patterns have to be considered. Since one of the objectives was to calculate
valuation of diseases, hence the focus was on the diseases for which target groups
were to spend some money during the time of sufferings.
Qualitative Assessment Basing on QSF: Here all the data were put into the
database and the questions or the attributes those were assumed to be directly
involved in the contribution of waterborne diseases‟ incidences were filtered and
results were obtained as such. Here is the list of questions used for data filter
operation:
What is the source of your water?
What is the distance of water point from your house?
How much time do you take to collect water from the source?
How much water do you receive every day?
What is the general condition of supplied water?
Do you boil your drinking water?
How much time you boil your drinking water?
Where do you store your drinking water?
Do you use lid to cover your container?
40
What type of Sanitation System you use?
What do you use to wash your hands after defecation?
These results were collected either in terms of HH or number of respondents and
displayed against:
Selected areas.
Community types
Urban Water Supply Options
Overall Conditions
Quantitative Assessment Basing on QSF: At this stage factors of qualitative
assessment were used for identification of health impacts in terms of quantitative
assessment. Since water quality and source water condition have direct effect on
health, hence, the lab-test result on microbiological quality (faecal coliform) of water
and SI risk grading have been incorporated as additional attribute columns. Hence
quantitative assessment was made with respect to twelve factors. These are:
The source of water.
Urban water supply options.
Distance from HH to water source.
Time to fetch water from water source.
Demand of water being met.
Boiling practices prevailing in the community
Duration of time spent to boil drinking water.
Storage of drinking water.
Sanitary system in use.
Hand wash practices after defecation as personal hygiene.
Water quality in terms of microbiological result.
SI Risk Grading
Here for the calculation of health impacts, the number of incidences and total
number of members affected by respective waterborne diseases against each
above factors were found out. Actual numbers of HH members exposed to the
particular disease were used for calculation during data filtering process. However,
where there were no incidences, no exposures were assumed and percentages
were shown as zero. Again where there were only few persons and all were affected
41
by same disease, then percentage shown as 100%. This assumption will naturally
yield high percentage of incidence rate against exposure which is rare in the reality
due to background level of immunity as explained in the Section 2.3.3. The process
of data filtration shown in the following steps:
Step-1: To find out the number of HH members exposed to diarrhoea,
typhoid and eye infections for the slum of Gulshan area. Here criteria used for
filter operations are:
o Thana: Gulshan
o Community type: Slum.
o Diseases: Diarrhoea, typhoid, eye infections (each considered
separately)
The results have been shown in terms of health matrix in the Table 3.4 through
Table 3.8.
Table 3.4: Data filtering process: Step-1
Thana Community
type
No. of Family
Members per HH
TOTAL Affected
by Diarrhoea
TOTAL Affected by
Typhoid
TOTAL Affected by
Eye Infections
Gulshan Slum. 6 6 6
Gulshan Slum. 3 3
Gulshan Slum. 3 1 3
Gulshan Slum. 6 6
Gulshan Slum. 4 1
Gulshan Slum. 9 1 2
Gulshan Slum. 6 6 6
Gulshan Slum. 2 2
Gulshan Slum. 4 4 4
Gulshan Slum. 3 3 3
Gulshan Slum. 5 4 1 5
Total: 28 3 36 % of incidence against Surveyed Population (rounded to next higher number)
55 6 71
One can see that the same family members might not be affected by more than one
disease at the same time and 51 members should be used for reference data in
order to find percentage of incidences. So to find out the correct percentage of
42
affected people against actual exposed HH family members, this matrix needs to be
corrected as such.
Step-2: To find out the actual number of HH members exposed to diarrhoea,
typhoid and eye infections respectively. Here, all the non-blanks data have been
queried by eliminating the blank data for specific disease. Hence three different
tables have been generated each depicting the actual scenario of single disease.
o For Diarrhoea:
Table 3.5: Data filtering process for diarrhoea: Step-2a
Thana Community
type
No. of Family
Members per HH
TOTAL Affected by Diarrhoea
TO
TA
L A
ffe
cte
d
by T
yp
hoid
TO
TA
L A
ffe
cte
d
by E
ye
in
fectio
ns
Gulshan Slum. 6 6 6
Gulshan Slum. 3 1 3
Gulshan Slum. 4 1
Gulshan Slum. 9 1 2
Gulshan Slum. 6 6 6
Gulshan Slum. 2 2
Gulshan Slum. 4 4 4
Gulshan Slum. 3 3 3
Gulshan Slum. 5 4 1 5
Total: 28 3 27
So it shows that out of 9 HHs of 42 family members only 28 persons were affected
by diarrhoea.
o For Typhoid:
Table 3.6: Data filtering process for typhoid: Step-2b
Thana Community
type
No. of Family
Members per HH
TO
TA
L A
ffe
cte
d
by D
iarr
hoe
a
TOTAL Affected by
Typhoid
TO
TA
L A
ffe
cte
d
by E
ye
infe
ctio
ns
Gulshan Slum. 9 1 2
Gulshan Slum. 5 4 1 5
Total: 5 3 5
43
So it shows that out of 2 HHs of 14 family members only 3 persons were affected by
typhoid.
o For Eye infections :
Table 3.7: Data filtering process for eye infections: Step-2c
Thana Community
type
No. of Family
Members per HH
TO
TA
L A
ffe
cte
d
by D
iarr
hoe
a
TO
TA
L A
ffe
cte
d
by T
yp
hoid
TOTAL Affected by
Eye infections
Gulshan Slum. 6 6 6
Gulshan Slum. 3 3
Gulshan Slum. 3 1 3
Gulshan Slum. 6 6
Gulshan Slum. 6 6 6
Gulshan Slum. 4 4 4
Gulshan Slum. 3 3 3
Gulshan Slum. 5 4 1 5
Total: 24 1 36
So it shows that out of 8 HHs of 36 family members all 36 persons were affected by
eye infections .
Step-3: After filtering process, all the data so far found out are compiled and
shown in the Table 3.6. So one can see that the aforesaid communities were
affected by diarrhoea, typhoid and eye infections at 67%, 22% and 100%
respectively instead of 55%, 6% and 71% as mentioned in the Table 3.2.
Table 3.8: Final result of data filtering process
Item
TOTAL Affected by
Diarrhoea Typhoid Eye
infections
Number of Incidences: 28 3 36
Number of Family Members Exposed: 42 14 36
% of incidence against Exposure (rounded to next higher number)
67 22 100
44
(b) Sanitary Inspection (SI): During sample collections, effort were made
to identify risk involved in the source of water (water point) related with sanitation
practices through Sanitary Inspection (SI) Form (Appendix B). Risk questions for SI
were chosen both in lines with WHO and considering local conditions which
otherwise would reveal the existing sanitation and hygiene practices of the
population under observation. There were 10 questions where risk of each question
was evaluated against either „„Y‟‟ for yes or „„N‟‟ for no type answer. Total score of
risks was calculated against 10 where 10 being the worst condition and 0 being the
best. The details of risk scores obtained during SI have been given in Table H.1 of
Appendix H. During evaluation of SI risk scores, criteria mentioned in Table 3.9
were used to grade the selected areas, communities and urban water supply
options.
Table 3.9: Criteria used for grading the SI risk scores
Serial Risk Score Grade Point Grade
1. >=9-10 4 Very high
2. >=6-<9 3 High
3. >=3-<6 2 Medium
4. >=0-<3 1 Low
Following steps are done in order to grade the areas, communities and urban water
supply options:
Step-1 (Calculation of Risk Scores): In order to calculate the risks involved, 1
was allotted for each one “Y” and 0 for each “N” answer. Finally total risks were
summed up to find out the total score of risks.
Step-2 (Grading of Selected areas, Communities and Urban Water Supply
Options): Here each water point was allotted with grade basing on the total
score of risks as shown in the Table H.1 of Appendix H. Next, basing on the
Equation 2.7 as mentioned in the Section 2.11.2, GPA was calculated and
graded the particular issue accordingly. Table H.2 to Table H.4 of Appendix H
have been given for the overall grading of selected areas, communities and
urban water supply options.
45
Step-3 (Using SI Risk Grade in Health Impact Assessment): Firstly a
new attribute column has been introduced in the Table G.1 of Appendix G and
then filling it by putting SI risk grade of each water point of Table H.1 of
Appendix H. Secondly the health impacts were found out using the filter process
as described before.
(c) Sample Collections: Initially aesthetic qualities of water were
examined in-situ. The users were asked about the presence of color, odor, dirt etc.
in their collected water and accordingly the observations were noted. At the same
time the exact location of water points were taken using Global Positioning System
(GPS) in order to mark it on the map for representation. Collected samples after
properly marked sealed and were taken to laboratory for testing. Table 3.10 shows
the list of laboratory tests were done on given parameters in order to get clear
picture of urban water quality both at source (WASA pump house/stand posts) and
at user‟s end.
Table 3.10: List of laboratory tests for collected water samples
Test Parameters Method of Testing
Aesthetic
Color (Pt-Co Unit) DR 5000 Spectrophotometer (HACH)
Odor Field observation and Questionnaire Survey
Presence of dirt
Physical Turbidity (NTU)
HI 93703 Microprocessor Turbidity Meter
pH HI 9024 Microcomputer pH Meter
Chemical Chlorine (Residual) (mg/l)
DR 5000 Spectrophotometer (HACH)
Microbiological FC (cfu /100ml)
Membrane Filtration and incubation in BOD Incubator (HACH) using MFC Broth media
3.3.5 Economic Valuation of Diseases
(a) General: There are a total of 1025 slums within Dhaka Metropolitan Area
(DMA) with a total of 267,065 households and on average 138 households per slum
(LGED 2005). 50 % of the slums rely on tap water as their primary drinking water
source, 2.6% use tube well Water, 0.4% use pond water, 1.3 % use river water and
0.1% uses other sources. The remaining 887 slums have no specified water source.
They rely on buying from vendors, public tankers and nearby slums. The vulnerable
community especially slum dwellers spend time on collecting water from public
sources, storing water and treating water before consumption. Households could
46
avoid all of these coping costs if piped water services are improved (i.e., water is
sufficient, reliable, and potable). Detail calculation of estimated health impact
valuation of waterborne diseases of Dhaka city has been given in Appendix K.
(b) Method Adopted: In this study an attempt was made to quantify and express
in monetary terms the full value of diseases as affected due to consumption of water
of urban water supply and associated poor sanitation and hygiene practices. To do
that, “Cost of illness approach” of Market based methods as stated in Section 2.9.4
was followed. Here willing to pay (WTP) to avoid the illness was not measured
rather health effect based on cost of illness of family members were valued by
calculating the costs.
(c) Quantifying the Indirect Cost: Quantifying direct cost is very simple and
easily available. But quantifying indirect cost requires different approach to follow. It
has been assumed that:
If the parents/earning member would not have affected by waterborne
diseases or would not have to take care of their family members like children,
then the parents/earning member would have gone for his/her work and earned
his/her wages in time. So here needs identification of wage of a daily-labour per
hour. Accordingly Table 3.11 shows the hourly average wage rate of various
types of labours.
Table 3.11: Calculation of hourly average wage rate
Serial Type of Labour
Average Wage Rate (Taka)
Remark Daily
(8 Hours/day) Hourly
1. Mason 300.00 37.50 BBS (2010)
2. Labour 200.00 25.00
3. Rickshaw/van Puller 150.00 18.75 Field Interview
4. Scavenger 50.00 6.25
Average 175.00 21.88
47
The leisure time costs of child diarrhoea also have been converted into
monetary terms by multiplying the time lost by a proportion of the hourly wage of
an individual in the household. For this study, it has been considered 50% of the
average hourly wage rate Tk. 10.94 (mean hourly wage rate was Tk. 21.88). The
50% estimate is similar to fractions used in estimating time costs of water
collection in Nepal (Pattanayak et al. 2005).
(d) Calculation for Whole of Dhaka: Table K.2a of Appendix K used the total
number of HH of slum community as found out by LGED (2005) and total population
found out by multiplying it with HH size (5.25) as found out by this study. Prevalence
rate was used to identify the likely incidences and cost of diseases was
implemented as such. Another approach used in Table K.2b of Appendix K, where
to identify the likely incidences, total population of Dhaka city as found out by BBS
(2011) was multiplied by percentage of population living in slum areas as reported.
Finally costs of diseases were used to find out the total value.
3.3.6 Prevalence Rate (PR)
Evaluation of PR for this study has been made on diarrohea, typhoid and eye
infections. Moreover, since data collected on various age-groups of both male and
female gender, hence the formula (Equation 2.2, 2.3, 2.4 and 2.5 ) as stated in the
Section 2.10.2 has been modified and used for different age-groups and gender too.
Here following steps were followed:
Step-1 (Identification of number of incidences): Here total number of
incidences was calculated for a particular group from existing data of
questionnaire survey e.g. female children of <5 years has been found out.
Step-2 (Identification of total surveyed population of particular group): Here
total number of family members (includes affected and non-affected persons)
exposed to certain diseases were calculated for a particular group from existing
data of questionnaire survey. Here total population (i.e. 210 persons) surveyed
or total female population (i.e. 96 persons) surveyed or total female HH
members of different age-group (i.e. 16 female persons of aging < 5 years)
surveyed have been considered in order to find different PR values. Since this
48
value has been used as denominator, hence the PR values of total population
surveyed differ significantly for each individual case.
Step-3 :(Use of required formula to identify PR): Here for particular issue
different formulas as given in Section 2.10.2 were used to find out PR of different
points of interest. The detail calculation of prevalence rate has been given in
Table L.1 through L.6 of Appendix L.
3.3.7 Climatic Factors
To identify correlation between selected climatic factors and the diarrhoeal incidents
of the selected areas, the annual and monthly records for both elements were
collected. Appendix C and Appendix D cover the yearly and monthly data of
diarrhoeal patients reporting ICDDR,B whereas Appendix F covers the yearly and
monthly climatic data. Correlation can be used effectively to study the future impact
of one factor when value of another factor is known. Following steps were followed
in order to find out the correlation:
Step-1 (Generation of trend of the factor): When monthly records of many
years of a particular climatic factor are plotted, a general trend of that factor can
be generated with reasonable probability. Here trends for both climatic factor
and incidences of waterborne diseases are plotted in the same chart; where
abscissa denotes the months of year and ordinate (primary and secondary axes)
for different values of two factors to see the similarity in occurrences.
Step-2 (Development of Correlation): Basing on the above information, now
scatter chart is used to find out the probable correlation between climatic factor
and number of patients reporting the ICDDR,B with waterborne diseases.
Step-3 (Formulation of Correlation): After a correlation is found out, a best fit
trend line is drawn using Microsoft Excel and the associated equation is
formulated as such. Here point to note that for formulation using regression
analysis, data is checked in order to find out if the correlation is linear or non-
linear i.e. exponential/ logarithmic. For linear correlation no data transformation
is required but for non-linear case data will be transformed.
49
CHAPTER 4
ANALYSIS OF DATA
4.1 Introduction
Water is undoubtedly the most precious natural resource that exists on our planet
without this seemingly invaluable compound, life on earth would not be in existence.
As we understand that our health is truly dependent on the quality and quantity of
the water we drink. Hence any deficiency either of it is going to have a negative
effect on our health. That is why safe, adequate and accessible supplies of water,
combined with proper sanitation, are basic needs and essential components of
primary health care. This chapter describe in details about the analysis part of the
total thesis work covering the important aspects like water, sanitation, hygiene and
climatic factors which have direct impact on human health.
4.2 Data Availability in Bangladesh
It is often found that relevant data on health are rarely maintained by an individual of
any class. Preservation and maintenance of data at national level is also in very
initial stage. With these limitations, attempt has been made to look for organizations
maintaining relevant health data so as to identify the severity of the areas of Dhaka
city as per as waterborne diseases are concerned. Analyzing such data will provide
more realistic scenario than that of guessing at random in order to select the sample
areas for this study. As such all the data related with waterborne diseases have
been collected from ICDDR,B and DSH. On the other hand, to fulfill another
objective of the thesis related with correlation between waterborne diseases and
climatic factors, the meteorological data has been collected from BMD. Other
secondary data have also been collected from WASA, DOE, DCC, BCUS, RAJUK,
Survey of Bangladesh (SOB), Bangladesh Bureau of Statistics (BBS) etc. All these
data and data collected at field level will allow us to attain the objective of this thesis.
4.3 Selection of Data
The number of patients suffered from waterborne diseases, reported to and/or
hospitalized to ICDDR,B from 1996 to 2010 have been used to identify the general
50
public health condition of Dhaka as per as waterborne diseases are concerned.
Here the types of data used are:
4.3.1 Yearly Records: Yearly records of patients of different age groups (e.g. <5,
5-14 and > 15 years) from different thanas of Dhaka city reported/hospitalized to
ICDDR, B from 1996 to 2010 have been averaged and given in Appendix-C. Basing
on these 15 years of records, a yearly trend could be developed as given in the
Figure 4.1 .
Figure 4.1 Yearly trends of waterborne disease’s patients of Dhaka city
While visiting the hospital and discussing with concerned authority of ICDDR, B
about the type of people and their pattern of reporting the hospital; following
information could be extracted:
Patients are mostly from vulnerable groups i.e. low-income and slum people.
Patients, those are critical in nature report to hospital more than those who
suffer regular basis.
Children (<5 years) and elderly people (> 15 years) suffer much than those
of middle ages (5-14 years) people.
0
2000
4000
6000
8000
10000
12000
Nu
mb
er
of
pat
ien
t
Thanas of Dhaka city
<5 Yrs 5-14 Yrs 15+ Yrs
51
Patients residing nearer to the hospitals, report more than those residing
away from it.
On the other hand, Figure 4.2 shows the number of children admitted during 2005-
2006 to Dhaka Shishu Hospital (DSH).
Figure 4.2 Children patients reporting DSH during 2005-06.
This figure also shows that patients locating nearby DSH have more reporting
incidences. The yearly trend as shown in Figure 4.1 to be more effective, the data of
different administrative areas of Dhaka city have been generalized against its
population. Here the population of thanas of Dhaka for the year of 2010 has been
estimated using geometric progression method as mentioned in the Section 2.2.3
and given in Appendix E. With this estimated thana population and number of
reported patients during 2010, a more generalized data for each 1000 people has
been calculated as shown in the Table 4.1. Now from this generalized data only the
first top four thanas i.e. Gulshan, Badda, Tejgaon and Mirpur have been selected
for this study. It may be noted that though the patients reporting ICDDR,B from
Mirpur and Demra have been found same (i.e. 12 out of 1000); but due to high
incidences of Mirpur (10,950) than Demra (8,300), Mirpur has been chosen. Here
Table 4.2 shows the average patients of different age groups of selected areas of
Dhaka city.
05
10152025303540
Nu
mb
er
of
Ch
ildre
n A
dm
itte
d
Diarrhoea Viral Hepatitis Jaundice Typhoid
52
Table 4.1 Generalized population of administrative areas of Dhaka city reporting ICDDR, B in 2010
Ser Name
Ma
le
Po
pu
lati
on
Fem
ale
Po
pu
lati
on
To
tal P
op
ula
tio
n
(200
1)
Pp=
c+
d
Pro
jecte
d P
op
(2
010)
Pf =
Pp (
1+
r)n
(r =
6%
, n
=9)
Re
po
rte
d t
o IC
DD
R,B
(2010)
Ou
t o
f 1
00
0
h =
g X
1000 / P
f
(a) (b) (c) (d) (e) (f) (g) (h)
1 Gulshan 107000 83000 190000 321002 8250 26
2 Badda 198000 161000 359000 606523 9200 16
3 Tejgaon 174000 128000 302000 510223 7450 15
4 Mirpur 301000 250000 551000 930903 10950 12
5 Demra 238000 190000 428000 723097 8300 12
6 Mohammadpur 251000 205000 456000 770403 7200 10
7 Uttara 188000 157000 345000 582871 5400 10
8 Lalbag 206000 140000 346000 584560 4500 8
9 Khilgaon 185000 152000 337000 569355 4350 8
10 Kotawali 162000 92000 254000 429128 3100 8
11 Hazaribag 71000 57000 128000 216254 1350 7
12 Kamrangirchar 76000 67000 143000 241596 1650 7
13 Sutrapur 206000 147000 353000 596387 3600 7
14 Kafrul 157000 133000 290000 489949 3250 7
15 Shabujbag 318000 131000 449000 758577 3850 6
16 Cantonment 70000 48000 118000 199359 1050 6
17 Shyampur 211000 165000 376000 635245 3050 5
18 Motijheel 162000 108000 270000 456160 1950 5
19 Ramna 149000 109000 258000 435886 2150 5
20 Dhanmondi 147000 106000 253000 427439 1850 5
21 Pallabi 232000 200000 432000 729855 1550 3
Source: BBS (2010), ICDDR, B (2010)
Table 4.2 Selected thana wise different age groups patients
Sample Areas <5 Yrs 5-14 Yrs 15+ Yrs Total
Gulshan 4150 650 3100 7900
Badda 3650 500 2850 7000
Tejgaon 2500 350 2250 5100
Mirpur 4950 900 5100 10950
Total: 15250 2400 13300 30950
Source: ICDDR,B (2010)
53
4.3.2 Monthly Records: To identify the general trends of waterborne diseases,
monthly records of eleven years (2000 to 2010) of patients from different thanas of
Dhaka city reported/hospitalized to ICDDR,B as given in Appendix-D has been
used. Basing on average monthly records of those eleven years, a general trend of
incidences has been found out for selected areas as given in the Figure 4.3.
Figure 4.3 General Trend of Patients of Waterborne Diseases
In this study, the data collected during second peak as marked by vertical lines.
4.3.3 Meteorological Data. The climate of Dhaka is tropical in nature with heavy
rain and bright sunshine in the monsoon and warm for the greater part of the year.
On the other hand during winter which is from November to March are however cool
and pleasant. Table 4.3 shows “at a glance” of Dhaka city climate:
Table 4.3 At a glance of Dhaka city climate
Temperature
Maximum Minimum
Summer 36.70 C 21.10 C
Winter 31.70 C 10.50 C
Rainfall 2540 mm annually
Humidity 80 per cent (approximately)
Source: DCC (2009)
Here monthly and annual records of selected factors of last 21 years (1990 to 2010)
have been collected from BMD and given in Appendix F. Since the diarrhoeal
diseases is a major problem as per as waterborne diseases are concerned; hence
0
200
400
600
800
1000
1200
1400
1600
1800
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Num
ber
of
dia
rrhoeal patients
Month
Tejgaon Badda Gulshan Mirpur
54
the effect of climatic factors have been used to find out the correlation with
diarrhoeal diseases only.
(a) Rainfall Pattern of Dhaka city: The 21 years rainfall pattern of Dhaka city is
based on the annual total rainfall data whose average value has been given in the
Table F.1 of Appendix F. Here the minimum rainfall has been recorded as 1169 mm
in the year of 1992 and maximum was 2885 mm in the year 2007 and the average
rainfall is about 2148 mm. Figure 4.4 shows the variations of annual rainfall of
Dhaka city from the year 1990 to 2010 (BMD 2010).
Figure 4.4 Variations of annual rainfall of Dhaka city
Basing on the average monthly rainfall of aforesaid 21 years, a general trend can be
developed and can be used for subsequent interpolation of data with waterborne
diseases. Figure 4.5 shows such trend of rainfall of Dhaka city indicating two peaks
at two different time frames mostly around Jun-July and another in September.
Figure 4.5 Trend of rainfall of Dhaka city
Average annual rainfall 2148mm
0
100
200
300
400
500
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Mo
nth
ly R
ain
fall (
mm
)
Month
55
(b) Temperature Pattern of Dhaka city: The 21 years temperature pattern of
Dhaka city is based on the annual average minimum, average maximum and
average temperature data as given in the Table F.1 of Appendix F. Here the
average minimum annual temperature has been recorded as 21.6°C in the year of
1997 and average maximum annual temperature was 31.7°C in the year 1996.
Figure 4.6 shows the variations of annual temperature in Dhaka city from the year
1990 to 2010 (BMD 2010).
Figure 4.6 Variations of average annual temperature of Dhaka city
Basing on the average monthly temperature of aforesaid 21 years, a general trend
can be developed and can be used for subsequent interpolation of data with
waterborne diseases.
Figure 4.7 Trend of temperature of Dhaka city
15
20
25
30
35
Tem
pera
ture
(°C
)
Year
Maximum Minimum Avgerage
10
15
20
25
30
35
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Tem
pe
ratu
re(°
C)
Month
Mean Maximum Minimum Avgerage
56
Figure 4.7 shows such trend of rainfall of Dhaka city indicating two peaks at two
different time frame i.e. around April-May and another around August-September.
(c) Humidity Pattern of Dhaka city: The 21 years humidity pattern of Dhaka city
is based on the annual average humidity data as given in the Table F.1 of Appendix
F. Figure 4.8 shows the variations of annual humidity in Dhaka city from the year
1990 to 2010 (BMD 2010).
Figure 4.8 Variations of average annual humidity of Dhaka city
Basing on the average monthly temperature of aforesaid 21 years, a general trend
can be developed and can be used for subsequent interpolation of data with
waterborne diseases. Figure 4.9 shows such trend of humidity of Dhaka city.
Figure 4.9 Trend of average annual humidity of Dhaka city
66
68
70
72
74
76
78
Hu
mid
ity(%
)
Year
55
60
65
70
75
80
85
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Hu
mid
ity(%
)
57
4.4 Analysis of Field Data
Basing on information in the Section 4.3.2, the field data was collected from July-
November 2010 only i.e. collecting data during second peak period (Figure 4.3).
4.4.1 Questionnaires Survey- An Overview
In this study, 40 HHs of 210 family members were interviewed. It can be seen that
the 3 to 6 members HH were the maximum covering about 79% of the total family
members surveyed. The average size of a HH was found to be more than 5
members/HH (i.e. 5.25 members/HH, Figure 4.10). During survey, it was found that
a single water point was being shared by in average more than 5 HHs (i.e. more
than 25 family members - one cluster) and same kind of water by number of
clusters. Accordingly, it was found that about 2,651 family members of different
clusters directly exposed to same water points and 67,500 members being indirectly
affected due to use of same kind of water supplied by urban water supply system.
Table 4.4 shows the distribution of these members residing in the following sample
areas are.
Figure 4.10 Distribution of population by number of person per HH
0
10
20
30
40
50
60
70
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Po
pu
lati
on
Su
rve
yed
Person per HH
5.25
58
Table 4.4 Sample area wise distribution of interviewed HHs and exposed
population
Serial Sample Areas
Number of HHs
Number of HH
Members
Number of Directly Exposed
Population
Number of Indirectly Exposed
Population
1. Gulshan 12 56 1150 27000
2. Tejgaon 10 48 455 12300
3. Badda 8 42 600 12700
4. Mirpur 10 64 446 15500
Total: 40 210 2,651 67,500
Table 4.5 shows the distribution of communities interviewed. However it was found
that about 55% and 45% were male and female gender respondents respectively.
Table 4.5: Age group wise distribution of interviewed communities
Community Type
Age Groups Interviewed (Number of HHs) Total Number of
HHs 15-30 Year 30-45 Year 45-60 Year
Slum 6 15 2 23
Low-income 6 7 4 17
Total: 12 22 6 40
The most of the interviewed male members were masons, rickshaw pullers, drivers
(baby taxi, mishuk, truck drivers etc.), vegetable vendors, workers, hawkers,
scavengers who mainly came from other districts (73% of total surveyed
respondents) of Bangladesh for economic reasons. Actually these people were
manual labourers who generally earned their livelihood under different climatic
condition and remained susceptible to the high temperatures. During survey, it was
learnt that they drink water usually from unreliable sources like construction sites,
road side hotels/restaurants, stand posts etc. without considering the quality of it.
This happened to be more during the day with high temperature.
4.4.2 Qualitative Assessment
(a) Sources of Water and Urban Water Supply Options: Qualitative assessment
starts with the identifications of the connection sources and urban water supply
options available to the communities of different selected areas. Table 4.6 shows
the distribution of number of HHs to urban water supply options as per community
and connection sources. It is seen that the most of the case, the sources of water
59
for the above communities were from private connections from nearby WASA line
using rubber, low quality plastic pipes following over the wasteland or most
unhygienic area as these can be seen in the Image 4.1, 4.2 and 4.3. The relevant
details of Questionnaire Survey have been given in Table G.1 of Appendix G.
Table 4.6 Distribution of number of HHs to urban water supply options as per
community type and connection sources
Community Type
Connection Sources
Urban Water Supply Options (Number of HHs)
Pip
ed
wa
ter
su
pp
ly w
ith
res
erv
oir
Pip
ed
wa
ter
su
pp
ly w
ith
ou
t
res
erv
oir
Ha
nd
pu
mp
co
nn
ecte
d t
o
su
pp
ly lin
e/S
TW
To
tal
Slum Private connection. 0 4 10 14
Public connection/Tap water 3 2 4 9
Low- income Private connection. 1 7 4 12
Public connection/Tap water 2 2 1 5
Overall Private connection. 1 11 14 26
Public connection/Tap water 5 4 5 14
Grand Total: 6 15 19 40
There were 27 water points as shown in Figure O.2 of Appendix O whose water
samples were tested. 3 of those were collected directly from WASA pump house in
order to test the state of delivery water quality. Table 4.7 and 4.8 are showing the
disposal of the rest 24 observed water points available for different urban water
supply options and having direct impact on to the vulnerable communities.
60
Image 4.1: Exposed water line at Mirpur
Image 4.2: Exposed water line at Gulshan (IPS Bosti)
Image 4.3: Exposed water line at Tejgaon
61
Table 4.7: Distribution of selected area wise number of observed water points
to urban water supply options
Selected Areas
Piped water supply with
reservoir (No)
Piped water supply without
reservoir (No)
Hand pump connected to supply line
(No)
Total Nos.
Gulshan 1 3 2 6
Tejgaon 1 2 2 5
Badda 1 5 6
Mirpur 2 4 1 7
Total: 4 10 10 24
Table 4.8: Distribution of community wise number of observed water points to
urban water supply options
Community
Piped water supply with
reservoir (No)
Piped water supply without
reservoir (No)
Hand pump connected to supply line
(No)
Total Nos.
Slum 2 4 7 13
Low-income 2 6 3 11
Total: 4 10 10 24
(b) Distance and Time Related with Water Source: Table 4.9 and 4.10
summarizes the distribution of HHs residing at different distances from water
sources and time taken for fetching water from those sources respectively. Figure
4.11 shows different distance range between households and water sources for the
selected sample areas.
Table 4.9: Distribution of number of HHs residing at different distances from
water sources.
Distance Urban Water Supply Options Community (Number of HHs)
Slum Low income Total
<50m
Piped water supply with reservoir 0 3 3
Piped water supply without reservoir 4 9 13
Hand pump connected to supply line 11 4 15
Sub Total: 15 16 31
<100 (50-100)m
Piped water supply with reservoir 0 0 0
Piped water supply without reservoir 2 0 2
Hand pump connected to supply line 1 0 1
Sub Total: 3 0 3
<250 (100-250) m
Piped water supply with reservoir 3 0 3
Piped water supply without reservoir 0 0 0
Hand pump connected to supply line 2 1 3
Sub Total: 5 1 6
Grand Total: 23 17 40
62
Table 4.10: Community wise number of HHs against time taken to fetch water
Community Type
Distance Travel
Time Taken (Number of HHs)
5 minutes
5-15 minutes
15-30 minutes
Total
Slum
<50m 15 0 0 15
<100 (50-100)m 0 2 1 3
<250 (100-250) m 0 1 4 5
Sub Total: 15 3 5 23
Low income
<50m 16 0 0 16
<100 (50-100)m 0 0 0 0
<250(100-250) m 0 1 0 1
Sub Total: 16 1 0 17
Grand Total: 31 4 5 40
Figure 4.11: Sample areas wise different distance range between households
and water sources.
(c) Water Demand: In this study Table 4.11 shows the distribution of number of
HHs against water demand and water sources' connections. While Table 4.12
shows the distribution of community wise HHs against water demand and urban
water supply options.
Table 4.11: Distribution of number of HHs against water demand and water
sources' connections
Sources' Connections Water Demand (Number of HHs)
100% 75% 50% Total
Supplied water through private connection
2 10 14 26
Supplied water through public connection/Tap water
0 6 8 14
Total: 2 16 22 40
0
2
4
6
8
10
12
14
Gulshan Tejgaon Badda Mirpur
Sample Area
Nu
mb
er
of
HH
s
<50m <100 (50-100)m <250 (100-250) m
63
Table 4.12: Distribution of community wise number of HHs against water demand and urban water supply options
Water Demand
Urban Water Supply Options Community Type
Total Slum Low income
Full/As per demand
Piped water supply with reservoir 0 0 0
Piped water supply without reservoir 0 2 2
Hand pump connected to supply line 0 0 0
Sub Total: 0 2 2
75% of demand
Piped water supply with reservoir 0 2 2
Piped water supply without reservoir 2 5 7
Hand pump connected to supply line 4 3 7
Sub Total: 6 10 16
50% of demand
Piped water supply with reservoir 3 1 4
Piped water supply without reservoir 4 2 6
Hand pump connected to supply line 10 2 12
Sub Total: 17 5 22
Grand Total: 23 17 40
(d) Aesthetic Quality of Water: During interview, the members of respective
communities were asked to give their opinion on the general condition of water they
use day to day life. Their observations on the aesthetic quality of supplied urban
water were noted. However, it was informed that those observations were temporary
in nature and generally observed right after the absence of electricity on the part of
WASA pump house. Sample area wise number of HH reporting different aesthetic
quality of water has been given in the Table 4.13.
Table 4.13: Sample area wise number of HHs reporting aesthetic quality of
water
Sample Areas
Clean and fresh
Odorous Turbid Contains dirt and
other foreign materials
Total
Gulshan 2 4 0 6 12
Tejgaon 0 7 2 1 10
Badda 0 6 0 2 8
Mirpur 5 1 0 4 10
Total: 7 18 2 13 40
(e) Boiling Practices of Drinking Water: In the context of water supply in Dhaka
city, due to risk of outbreaks of waterborne diseases, people often boil the supply
water prior to drinking. But boiling practices depend on the availability of fuel,
economic ability, awareness of diseases and its consequences. Table 4.14 shows
the distribution of HHs of different communities against water boiling practices and
64
Table 4.14: Distribution of HHs of different community types against water boiling practices and urban water supply options
Boiling Practices
Urban Water Supply Options Community Type
Total Slum Low income
Yes
Piped water supply with reservoir 0 3 3
Piped water supply without reservoir 0 6 6
Hand pump connected to supply line 0 4 4
Sub Total: 0 13 13
No
Piped water supply with reservoir 3 0 3
Piped water supply without reservoir 6 3 9
Hand pump connected to supply line 14 1 15
Sub Total: 23 4 27
Grand Total: 23 17 40
urban water supply options. Table 4.15 shows the distribution of HHs of low-income
community using different water supply options. There were 13 HHs of low-income
community who usually boiled water for different time range.
Table 4.15: Distribution of low-income community HHs against water boiling duration and urban water supply options
Urban Water Supply Options Boiling Duration
5-15 minutes 15-30 minutes
Piped water supply with reservoir 0 3
Piped water supply without reservoir 3 3
Hand pump connected to supply line 1 3
Total: 4 9
(f) Storage of Water in Practice: At domestic water supply system, storage of
water plays a vital role; because it provides a kind of assurance to the user about its
availability and quality during scares time. There were mainly 4 types of storage
container noticed during the survey; these are:
Drum: These are plastic drums formerly used for preservation and storage of
chemicals.
Kolosh (Pitcher): These were both earthen and silver pitchers.
Patil (Cooking ware): These were also used side by side after their cooking.
Water Bottle: These were the PET bottles usually collected from unreliable
sources by vulnerable groups after being used.
Table 4.16, Table 4.17 and Table 4.18 show the different distribution of HHs with
respect to storage system for different communities, selected areas and urban
supply options. Generally the community was seen using lids to cover the
containers which provide them first hand safety from the flies, leaves etc.
65
Table 4.16 Distribution of number of HHs of different community with respect to water storage system at HH level.
Community Drum Kolosh Patil Water Bottle Total
Slum 8 8 0 7 23
Low-income 1 14 1 1 17
Total: 9 22 1 8 40
Table 4.17 Distribution of number of HHs of different selected areas with respect to water storage system at HH level.
Selected Areas Drum Kolosh Patil Water Bottle Total
Gulshan 4 4 0 4 12
Tejgaon 3 6 0 1 10
Badda 1 6 0 1 8
Mirpur 1 6 1 2 10
Total 9 22 1 8 40
Table 4.18 Distribution of number of HHs of different urban water supply system with respect to water storage system at HH level.
Urban Water Supply Options Drum Kolosh Patil Water Bottle
Total
Piped water supply with reservoir 0 5 0 1 6
Piped water supply without reservoir 3 9 1 2 15
Hand pump connected to supply line 6 8 0 5 19
Total: 9 22 1 3 40
(g) Sanitation Systems in Use: Sanitation can contribute greatly to preventing
the spread of infectious diseases through transmission of disease causing agents as
is the case when pathogenic organisms from the excreta of an infected person are
transmitted to a healthy person. In this study different sanitation systems were taken
Table 4.19: Sample area wise distribution of number of HHs of different communities having different sanitation systems
Sample Area
Community Type
Sanitation Systems
Sanitary sewer
Septic tank
system
Pit latrine
Hanging latrine
Unsanitary Total
Gulshan Slum 0 0 10 0 1 11
Low-income 0 0 1 0 0 1
Tejgaon Slum 0 0 2 0 2 4
Low-income 0 5 1 0 0 6
Badda Slum 0 2 0 0 2 4
Low-income 2 2 0 0 0 4
Mirpur Slum 0 0 2 2 0 4
Low-income 0 4 2 0 0 6
Subtotal Slum 0 2 14 2 5 23
Low-income 2 11 4 0 0 17
Grand Total: 2 13 18 2 5 40
66
into consideration in order to locate any possibilities of linking between waterborne
diseases‟ incidences in the selected areas. Table 4.19 shows such information as
sample wise distribution of HHs of different communities.
(h) Hygiene Practices-Use of Hand Wash Medium: Hand washing is one of the
important aspects for effective personal hygiene maintenance. It has direct impact
on the hygiene practices only when its three points are addressed properly; these
are quantity of water, time of washing and medium used for washing. As it was
already discussed in Section 2.7.2 that the most critical times for hand washing are
following defecation and before eating. However this study identified soap, ash/soil
as means of hand washing following defecation. Table 4.20 shows the details of the
study area about the state of hand washing among the communities.
Table 4.20: Sample area wise distribution of number of HHs of different communities showing hand washing practices
Sample Area Community Type Soap Ash/Soil Nothing Total
Gulshan Slum 1 0 10 11
Low-income 1 0 0 1
Tejgaon Slum 1 1 2 4
Low-income 6 0 0 6
Badda Slum 0 0 4 4
Low-income 4 0 0 4
Mirpur Slum 1 0 3 4
Low-income 6 0 0 6
Total Slum 3 1 19 23
Low-income 17 0 0 17
Grand Total: 20 1 19 40
67
(i) Water Quality of Collected Samples: In this study, the sample water was
tested for its physical, chemical and microbiological qualities as stated in the Section
3.3.3. During interview with pump operators (representative from WASA), it was
learnt that generally the quality of pump house water was quite acceptable and
needed no extra treatment. However sometimes they use chlorine gas or bleaching
powder in order to make residual chlorine available in the distribution network. It
was found that the samples of WASA pump houses were within the range of
drinking water standards of Bangladesh. It shows the source water quality on which
the community has to rely on. The detailed analysis of samples has been given in
Appendix I. Following Tables (Table 4.21 through 4.23) shows the state of
contamination described in terms of number of samples at different FC count.
Table 4.21: Area wise number of samples of different faecal coliform concentration
Selected Areas FC Count (cfu/100ml)
0-100 100-200 200-300 300-400
Gulshan 2 1 3 0
Tejgaon 1 2 2 0
Badda 0 3 2 0
Mirpur 0 3 3 1
% Covering 17 37 42 4
Table 4.22: Community wise number of samples of different faecal coliform concentration
Community FC Count (cfu/100ml)
0-100 100-200 200-300 300-400
Slum 2 3 7 0
Low-income 1 6 3 1
% Covering 17 37 42 4
Table 4.23: Urban water supply option wise number of samples of different faecal coliform concentration
Urban Water Supply Options FC Count (cfu/100ml)
0-100 100-200 200-300 300-400
Piped water supply with reservoir 0 3 1 0
Piped water supply without reservoir 2 3 4 1
Hand pump connected to supply line 2 3 5 0
% Covering 17 37 42 4
68
(j) Sanitary Inspection (SI): Sanitary Inspection (SI) form (Appendix B) was
used to identify risk involved in the source of water (water point) related with
sanitation practices. There were 27 water points out of which 3 were from WASA
Ground Water Supply Pump (WGWSP). SI was done for those water points and
Table 4.24: Area wise distribution of number of water points as per risk grade
Selected Area
Number of Water Points Obtained Grade
Low Medium High Very High Total
Gulshan 2 3 1 6
Tejgaon 2 2 3 7 Badda 3 3 6 Mirpur 1 3 3 1 8
Total: 3 10 12 2 27
samples were tested in order to find out the source contamination. Detail risk score
analysis has been given in Appendix H. Following Table 4.24 shows the distribution
of water points as per grade obtained after analyzing in Table H.1 of Appendix H.
However for the sake of exact calculation of the community, the above three “low”
graded water points were not considered in this study. However they have been
considered as one of the comparative measures. Here the WGWSPs had very low
score and maintained properly. Community wise and urban supply options wise risk
grade have been given in the Table 4.25 and 4.26 respectively.
Table 4.25: Community wise distribution of number of water points as per SI risk grade
Community Type
Number of Water Points Obtained Grade
Medium High Very High Total
Slum 5 6 2 13
Low-income 5 6 0 11
Total: 10 12 2 24
Table 4.26: Urban supply options wise distribution of number of water points as per SI risk grade
Urban Supply Options Number of Water Points Obtained Grade
Medium High Very High Total
Piped water supply with reservoir 3 1 1 5
Piped water supply without reservoir 3 6 1 10
Hand pump connected to supply line 4 5 0 9
Total: 10 12 2 24
69
Detail calculation for overall grading using formula as mentioned in the Section
2.11.2 have been given in the Table H.2 to H.4 of Appendix H.
4.4.3 Quantitative Assessment
(a) An Overview: The overall incidences of waterborne diseases of various age
groups according to the genders have been given in the Table 4.27. Here it shows
that elderly people (> 15 Years) of both male and female genders were found to be
more in percentage than those of other age groups. On the other hand, Table 4.28
shows the Sample areas wise state of waterborne diseases‟ incidences of different
genders. This table shows that in every sample areas, the rates of incidences are
more for male than those of females.
Table 4.27: Gender wise overall incidences of waterborne diseases of different age groups
Gender Age
Groups Exposure Number
Number of Incidences
Diarrhoea Typhoid Eye
Infections
Female (F)
<5 Years 16 10 2 3
5-14 Years 20 9 1 8
>15 Years 60 26 3 14
Subtotal: 96 45 6 25
Male (M)
<5 Years 17 5 1 7
5-14 Years 26 18 1 9
>15 Years 71 33 2 24
Subtotal: 114 56 4 40
Grand Total: 210 101 10 65
Table 4.28: Sample areas wise state of waterborne diseases’ incidences of
different genders
Sample Areas
Gender
Number of Incidences
Diarrhoea Typhoid Eye
Infections
Gulshan
Female (F) 13 2 15
Male (M) 17 1 21
Subtotal: 30 3 36
Tejgaon
Female (F) 9 2 5
Male (M) 12 0 6
Subtotal: 21 2 11
Badda
Female (F) 9 1 4
Male (M) 11 2 8
Subtotal: 20 3 12
Mirpur
Female (F) 14 1 1
Male (M) 16 1 5
Subtotal: 30 2 6
Grand Total: 101 10 65
70
Table 4.29 shows the community wise waterborne diseases‟ incidences. It is evident
that the incidents of slum were more than those of low-income group. To be more
specific, though the slum communities were comprised of 23 HHs of 117 family
members, but while interviewing, it was found that 61 persons of 21 HHs suffered
from diarhoea, 8 persons of 6 HHs suffered from Typhoid and 42 persons of 14 HHs
suffered from eye infections . Out of 40 HHs, 101 members have been found
affected by diarhoea, 10 members by typhoid and 116 members by eye infections
during last one year. These data will be useful to identify health impacts for
communities, selected areas, urban water supply options and present overall state
of the incidences against exposure.
Table 4.29: Community wise state of waterborne diseases’ incidences
Community
Num
ber
of H
H
Num
ber
of H
H M
em
bers
Number of Incidences
Diarrhoea Typhoid Eye Infections
Affecte
d
Not A
ffecte
d
Out of
Mem
bers
/HH
Affecte
d
Not A
ffecte
d
Out of
Mem
bers
/HH
Affecte
d
Not A
ffecte
d
Out of
Mem
bers
/HH
Slum 23 117 61 47 108/21 8 30 38/6 42 29 71/14
Low-income 17 93 40 26 66/12 2 4 6/1 23 22 45/9
Total: 40 210 101 73 174/33 10 34 44/7 65 51 116/23
(b) Water Sources‟ Connections: In qualitative assessment it was seen majority
of the connections were using private means (65%) and 54% of it was shared by
slum people. Table 4.30 shows the waterborne diseases‟ incidences found against
water sources‟ connections.
71
Table 4.30: Waterborne diseases’ incidences with respect to water sources’
connections
Water Sources’ Connections
Diarrhoea Typhoid Eye Infections
Num
ber
of In
cid
ences
Num
ber
of F
am
ily
Mem
bers
Expose
d
% o
f in
cid
ence a
ga
inst
Exposure
% o
f in
cid
ences a
gain
st
Tota
l in
cid
ences
Num
ber
of In
cid
ences
Num
ber
of F
am
ily
Mem
bers
Expose
d
% o
f in
cid
ence a
ga
inst
Exposure
% o
f in
cid
ences a
gain
st
Tota
l in
cid
ences
Num
ber
of In
cid
ences
Num
ber
of F
am
ily
Mem
bers
Expose
d
% o
f in
cid
ence a
ga
inst
Exposure
% o
f in
cid
ences a
gain
st
Tota
l in
cid
ences
Private Connection
75 121 62 74 6 27 23 60 50 93 54 77
Public Connection/Tap
Water 26 53 50 26 4 17 24 40 15 23 66 23
Grand Total: 101 174 59 100 10 44 23 100 65 116 57 100
(c) Urban Water Supply Options: Health impact due to use of urban water
supply options was the main objective of this thesis. Table 4.31 shows the health
impacts in terms of waterborne diseases‟ incidences with respect to urban water
supply options and Table 4.32 shows community wise waterborne diseases‟
incidences with respect to urban water supply options.
Table 4.31: Waterborne diseases’ incidences with respect to urban water
supply options
Urban Water Supply Options
Diarrhoea Typhoid Eye infections
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Piped water supply with reservoir
20 31 65 0 0 0 10 11 91
Piped water supply without reservoir
27 56 49 4 15 27 22 40 55
Hand pump connected to supply line
54 87 63 6 29 21 33 65 51
Grand Total: 101 174 59 10 44 23 65 116 57
72
Table 4.32: Community wise waterborne diseases’ incidences with respect
to urban water supply options
Community Gender
Number of Incidences
Piped water supply with reservoir
Piped water supply without
reservoir
Hand pump connected to supply line
Dia
rrho
ea
Typhoid
Eye
infe
ctions
Dia
rrho
ea
Typhoid
Eye
infe
ctions
Dia
rrho
ea
Typhoid
Eye
infe
ctions
Slum
Female 3 0 3 7 1 4 19 4 9
Male 5 0 4 5 1 7 22 2 15
Sub Total: 8 0 7 12 2 11 41 6 24
Low-income
Female 6 0 2 6 1 4 4 0 3
Male 6 0 1 9 1 7 9 0 6
Sub Total: 12 0 3 15 2 11 13 0 9
Grand Total: 20 0 10 27 4 22 54 6 33
(d) Distance and Time Related with Water Sources: In this study Table 4.33 and
Table 4.34 show that incidences of waterborne diseases queried against distance
and time taken to fetch water from its sources respectively. Though the number of
incidences are more within 50m distance or < 5minutes walk. This happened due to
the fact, the maximum people reside within 50m distance or < 5minutes walk. But
however percentage of exposure found to be more for consumers who had to fetch
water from longer distance.
73
Table 4.33: Waterborne diseases’ incidences with respect to distance
between HH and source
Distance Between HH and Water Source
Diarrhoea Typhoid Eye infections
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
<50m 81 137 60 7 30 24 51 98 53
<100m (50m-100m) 6 18 34 3 14 22 5 5 100
<250m (100m-250m) 14 19 74 0 0 0 9 13 70
Table 4.34: Waterborne diseases’ incidences with respect to time taken to
fetch water from source
Time Taken to Fetch Water from
Source
Diarrhoea Typhoid Eye infections
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
5 minutes 81 137 60 7 30 24 51 98 53
5-15 minutes 3 18 17 2 9 23 2 6 34
15-30 minutes 17 19 90 1 5 20 12 12 100
74
(e) Water Demand: This entails the usual quantity of water accessible to
communities. Table 4.35 shows the number of incidences with respect to water
demand as observed during survey.
Table 4.35: Waterborne diseases’ incidences with respect to water received
against demand
Water Received Against Demand
Diarrhoea Typhoid Eye infections
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Full/As per demand 5 5 100 2 6 34 3 5 60
75% of demand 29 50 58 2 8 25 36 50 72
50% of demand 67 119 57 6 30 20 26 61 43
(f) Water Boiling Practices: Since boiling practices depend on the availability of
fuel, awareness of diseases it also guide user to boil water at certain time duration
so as to reduce the pathogens survival rate. Table 4.36 shows the incidences with
respect to water boiling practices while Table 4.37 shows the incidences with
Table 4.36: Number of waterborne diseases’ incidences with respect to
boiling of water.
Water Boiling Practices
Diarrhoea Typhoid Eye infections
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Yes 35 62 57 2 6 34 15 31 49
No 66 112 59 8 38 22 50 85 59
75
respect to water boiling duration for the HHs having boiling practices in vogue.
Table 4.37: Number of waterborne diseases’ incidences with respect to time
spent for boiling of water.
Water Boiling Time
Diarrhoea Typhoid Eye infections
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
5-15 minutes 10 18 56 2 6 34 0 0 0
15-30 minutes 25 44 57 0 0 0 15 31 49
Total: 35 62 57 2 6 34 15 31 49
(g) Storage of Water: Table 4.38 shows the incidences with respect to water
storage system. It clearly shows that though the use of patil as storage system is not
that versatile; the high values of percentage in exposure suggests further as non-
hygienic means of storing drinking water.
Table 4.38: Waterborne diseases’ incidences with respect to storage of
water.
Water Storage System
Diarrhoea Typhoid Eye infections
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Drum 20 45 45 3 15 20 0 25 0
Kolosh 55 84 66 5 21 24 36 67 54
Patil 4 5 80 0 0 0 0 0 0
Water Bottle 22 40 55 2 8 25 17 24 71
(h) Sanitary Practices: Table 4.39 shows the incidences with respect to
sanitation system that the community uses every day.
76
Table 4.39: Number of waterborne diseases’ incidences with respect to
sanitary practices.
Sanitary System
Diarrhoea Typhoid Eye infections
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Sanitary sewer 2 6 34 0 0 0 3 6 50
Septic tank system 32 54 60 1 4 25 19 43 0
Pit latrine 50 81 62 7 28 25 38 52 74
Hanging latrine 7 11 64 0 0 0 1 6 17
Unsanitary 10 22 46 2 12 17 4 9 45
(i) Hygiene Practices: Table 4.40 shows the incidences with respect to hygiene
practices using different hand wash media like soap, ash, soil etc.
Table 4.40: Number of waterborne diseases’ incidences with respect to
hand wash media.
Hygiene Practices- Hand
Wash Media
Diarrhoea Typhoid Eye infections
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Soap 46 84 55 4 14 29 25 61 41
Ash/soil 2 3 67 0 0 0 0 0 0
Nothing 52 85 62 6 30 20 35 55 64
(j) Water Quality: In this study, quantitative analysis of water has been done
using microbiological qualities‟ results i.e. presence of faecal coliform as an
indicator. Table 4.41 shows overall health impacts with respect to faecal coliform
concentration (cfu/100ml).
77
Table 4.41: Overall health impacts based on water quality (FC concentration)
Water Quality (cfu/100ml)
Diarrhoea Typhoid Eye infections
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
Nu
mb
er
of
Incid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce
aga
inst
Exp
osu
re
0-100 18 39 47 3 13 24 4 15 27
100-200 29 46 64 2 6 34 22 32 69
200-300 47 79 60 5 25 20 35 57 62
300-400 7 10 70 0 0 0 4 12 34
(k) Sanitary Inspection (SI): According to the methods described in the Section
3.3.4, a detail risk grading done based on the risk score of each water point and has
been given in Table H.1 of Appendix H. The overall grading of the selected areas,
communities and urban water supply system based on SI risk score have been
given in Table H.2 to Table H.4 of Appendix H. Table 4.42 shows the overall
incidences with respect to SI risk grade.
Table 4.42: Number of waterborne diseases’ incidences with respect to SI
risk grade.
SI Risk Grade
Diarrhoea Typhoid Eye infections
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Nu
mb
er
of In
cid
en
ces
Nu
mb
er
of F
am
ily
Me
mb
ers
Exp
ose
d
% o
f in
cid
en
ce a
ga
inst
Exp
osu
re
Medium 37 57 65 3 10 30 18 36 50
High 52 105 50 7 34 21 37 65 57
Very High 12 12 100 0 0 0 10 15 67
4.4.4 Economic Valuation of Diseases
It was revealed that the surveyed population expended the most for diarrhoea,
typhoid and eye infections. Hence for economic valuation, these three waterborne
78
diseases have been considered. During economic valuation, “Cost of illness
approach” of Market based methods has been considered in the calculation.
Accordingly the direct and indirect costs involved were explored as it can be seen in
the Table 4.43 to Table 4.45.
Table 4.43: Cost of waterborne disease- Diarrhoea
Serial No
Description Observation
(No)
Cost of Diarrhoea (Taka)
Mean Std.Dev. Min Max
1. Home treatment 33 227.27 211.86 30.00 1000.00
Transportation 27 107.41 108.93 50.00 600.00
Doctor‟s fee 28 180.71 135.04 30.00 500.00
Medical expenses 33 278.79 146.32 100.00 600.00
Direct cost of Diseases 33 759.39 438.26 230.00 1850.00
2. Parent‟s work lost (when both/either of them is patient)
17 446.61 349.57 131.00 1313.00
Parent‟s work lost due to child disease
33 356.71 253.78 66.00 1225.00
Parent‟s leisure lost due to child disease
32 181.19 140.62 33.00 591.00
Indirect cost of Diseases
33 762.48 479.06 175.00 1772.00
3. Total cost: 1521.88
4. No of Days to suffer: 33 5.03 2.02 3 10
Table 4.44: Cost of waterborne disease- Typhoid
Serial No
Description Observation
(No)
Cost of Typhoid (Taka)
Mean Std.Dev. Min Max
1. Home treatment 7 1107.14 497.01 500.00 2000.00
Transportation 7 235.71 124.88 100.00 500.00
Doctor‟s fee 6 291.67 162.53 150.00 500.00
Medical expenses 7 1828.57 1704.62 300.00 5000.00
Direct cost of Diseases 7 3621.43 2070.80 1700.00 7600.00
2. Parent‟s work lost (when both/either of them is patient)
2 1969.20 0.00 1969.00 1969.00
Parent‟s work lost due to child disease
5 805.18 358.66 459.00 1313.00
Parent‟s leisure lost due to child disease
5 312.88 199.58 153.00 656.00
Indirect cost of Diseases
7 1361.25 715.60 613.00 2626.00
3. Total cost (Taka): 4982.68
4. No of Days to suffer: 7 17.43 7.18 7 30
Detail calculation of estimated health impact valuation of waterborne diseases has
been given in Appendix K.
79
Table 4.45: Cost of waterborne disease- Eye infections
Serial No
Description Observation
(No)
Costs of Eye Infections (Taka)
Mean Std. Dev.
Min Max
1. Home treatment 14 47.14 21.00 25.00 100.00
Transportation 7 32.86 16.04 20.00 50.00
Doctor‟s fee 8 81.25 54.10 30.00 200.00
Medical expenses 23 138.04 33.60 50.00 200.00
Direct cost of Diseases 23 205.00 80.58 50.00 400.00
2.
Parent‟s work lost (when both/either of them is patient)
20 559.03 327.74 109.00 1072.12
Parent‟s work lost due to child disease
13 279.39 141.84 109.00 459.48
Parent‟s leisure lost due to child disease
14 110.96 52.35 44.00 229.74
Indirect cost of Diseases 23 711.58 427.98 131.00 1531.60
3. Total cost (Taka): 916.58
4. No of Days to suffer: 23 6.26 1.45 3 10
4.4.5 Analysis of Prevalence Rate
It has already been discussed in Section 2.10.2 that PR values differ basing on the
value of denominator i.e. total population surveyed. Hence different PR value of
same group could be found out if different denominator value is used. In this study,
prevalence rate for all three major diseases of vulnerable people of different age-
groups and genders have been considered. Moreover attempt has been made to
show the prevalence rate of those diseases among the different communities, areas
and urban water supply options also. The basic data for prevalence rate has been
given in the following tables as Table 4.46 to Table 4.49.
Table 4.46: Basic data for prevalence rate of different age-groups
Age Group (Years)
Gender Surveyed
Population (Number)
Number of Incidences
Diarrhoea Typhoid Eye
Infections
<5 F 16 10 2 3
M 17 5 1 7
5-14 F 20 9 1 8
M 26 18 1 9
>15 F 60 26 3 14
M 71 33 2 24
F 96 45 6 25
M 114 56 4 40
For Entire Sample 210 101 10 65
80
Table 4.47: Basic data for prevalence rate of different community
Community Surveyed
Population
Number of Incidences
Diarrhoea Typhoid Eye
Infections
Slum 117 61 8 42
Low-income 93 40 2 23
Total 210 101 10 65
Table 4.48: Basic data for prevalence rate of different selected areas
Selected Areas Surveyed Population
Number of Incidences
Diarrhoea Typhoid Eye Infections
Gulshan 56 30 3 36
Tejgaon 48 21 2 11
Badda 42 20 3 12
Mirpur 64 30 2 6
Total 210 101 10 65
Table 4.49: Basic data for prevalence rate of different urban water supply
options
Urban Water Supply Options Surveyed
Population
Number of Incidences
Diarrhoea Typhoid Eye
Infections
Piped water supply with reservoir 37 20 0 10
Piped water supply without reservoir 77 27 4 22
Hand pump connected to supply line 96 54 6 33
Total 210 101 10 65
The detail calculation of prevalence rate has been given in Table L.1 through L.6 of
Appendix L, where Table L.1 through L.3 show the prevalence rates of different age-
groups of different genders and Table L.4 to Table L.6 show the prevalence rates of
the different communities, areas and urban water supply options respectively.
81
4.5 Development of Correlation Between Diarrhoea Patient Reproting
Cases and Climatic Factors
4.5.1 Identification of Correlation
Since the diarrhoeal diseases are major concerned as per as waterborne diseases
incidences; hence the monthly average data of 11 years (2000 to 2010) have been
used as given in the Table M.1 of Appendix M. Here, Appendix M has been
developed from the data given in Appendix D and Appendix F. Taking data (from
2000 to 2010) from Appendix D to identify the average state of diarrhoeal incidences
for the selected areas and Dhaka as a whole following Figure 4.12 can be
generated:
Figure 4.12: Trend of diarrhoeal patients of sample area and Dhaka
This 11 years result shows that the surge of patients start from March and ends
around 1st week of June (taking 600 patients as base line) and again starts from
mid of July and ends on October. Following figures i.e. Figure 4.13 through Figure
4.15 show the pattern of both factors.
0
200
400
600
800
1000
1200
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Nu
mb
er
of
Dia
rrh
oeal
Pati
en
ts
Month
Average representative data of Dhaka City
Average representative data of Selected Areas
82
Figure 4.13: Diarrhoeal patients of sample area and average rainfall
Figure 4.14: Diarrhoeal patients of sample area and average temperature
Figure 4.15: Diarrhoeal patients of sample area and average humidity
0
100
200
300
400
500
600
700
0
500
1000
1500
2000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Rain
fall(
mm
)
Num
ber
of
Patients
Month
Tejgaon Badda Gulshan Mirpur Rainfall(mm)
17
19
21
23
25
27
29
31
0
500
1000
1500
2000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Tem
pera
ture
(°C
)
Num
ber
of
Patients
Month Tejgaon Badda Gulshan Mirpur Temperature(°C)
50.0
55.0
60.0
65.0
70.0
75.0
80.0
85.0
0
500
1000
1500
2000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Hum
idity
(%)
Num
ber
of
Patients
Month
Tejgaon Badda Gulshan Mirpur Humidity(%)
83
Basing on the figures above, it can be seen that Figure 4.18 i.e. figure representing
diarrhoeal patients of sample area and average temperature is the best suiting.
Now if the climatic factors are plotted against diarrhoeal patients of selected areas
of Dhaka city on scatter chart, following Figure 4.16 through Figure 4.18 will be
found. On the other hand using formula of correlation coefficient in Section 2.11.5
same can be found out for each selected areas of Dhaka city as given in Table 4.50.
Figure 4.16 Diarrhoeal patients-rainfall correlation (2000-2010)
Figure 4.17 Diarrhoeal patients-temperature correlation (2000-2010)
0
200
400
600
800
1000
1200
1400
1600
1800
0 100 200 300 400 500
Nu
mb
er
of
Pa
tie
nts
Rainfall (mm)
Tejgaon Badda Gulshan Mirpur
0
200
400
600
800
1000
1200
1400
1600
1800
0 5 10 15 20 25 30 35
Nu
mb
er
of
Pa
tie
nts
Temp(°C)
Tejgaon Badda Gulshan Mirpur
84
Figure 4.18 Diarrhoeal patients-humidity correlation (2000-2010)
Hence it is obvious that temperature has better correlation than rainfall and humidity
and hence has direct impact on the diarrhoeal diseases. Calculations of correlation
Table 4.50: Correlation coefficient of climatic parameters and diarrhoeal
incidences of the selected areas
Selected Areas Correlation Coefficient(Cr)
Rainfall Temperature Humidity
Tejgaon 0.306613 0.716571 0.037387
Badda 0.461451 0.712855 0.38716
Gulshan 0.241612 0.633132 0.085564
Mirpur 0.508958 0.81561 0.311589
factor for the generalized data of selected areas and Dhaka city have been given in
the Table M.3 and Table M.4 of Appendix M respectively.
4.5.2 Development of Correlation Equation
After identification of correlation, the correlation equations for temperature with the
selected areas and Dhaka as a whole have been developed. Basing on the data as
given in the Table M.1 of Appendix M, following table shows the acceptance of
equation as developed using Microsoft Excel software:
0
200
400
600
800
1000
1200
1400
1600
1800
0.0 20.0 40.0 60.0 80.0 100.0
Nu
mb
er
of
Pa
tie
nts
Humidity(%)
Tejgaon Badda Gulshan Mirpur
85
Table 4.51: Selection of correlation equation based on correlation
coefficients
Area Linear Non-linear (Logarithmic)
Equation R2 Cr Equation R
2 Cr
Tejgaon y =25.131x - 225.92 0.5135 0.71659 y =10^(0.0292x + 1.8517) 0.6186 0.78651
Badda y = 43.126x - 519.99 0.5082 0.71288 y =10^(0.0346x + 1.8506) 0.6275 0.79215
Gulshan y = 18.794x + 51.775 0.4009 0.63317 y =10^(0.0152x + 2.3295) 0.4548 0.67439
Mirpur y = 77.364x - 1116.6 0.6652 0.8156 y =10^(0.0428x + 1.8067) 0.8249 0.90824
Avg. Study Areas
y = 41.083x - 451.88 0.6393 0.79956 y =10^(0.032x + 1.9392) 0.7507 0.86643
Dhaka y = 19.002x - 136.98 0.5544 0.74458 y =10^(0.0244x + 1.9045) 0.6387 0.79919
From above correlation coefficients, it is understood that the non- linear equations
are better suited than linear equation. As such Figure 4.19 shows result of the
exponential equations of selected areas and Dhaka- developed in terms of equation
lines on the scatter chart using MS Excel software.
Figure 4.19: Average diarrhoeal patients-temperature correlation for study
areas and Dhaka as a whole (2000-2010)
y = 0.032x + 1.9392 R² = 0.7507
y = 0.0244x + 1.9045 R² = 0.6387
2.00
2.20
2.40
2.60
2.80
3.00
3.20
17 19 21 23 25 27 29 31
Log(
Ave
rage
Nu
mb
er
of
Pat
ien
ts)
Temperature (°C)
Avg No. of Patients(Selected Area) Avg No. of Patients(Dhaka)
EQ Line(Selected Area) EQ Line (Dhaka)
86
Equation for the Average Number of Patients of Selected Areas: From the
above figure, Equation 4.1 can be shown for the average number of patients
of selected areas and temperature.
Ysa = 10(0.032x + 1.9392) (4.1)
Where x stands for the temperature in degree and Ysa stands for average
number of patients of the selected areas affected by diarrhoea with a
standard deviation of 183 numbers of patients. Here Ysa has been rounded
up to the next higher number in case of decimal.
Equation for the Average Number of Patients of Dhaka: Again the Equation
4.2 can be shown for the average number of patients of Dhaka and
temperature.
Ydk = 10(0.0244x + 1.9045) (4.2)
Where x stands for the temperature in degree and Ydk stands for average
number of patients of Dhaka affected by diarrhoea with a standard deviation
of 91 numbers of patients. Here Ydk has been rounded up to the next higher
number in case of decimal value.
87
CHAPTER 5
RESULTS AND DISCUSSIONS
5.1 Introduction
In this chapter, the results of the thesis paper have been presented. Initially an
attempt was made to identify the most affected administrative areas of Dhaka city as
per as waterborne diseases are concerned. From there only top four were selected
and data collected from those localities as such. During questionnaire survey the
questions were so chosen in order to ascertain the qualitative assessment of urban
water supply, sanitation and hygiene. Here the qualitative assessment was based
on the number of HH responded to a specific issue. These results are presented in
terms of charts and tables. On the other hand quantitative assessment denotes
health impacts as a result of those factors were counted in terms of number of
incidences taking place last one year. Basing on these results the prevalence rates,
economic valuation were done and presented in charts and tables. It has to be
remembered that selection of administrative areas of Dhaka city were based on the
reported cases/incidences of waterborne diseases; whereas the result based on the
field survey, it was mostly non reporting to hospital and clinic cases- relating with
most common waterborne diseases like diarrhea, typhoid and eye infections .
5.2 Qualitative Assessment
5.2.1 Urban Water Supply Options
This study has identified three types of urban supply options (Table 3.3) mainly
connected by two types of sources. From Table 4.6 it is seen that maximum number
of HHs (65%) had their supplied water of DWASA through private connections and
the rest 35% had their supplied water of DWASA through public connections. No
shallow tubewells were noticed during survey. These public connections also
included some conventional public stand-posts. On the other hand, most of the
private connections were made with unreliable materials like flexible rubber, leaky
PVC or GI pipes for collection of drinking water from DWASA line to their point of
distribution. The photographed images (Image 4.1 to 4.3) showed the extent of
vulnerabilities of visited communities and their state of awareness about health
education or hygiene. Figure 5.1 shows the overall state of the urban water supply
options where it has been revealed that about 47% of HHs are having hand pump
88
connected to supply line, 38% of HHs are having piped water supply without
reservoir and rest 15% HHs are having piped water supply with reservoir. So it was
about 85% of the total HHs those were to rely on uncertain water availability.
Moreover due to poor materials used in hand pump option for connection, there are
more likelihood of various contamination en-route than usual.
Figure 5.1: Overall state of different water supply options
Figure 5.2 shows the overall state of community wise water supply options
Figure 5.2: Community wise state of different water supply options
It shows that slum community is having more percentages of hand pumps
connected to supply line; whereas low-income groups are having piped water supply
15%
37% 48%
Piped water supply with reservoir Piped water supply without reservoir
Hand pump connected to supply line
0%
20%
40%
60%
80%
100%
Supplied waterthrough private
connection.
Supplied waterthrough public
connection
Supplied waterthrough private
connection.
Supplied waterthrough public
connection/Tapwater
Slum Low in-comePiped water supply with reservoir Piped water supply without reservoir
Hand pump connected to supply line
89
without reservoir. This also shows the state of vulnerability in terms of contamination
associated with slum community using hand pump option and in terms of non-
availability of water with slum and low-income communities.
5.2.2 Distance of Water Source and Time Require to Fetch Water
From Table 4.9 and 4.10, it can be seen that maximum percentage (77%) of the
surveyed HHs were residing very close (<50 m) to the sources thus taking very less
time (around 5 minutes) to fetch water. On the other hand, basing on the urban
water supply options, it can be seen that 79% hand pumps connected to supply line
were located closer to <50m distance. The slum community was to travel maximum
distance to fetch water than that of low-income and spending longer time for this
case. Taking longer time includes journey time, queue time and collection time of
water from the source. When large number of populations sharing the same water
point then the time spent in queue was more than that of journey time. This was
observed for slum community residing at Gulshan area. The Figure 5.3 to 5.5 shows
the state of community type, urban water supply options and overall condition
against the distance from HH to source.
Figure 5.3: Community wise different distance range between households and
water source.
0%
20%
40%
60%
80%
100%
Slum Low-income
Nu
mb
er
of
HH
(%
)
Community Type
<50m <100 (50-100)m <250 (100-250) m
90
Figure 5.4: Urban water supply options wise different distance range between
households and water source.
Figure 5.5: Overall state of different distance range between households and
water source.
5.2.3 Quantity and Accessibility to Water
From Table 4.12 and Figure 5.6, it is evident that slum community had less quantity
and less accessibility to water. On the other hand, Figure 5.7 shows that the HHs
having hand pump connected to WASA lines got less water than their expected
demand. Other options i.e. piped water supply with and without reservoir had mixed
demand mitigation. However Figure 5.8 shows the overall condition of the state of
the quantity of water the communities were having every day. It is seen that 95% of
HHs never had their demand fulfilled out of which only 55% could mitigate their daily
need by just half of their demand. Only 5% showed their fulfillment of their demand
as per as water availability are concerned.
02468
101214161820
Piped water supply withreservoir
Piped water supplywithout reservoir
Hand pump connectedto supply line
Nu
mb
er
of H
H
Urban Water Supply Options
<50m <100 (50-100)m <250 (100-250) m
77%
8% 15%
<50m <100 (50-100)m <250 (100-250) m
91
Figure 5.6: State of different water demand against community type
Figure 5.7: State of different water demand against urban water supply options
Figure 5.8: Overall state of different water demand fulfillment
0%
20%
40%
60%
80%
100%
Slum Low-income
Num
ber
of
HH
s
Community Type
Full/As per demand 75% of demand 50% of demand
0%
20%
40%
60%
80%
100%
Piped water supply withreservoir
Piped water supply withoutreservoir
Hand pump connected tosupply line
Nu
mb
er
of
HH
s (%
)
Water Demand
Full/As per demand 75% of demand 50% of demand
5%
40% 55%
Full/As per demand 75% of demand 50% of demand
92
5.2.4 Water Boiling Practices
During interview it was found that though the communities were aware of boiling of
water and its effect in maintaining good health but due to economic reason
especially the slum people avoid boiling of water. Based on such information of
Table 4.14, the Figure 5.9 clearly shows the state of boiling practices among the
communities. Again the low-income community has mixed proportion of boiling
water. Figure 5.9 shows that 76% of low-income HHs boil water for drinking
purpose. Since duration of boiling of water plays a vital role in ensuring proper home
treatment of water. The Table 4.15 shows the distribution of this group (13 HHs)
against different time range used for boiling purpose. It shows that there were about
31% of low-income HHs who boiled water for 5-15 minutes and rest 69% of HHs
who boiled water for 15-30 minutes. No HHs were found boiling water more than 30
minutes. Table 4.17 and Figure 5.10 show area wise distribution of HHs practicing
boiling. It shows that more than 90% of HHs residing at Gulshan area, 80% of HHs
at Tejgaon, 50% of HHs at Badda and 40% of HHs at Mirpur did not boil water.
Figure 5.9: Community wise percentages of HHs having water boiling
practices
Figure 5.11 shows the overall state of the water boiling practices as prevailing within
the community. It is evident from this state that large number of people (68%) do not
boil their water for drinking purpose though they already aware about the
consequences. However because of the economic reason they avoid doing that
practices at home.
0%
20%
40%
60%
80%
100%
Slum Low-income
Nu
mb
er
of
HH
s (%
)
Community Type
Yes No
93
Figure 5.10: Sample area wise state of water boiling practices by HHs.
Figure 5.11: Overall state of water boiling practices observed in the study area
5.2.5 Storage of Water
As it has been discussed that this study identified mainly 4 types of storage
container like drum, kolosh, patil and water bottle. From Table 4.16 it was shown
55% of HHs alone accounted for kolosh type storage system as it can be seen in
the Figure 5.12 below also. Figure 5.13 shows the pattern of water storage system
maintained by the vulnerable communities. It shows that low-income community
(82%) stored their water mostly in kolosh but slum community stored their water
equally in drum (35%), kolosh (35%) and water bottle (30%).
0%
20%
40%
60%
80%
100%
Gulshan Tejgaon Badda Mirpur
HH
Nu
mb
er
Sample Areas
Yes No
32%
68%
Yes No
94
Figure 5.12: Overall state of different water storage system
During survey, it was observed that though the containers were covered by the lids
but drums and water bottle were maintained poorly. Slums were often found putting
the utensils like mug, jug etc. inside their drums without washing those properly in
order to take water. Those practices could be detrimental in keeping good health.
Figure 5.13: Community wise number of HHs for different water storage
system
Figure 5.14 shows the sample area wise distribution of HHs for different water
storage system. It shows that in Gulshan, the use of drum, Kolosh and water bottle
were more or less equal in proportion. But for the rest 3 areas, it was the Kolosh
which were used extensively in their respective areas.
22%
55%
3%
20%
Drum Kolosh Patil Water Bottle
0%
20%
40%
60%
80%
100%
Slum Low-income
Nu
mb
er
of
HH
s
Community Type
Drum Kolosh Patil Water Bottle
95
Figure 5.14: Sample area wise number of HHs for different water storage
system
5.2.6 Sanitation Systems
Table 4.19 shows the type of sanitary practices observed within the communities of
the study areas. It is evident from the table that slum community had more pit latrine
system (64%) where low-income community based on septic tank system (67%).
However a substantial number of slum HHs were found to be using hanging and
unsanitary latrines. On the other hand Figure 5.15 shows area wise distribution of
Figure 5.15: Distribution of HHs according to sample area based on sanitation
system in use.
0%
20%
40%
60%
80%
100%
Gulshan Tejgaon Badda Mirpur
Nu
mb
er
of H
Hs
Sample Area
Sanitary sewer Septic tank system Pit latrine Hanging latrine Unsanitary
0%
20%
40%
60%
80%
100%
Gulshan Tejgaon Badda Mirpur
Nu
mb
er
of
HH
s
Sample Area
Drum Kolosh Patil Water Bottle
96
sanitation system. It shows that 92% of HHs at Gulshan, 30% of HHs at Tejgaon
and 40% at Mirpur used pit latrine system. On the other hand, there were almost
equal percentage of HHs using septic tank system in Tejgaon (50%), Badda (50%)
and Mirpur (40%). There were about 25% HHs of Badda found defecating in the
field (unsanitary system). Figure 5.16 shows the overall state of sanitary practices in
the sample area. It shows that about 45% of the population depended on community
based pit latrine sanitation system followed by septic tank system (32%). On the
other hand, about 13% of surveyed population went for unsanitary system and very
small portion (5%) were using sanitary sewer and hanging latrine system.
Figure 5.16: Overall state of sanitary practices in the sample area.
5.2.7 Hygiene Practices-Use of Hand Wash Medium
Table 4.21 and Figure 5.17 show that a large number of people (48%) used nothing
after defecation which shows the lack of hygiene education among the community
members. Again Figure 5.18 shows the community wise state of the hygiene
practices. It shows that 83% of slum HHs did not use any media to wash their
hands, on the contrary 100% low-income HHs were found very much aware about
use of media (in this case soap). Figure 5.19 shows the area wise state of the
hygiene practices. It was found that 83% of HHs of Gulshan and 50% of Badda did
not use any medium to wash their hands in order to maintain good health.
5%
32%
45%
5% 13%
Sanitary sewer Septic tank system Pit latrine Hanging latrine Unsanitary
97
Figure 5.17: Overall state of hygiene practices
Figure 5.18: Community wise distribution of HHs based on hand wash media.
Figure 5.19: Sample area wise distribution of HHs based on hand wash
medium.
0%
20%
40%
60%
80%
100%
Gulshan Tejgaon Badda Mirpur
Nu
mb
er
of
HH
s
Sample Area
Soap Ash/Soil Nothing
50%
2%
48%
Soap Ash/Soil Nothing
0%
20%
40%
60%
80%
100%
Slum Low-income
Nu
mb
er
of
HH
s
Community Type
Nothing Ash/Soil Soap
98
5.2.8 Water Quality of Collected Samples
(a) Aesthetic Water Quality: From Table 4.13 it is seen the communities of
different areas were facing different kind of aesthetic water qualities. While
communities at Tejgaon (70%) and Badda (75%) complained their water to be
odorous but the communities at Gulshan (50%) and Mirpur (40%) were experiencing
water mixed with foreign materials. Again from Figure 5.20, it is seen that the water
collected by slum community was often contained dirt/foreign materials but the
water collected by low income group were often odorous water. As per as urban
water supply options, the 67% of hand pumps connected to supply line provided
occasional odorous water to the community; whereas 61% of .piped water supply
without reservoir provided water with dirt/foreign materials. Figure 5.21 shows the
overall state of aesthetic quality of water of study area. It shows that 44% of the HHs
were experiencing occasional odorous water and 33% of the HHs were
experiencing dirt/foreign materials.
Figure 5.20: Community wise percentages of households reporting the
aesthetic quality of water.
0%
20%
40%
60%
80%
100%
Slum Low-income
Nu
mb
er
of
HH
Re
po
rtin
g (%
)
Community Type
Clean and fresh Odorous Turbid Contains dirts and other foreign matterials
99
Figure 5.21: Overall state of aesthetic quality of water of study area
(b) Physical Parameters:
Turbidity
The turbidity of all water samples tested was within the Bangladesh Standard of
10 NTU, with a median value of 1.00 NTU and maximum value of 2.91 NTU.
pH
From the Appendix I, it can be seen that pH of the tested water samples varied
from 6.10 to 7.84. There are about five samples (21%) have pH value less than
6.5. The mean value, median value and standard deviation are 6.82, 6.78 and
0.45 respectively. These standard values were nearly satisfying the Bangladesh
Standard of 6.5 to 8.5. pH distribution of the water points are given in the Figure
5.22 and 5.23.
Figure 5.22: pH distribution of the water sample of different communities
17%
45%
5%
33%
Clean and fresh Odorous Turbid Contains dirts and other foreign matterials
0%
10%
20%
30%
40%
50%
60%
<6.0 6.0-6.5 6.5-7.0 7.0-7.5 7.5-8.0 8.0-8.5
% o
f Fr
eq
ue
ncy
pH Range
Slum Low-income
100
Figure 5.23: pH distribution of the water sample of different areas
(c) Chemical Parameter:
Chlorine (Residual)
The concentration of chlorine was tested to check the adequacy of the chlorine
level to safeguard against potential microbial contamination in the distribution
network. If the chlorine level is more than 0.05 mg/l for a contact period of 10-20
minutes, it would be effective in killing pathogen (Ahmed and Rahman, 2000).
There are about eleven samples (46%) those have chlorine values less than
0.05mg/l and there are fourteen samples (58%) those have chlorine value less
than the Bangladesh Standard i.e. 0.2 mg /l. Improper chlorination done at deep
tubewell pump locations could be the major reasons for these large percentage
of non-availability of chlorine at the delivery end. It can be seen from Appendix I
that chlorine of the tested water samples varied from 0.01 mg/l to 1.02 mg/l. The
mean value, median value and standard deviation are 0.30, 0.16 and 0.35 mg/l
respectively.
(d) Microbiological Quality: As discussed in Section 4.4.2. that excluding
DWASA pump house water samples, other samples contained varying degree FC
concentration and maximum (67%) shown in the range of 100-300 cfu/100ml. Figure
5.24 shows the percentage exceeding the stated values for the different
communities. It shows, e.g. at the FC concentration of 100 cfu/100ml, while the slum
has 77% of its samples exceeding the given concentration; low-income group has
0%
20%
40%
60%
80%
100%
<6.0 6.0-6.5 6.5-7.0 7.0-7.5 7.5-8.0 8.0-8.5
% o
f Fr
eq
ue
ncy
pH Range
Gulshan Tejgaon Badda Mirpur
101
91% of its samples exceeding the stated concentration. Figure O.3 of Appendix O
shows the FC concentration in selected areas.
Figure 5.24: Microbial water qualities of water supply in different communities
5.2.9 Sanitary Inspection (SI)
From H.1 of Appendix H, the overall condition of the water point including the
WGWSPs can be seen in the Figure 5.25. It is clearly understood that more than
50% of the water points were not sanitarily in sound condition, indicating poor
maintenance, a very low level hygiene awareness and a very high level potential
threat of water related diseases to the communities using those. Again from the
Figure 5.25: State of overall SI risk grading of water points of study area.
Table 4.25 and Figure 5.26, it is seen that slum water points were more vulnerable
and susceptible to source related contamination than low-income community and
likely to have more incidences of waterborne diseases. Figure 5.27 generated from
Table H2 of Appendix H shows the overall SI grading of the community.
11%
37% 45%
7%
Low Medium High Very High
0
20
40
60
80
100
0 100 200 300 400
% E
xcee
din
g th
e st
ate
d F
C
cou
nt
FC Count (cfu/100ml)
Slum Low-income
102
Figure 5.26: Comparative state of communities based on SI risk grading.
Figure 5.27: Overall state of communities based on SI risk grading.
Similarly Figure 5.28 shows that it was Gulshan area which is the most vulnerable
area followed by Mirpur, Tejgaon and Badda respectively. This was also seen in the
Figure 5.29 shows the overall SI grading of the selected areas.
Figure 5.28: Comparative state of vulnerable areas based on SI risk grading.
0%
20%
40%
60%
80%
100%
Slum Low-income
Wat
er
Po
int
Co
vera
ge
Community Type
Medium High Very High
7
5.7
0
2
4
6
8
10
Slum Low-income
Gra
de
d R
isk
Sco
re
Community Type
0%
20%
40%
60%
80%
100%
Gulshan Tejgaon Badda Mirpur
Wat
er
Po
int
Co
vera
ge
Sample Area
Medium High Very High
103
Figure 5.29: Overall state of selected areas based on SI risk grading.
On the other hand, in Figure 5.30 shows the water points having both urban water
supply options like hand pump connected to supply line and piped water supply
without reservoir possess high percentage of high grade coverage indicating low
level maintenance at the source by the user group. Both the options have very little
differences in risk grading as can be seen in the Figure 5.31.
Figure 5.30: Comparative state of urban water supply options based on SI risk
grading.
7.50
6.10 5.80 6.30
0
1
2
3
4
5
6
7
8
9
10
Gulshan Tejgaon Badda Mirpur
Gra
de
d R
isk
Sco
re
Sample Area
0%
20%
40%
60%
80%
100%
Piped water supply withreservoir
Piped water supply withoutreservoir
Hand pump connected tosupply line
Wat
er
Po
int
Co
vera
ge
Urban Water Supply Options Medium High Very High
104
Figure 5.31 Overall state of urban water supply options based on SI risk
grading.
5.3 Quantitative Assessment
In the Figure 5.32 shows the overall state of the affected and non-affected persons
of the study area. It was found out that about 58%, 23% and 56% of HH members
were affected by diarrhoea, typhoid and eye infections respectively. Figure 5.33
shows the gender distribution of the affected persons. It represents that male were
more vulnerable to the waterborne diseases. This could be that male were away
from houses and consumed water and food from unreliable sources.
Figure 5.32: Overall state of waterborne diseases of interviewed households
4.78
6.65 6.71
0
1
2
3
4
5
6
7
8
9
10
Piped water supply withreservoir
Piped water supply withoutreservoir
Hand pump connected tosupply line
Gra
de
d R
isk
Sco
re
Urban Water Supply Options
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Diarrhoea Typhoid Eye Infections
Nu
mb
er
of
Inci
de
ncs
Affected Not Affected
105
Figure 5.33: Gender distributions of the affected persons
Figure 5.34 shows gender wise age-group diarrhoeal incidences. Here it is seen that
female children <5 years suffer from diarrhoea just double than male percentage.
Gender difference in the family could be one of the main reasons where female
children (<5 years) are not equally taken care by their parents of vulnerable
communities. On the contrary male group of age more than 5 years had more
Figure 5.34: Comparison between male and female diarrhoeal incidences
vulnerability than female of same age group. This could be that male children are
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Diarrhoea Typhoid Eye Infections
% o
f In
cid
en
ces
Diseases
Female (F) Male (M)
10%
9%
26%
5%
18%
32%
Female (45%) Male (55%)
<5 Years 5-14 Years >15 Years
106
more susceptible than female due to their nature of activities/works and had more
contact with external food and contaminated environment.
Within the age-groups of both genders, it is seen that the elderly people (> 15 years)
suffer much. These can be seen in the following Figure 5.35 (a-1,a-2 and a-3):
Figure 5.35 State of different gender age-groups for waterborne diseases
a-2
a-3
a-1
107
Health impacts with respect to each factor as described in the Section 4.4.3 have
been given in Appendix N in details. Basing on the assessment following overall
evaluation can be made:
5.3.1 Overall Evaluation on Health Impacts
(a) Community Wise: From the Table J.1 of Appendix J, the combined
vulnerability score as found for the community can be seen in the Figure 5.36. It
shows that the state of vulnerability for slum is more than that of low-income
community. Figure 5.37 points out that incase of diarrhoea incidences, the slum
community entered into the high vulnerability zones (≥ 6 to <8) due to the SI risk,
Figure 5.36: Overall vulnerability of communities
water quality and time duration to fetch water from the source. It means that these
are the most critical issues those needed to be addressed by improving water point
5.83 5.61
1.42 1.67
6.67
4.34
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
Slum Low-incomeCo
mb
ine
d V
uln
era
bil
tiy S
co
re
Community
Diarrhoea Typhoid Eye Infections
108
R² = 0.9831
R² = 0.9838
0
10
20
30
40
50
0% 25% 50% 75% 100%
Nu
mb
er
of
Inci
de
nce
s
Demand to meet
Slum Low-income Linear (Slum) Linear (Low-income)
Figure 5.37: State of vulnerability of communities based on diarrhoea
incidences
sanitation, replacing of illegal connection between sources and WASA lines with
authorized lines, making easily accessible and adequate water supply to the
community. Same way for the low-income community, sources of water, urban
water supply options, demand of water, boiling practices including time and storage
practices etc. are to be taken care to improve their health and sanitation. It is
evident that slum community had less quantity and less accessibility to water. As a
result when supplied water quantity increased, the diarrhoea incidences were found
to be decreased and their negative correlations for both slum and low-income
community have been given in Figure 5.38. On the other hand, a positive correlation
Figure 5.38: Correlation between demand and number of diarhoea incidences.
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Slum Low-income
109
(r2 = 0.7419) was found between FC count and diarrhoea incidences in percentage
as shown in the Figure 5.39.
Figure 5.39: Correlation between FC count and diarrhoea incidences in percentage.
For typhoid, in Figure 5.40, the slum community vulnerability score is low but still
needed to stress the following points like connections of sources of water,
Figure 5.40: State of vulnerability of communities based on typhoid
incidences
accessibility of water, storage practices, hand wash practices and sanitation of
water points. On the other hand low-income community needs to be very careful
about connections of water of sources, accessibility of water, boiling of water
R² = 0.7419
0
20
40
60
80
100
0 100 200 300 400 500
% o
f in
cid
en
ce a
gain
st E
xpo
sure
FC Count (cfu/100ml)
0
0.5
1
1.5
2
2.5
Vu
lne
rab
ility
Sco
re
Criteria
Slum Low-income
110
practices, hygiene practices and water point sanitation. Figure 5.41 shows the
vulnerability for eye infections for both communities. It clearly indicates that slum
Figure 5.41: State of vulnerability of communities based on eye infections
incidences
community was at the very disadvantageous stage. Due to water sources‟
connection, vulnerable water supply option used, distance between source and HH,
demand, water quality and water point sanitation all these factors pushed this
community into the high vulnerability zones. Apart from personal contact, since eye
infection is depended on the quantity and quality of water used by an individual,
hence those critical issues to be improved in order to reduce the disease. Figure
5.42 shows such correlation (Cr = 0.99) between FC concentration and number of
Figure 5.42: Correlation between SI risk score and percentage of eye
infections’ incidences against exposures.
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Criteria
Slum Low-income
R² = 0.9897
20
40
60
80
0 1 2 3 4
% o
f in
cid
en
ce a
gain
st
Exp
osu
re
Grade on Risk Score
111
eye infections‟ incidences. On the other hand low-income community was exposed
to medium vulnerability range mostly due to high incidence rate of eye infections
with respect to urban water supply system. Now, if all the scores are summed up
then the cumulative vulnerability scores will be as Figure 5.43.
Figure 5.43: The order of community based on cumulative vulnerability scores
(b) Selected Areas Wise: From the Table J.2 of Appendix J, the combined
vulnerability score as found for the areas can be seen in the Figure 5.44.
Figure 5.44: Overall vulnerability of selected areas of Dhaka city
0.00
5.00
10.00
15.00
Slum Low-incomeCu
mu
lati
ve V
uln
erab
ility
Sc
ore
s
Diarrhoea Typhoid Eye Infections
6.55 7.01
3.64
5.57
0.94 0.68 0.80 1.67
8.93
5.38
2.51 2.19
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ined
Vu
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iltiy
Sco
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Selected Areas
Diarrhoea Typhoid Eye Infections
112
It shows that the state of vulnerability for Tejgaon and Gulshan are more than those
of Mirpur and Badda. Figure 5.45 points out that incase of diarrhoea incidences,
Tejgaon and Gulshan entered into the high vulnerability zones (≥ 6 to <8) due to
various reasons like water source‟s connection, urban supply options, distance and
Figure 5.45: State of vulnerability of selected areas based on diarrhoea
incidences
time to fetch water, boiling practices, hand wash practices, water quality and SI risk.
While Gulshan was having problem related with accessibility and adequacy of
water, storage and water point sanitation related issues; Tejgaon suffered more
importantly with demand, boiling practices and water quality. Again the state of
MIrpur was different as the community living there, having problem related with
urban water supply options, storage systems and water point sanitation. Again for
typhoid, Mirpur was suffering much due to inadequate boiling practices, poor
personal hygiene and water point sanitation as it can be seen Figure 5.46.
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Gulshan Tejgaon Badda Mirpur
113
Figure 5.46: State of vulnerability of selected areas based on typhoid
incidences
For eye infections, the communities residing at Gulshan were extremely exposed to
the vulnerable state. The Figure 5.47 shows very high vulnerability score for
Figure 5.47: State of vulnerability of selected areas based on eye infections
incidences
Gulshan while high for Tejgaon. Figure O.7 to Figure O.9 of Appendix O shows
vulnerability state of selected areas according to waterborne diseases. If all the
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Gulshan Tejgaon Badda Mirpur
0
0.5
1
1.5
2
2.5
Vu
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abili
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core
Gulshan Tejgaon Badda Mirpur
114
vulnerability were summed up the results became Figure 5.48 which indicates the
order of vulnerability for the selected areas.
Figure 5.48: The order of selected areas based on cumulative vulnerability
scores
(c) Urban Water Supply Options Wise: From the Table J.3 of Appendix J, the
combined vulnerability score as found for the urban water supply options can be
seen in the Figure 5.49.
Figure 5.49: Overall vulnerability of urban water supply options
It shows that the combined vulnerability scores for diarrhoea with respect to „Hand
pump connected to supply line‟ and „Piped water supply with reservoir‟ are in the
high range. Figure 5.50 points out causes of those increases in details. It is clearly
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
Gulshan Tejgaon Badda MirpurCu
mu
lati
ve V
uln
erab
ility
Sco
res
Diarrhoea Typhoid Eye Infections
6.05 5.65
6.45
2.00 1.29
7.04
5.04 5.29
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
Piped water supply withreservoir
Piped water supply withoutreservoir
Hand pump connected tosupply line
Co
mb
ined
Vu
lner
abilt
iy S
core
Urban Water Supply Options
Diarrhoea Typhoid Eye Infections
115
evident that for „Piped water supply with reservoir‟, time to fetch water, demand,
boiling practices, sanitary practices and water quality etc. are major concerns as per
Figure 5.50: State of vulnerability of urban water supply options based on
diarrhoea incidences
as diarrhoea is concerned. On the other hand for „Piped water supply without
reservoir‟, demand, storage practices, sanitary practices, water quality and SI risk
Figure 5.51: State of vulnerability of urban water supply options based on
typhoid incidences
are the major concerned. Again the community using „Hand pump connected to
supply line‟ system, distance and time to fetch water, boiling practices with certain
0
0.5
1
1.5
2
2.5
3
3.5
Vu
lne
rab
ility
Sco
re
Piped water supply with reservoir Piped water supply without reservoir
Hand pump connected to supply line
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Piped water supply with reservoir Piped water supply without reservoirHand pump connected to supply line
116
duration, hand wash practices , water quality and water point related SI risk etc. are
the major concerned. Figure 5.52 clearly indicating the case of eye infections for
Figure 5.52: State of vulnerability of urban water supply options based on eye
infections incidences.
those who are using “Piped water supply with reservoir‟. Poor maintenance of the
reservoir could be another cause of such results. Now, if all the vulnerability were
summed up then results can be shown in Figure 5.53.
Figure 5.53: The order of urban water supply system options based on
cumulative vulnerability scores
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
Piped water supply withreservoir
Piped water supply withoutreservoir
Hand pump connected tosupply line
Cu
mu
lati
ve V
uln
erab
ility
Sco
res
Diarrhoea Typhoid Eye Infections
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Piped water supply with reservoir Piped water supply without reservoirHand pump connected to supply line
117
5.4 Evaluation on Estimated Health Impact Valuation of Waterborne
Diseases
From Table 4.43 it is seen that out of forty HHs, thirty three HHs (83%) had suffered
from diarrhoea. Each non-reported diarrhoea incidence remains on average for 5.03
days with standard deviation of 2.02 days. The direct, indirect and total costs were
Tk. 759.4, Tk. 762.48 and Tk. 1521.88 respectively. During survey, it was found that
minimum and maximum numbers of days suffered by the population were 3 days
and 10 days respectively. On the other hand, Table 4.44 shows that out of forty
HHs, only seven HHs (18%) had suffered from typhoid. Each incidence remains on
average for 17.4 days with standard deviation of 7.2 days. The direct, indirect and
total costs were about Tk. 3621.43, Tk. 1361.25 and Tk. 4982.68 respectively. In
case of Typhoid, it was found that minimum and maximum numbers of days
suffered by the population were 7 days and 30 days respectively. It was observed
that the home treatment and medical expenditure of typhoid incidence were the
most expensive and higher than both diarrhoea and eye infections.
Table 4.45 shows that out of forty HHs, twenty three HHs (58%) had suffered from
eye infections. Each incidence remains on average for 6.3 days with standard
deviation of 1.5 days. The direct, indirect and total costs were Tk. 205, Tk. 711.58
and Tk. 916.58 respectively. The indirect cost is about 2.5 times more than that of
direct cost and it is because the individual remain absent from his work place due to
contagious nature of the disease. During survey, it was found that minimum and
maximum numbers of days suffered by the population were 3 days and 10 days
respectively.
Hence the total cost of diseases for last one year found from Table K.1 of Appendix
K for the selected areas are 149,892,036.19 Tk. (using incidence rate against
exposure) and 87,138,383.05 Tk. (using prevalence rate of community type). This
difference has come from very high incidence rate at smaller HHs size.
According to LGED (2005) report, the estimated total cost of non-reporting
waterborne diseases of slum areas of entire Dhaka city was 1,756,718,564 Tk. or
26,188,410 USD (exchange rate 1$ = 67.08 Tk. for 2005-06). But now, according to
BBS (2011) census and media report those amount is expected to be more than
5,653,819,097 Tk. or 81,726,208 USD (exchange rate 1$ = 69.18 Tk. for 2009-
10). Figure 5.54 shows the comparison between the cost of non-reporting selected
118
waterborne diseases and revised Gross Domestic Product (GDP) at current price
and GDP at constant price for the year 2009-10 (BBS 2010).
Figure 5.54: Comparison between the cost of non-reporting waterborne
diseases, GDP at current price and GDP at constant price (2009-10).
5.5 Evaluation of Prevalence Rate
It has already been discussed in Section 3.3.5 about the different use of formulas.
From Appendix L, following results can be shown in Figure 5.55:
Figure 5.55: Prevalence rate of waterborne diseases.
Above figure shows that vulnerable people are more susceptible to the diarrhoea
than those of eye infections and typhoid. This could be because of diarrhoea takes
6,923,795 3,600,465
5,653
1
10
100
1,000
10,000
100,000
1,000,000
10,000,000
GDP in current price(2009-10)
GDP in constant price(2009-10)
Estimated SelectedDisease Cost
Mill
ion
Tak
a
480.95
47.62
309.52
0
100
200
300
400
500
600
Diarrhoea Typhoid Eye Infections
Pre
vale
nce R
ate
(in
1000)
Waterborne Diseases
119
place not only as a result of water usage but also due to contaminated food intake.
On the other hand Figure 5.56 shows the state of PR values of different genders:
Figure 5.56: The state of PR values of different genders
It shows that males are more vulnerable to diarrhoea and eye infections than those
of female. It is because of rate of involvement by male with outside environment is
more than that of female counter part. If the data is further analyzed according to
age-groups than it can be seen in Figure 5.57 that the PR values of female children
under five are much higher than those of male children. It gives us an insight that
female children are more neglected due to gender issue at this level. On the other
Figure 5.57: The State of PR values of different age-groups of different
genders suffering from diarrhoea.
214.29
28.57
119.05
266.67
19.05
190.48
1
10
100
1000
Diarrhoea Typhoid Eye Infections
PR
TP
Female(F) Male(M)
625.00 294.12
450.00 692.31 433.33 464.79
104.17
43.86
93.75 157.89
270.83 289.47
47.62 23.81
42.86
85.71 123.81 157.14
1
10
100
1000
F M F M F M
<5 5-14 >15
Pre
vale
nce
Rat
e
Age-Group
PRIG PRGT PRTP
120
hand, for children between 5-14 years, male children suffer more than female. This
is because at this stage male children of vulnerable community start involving
themselves in various unhygienic activities like scavenging in order to help their
respective family. However the PR for elderly male people (15 years) is little more
than female thus signifies about their same state of vulnerability in their job. Figure
5.58 shows the different age-groups suffering typhoid. Here the female prevalence
Figure 5.58: The State of PR values of different age-groups of different
genders suffering from typhoid
rates against total population (PRTP) below 5 years and above 15 years were more
than those of males. On the other hand, Figure 5.59 shows the different age-groups
suffering eye infections. Here male prevalence rates were more than female.
Figure 5.59: The State of PR values of different age-groups of different
genders suffering from eye infections
125.00
58.82 50.00 38.46 50.00 28.17
20.83
8.77 10.42 8.77
31.25 17.54
9.52 4.76 4.76 4.76
14.29 9.52
1
10
100
1000
F M F M F M
<5 5-14 >15
Pre
va
len
ce
Ra
te
Age-Group
PRIG PRGT PRTP
187.50
411.76 400.00 346.15 233.33
338.03
31.25 61.40
83.33 78.95 145.83
210.53
14.29
33.33 38.10 42.86 66.67
114.29
1
10
100
1000
F M F M F M
<5 5-14 >15
Pre
va
len
ce R
ate
Age-Group PRIG PRGT PRTP
121
Table L.4 to Table L.6 show the different PR values for community, selected areas
and urban water supply options respectively. Very high PR values for slum, Gulshan
area and “Hand pump connected to supply line” are found.
5.6 Correlation Between Diarrhoea Patient Reproting Cases and Climatic
Factors
Basing on the Equation 4.1 and 4.2 as developed in the Section 4.5.2, projected
data of diarrhoeal patients for both selected areas and Dhaka have been given in
the Table M.5 of Appendix M and presented in the Figure 5.60 and Figure 5.61.
Figure 5.60: Projected average diarrhoeal patients of study areas based on temperature
Figure 5.61: Projected average diarrhoeal patients of Dhaka based on temperature
0
100
200
300
400
500
600
700
800
900
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40Av
era
ge N
um
ber
of
Pati
en
ts
Temperature (°C)
Average Nos. Lower bound Higher bound
0
500
1000
1500
2000
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
Av
era
ge
Nu
mb
er
of
Pati
en
ts
Temperature (°C)
Average Nos. Lower bound Higher bound
122
Figure 5.62 shows that during surge periods the record of average “monthly average
maximum temperature” of 21 years (1990-2010) and 11 years (2000-2010) both
were same i.e. 33.8°C (in April) and 32.0°C (in September). It was found that during
2000-2010, the average patients reported in those two months were within the
bound drawn. It was again observed from 21 years‟ (1990-2010) records that the
monthly average maximum temperature raised up to 36.4 °C in April of 1995 and up
to 33.8 °C in September of 1996 respectively.
Figure 5.62: Average maximum temperature profile at different time range
Hence using the correlation formula, the results of likely diarrhoeal incidences and
actually reported have been given in the Table 5.1. Since there were no monthly
Table 5.1: Number of likely and actual diarrhoeal Incidences with respect
to temperature
Temperature (°C)
Selected Areas Dhaka
Number of Likely Diarrhoeal Incidences
Actual Avg.
Reported (2000-2010)
Number of Likely Diarrhoeal Incidences
Actual Avg.
Reported (2000-2010)
Average Nos.
Lower bound
Higher bound
Average Nos.
Lower bound
Higher bound
32.0 919 736 1102 763 485 394 576 400
33.8 1050 867 1233 975 537 446 628 550
36.4 1271 1088 1454 - 621 530 712 -
data available before 2000, hence actual average reported cases have been kept
blank.
26.9
31.2
34.8
36.4 35.1
34.5 32.8
32.7
33.8
33.1
30.7
28.0
24.0
26.0
28.0
30.0
32.0
34.0
36.0
38.0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Tem
pera
ture
(°C
)
Month
Max Avg. (1990-2010)
Max Avg. (2000-2010)
Max Temperature Recorded (1990-2010)
123
5.7 GIS Representation of Relevant Data In Thematic Maps
Thematic maps based on different themes provide quick planning tools for decision
makers and planners. In this thesis paper, the relevant data has been collected from
Appendix G through Appendix J and processed those data using GIS software like
ArcGIS Catalogue and ArcGIS Map and finally representing them in different
thematic maps in Appendix O.
In Figure O.1 of Appendix O, the distribution of DTWs and water bodies around the
selected areas of Dhaka city have been shown which otherwise will allow to identify
the available water sources and their relative impacts on neighborhood habitats.
Figure O.2 has shown the distribution of 27 water sample points from where water
were collected and tested and Figure O.3 has shown the FC concentration at the
respective sources thus pin pointing the most vulnerable source in the selected
areas. Again the sample point wise incidences‟ state of waterborne diseases have
been shown in Figure O.4 to Figure O.6 and the vulnerability state of the
communities at different selected areas have been shown in Figure O.7 through
Figure O.9 of Appendix O.
124
CHAPTER 6
CONCLUSIONS AND RECOMMENDATIONS
6.1 Conclusions
Due to Rapid urbanization and unplanned population growth of Dhaka city, the
facilities of an ideal metropolitan city are declining every day; environmental
degradation notably water pollution is taking place too fast to cope with. The
evidence from the literature consistently points to use of water as being important to
controlling disease and the fact that lack of access to water may impede its use and
thereby adversely affect health. But at present the only public water providing
organization - DWASA is facing various challenges both for quantity and quality of
water. Moreover it could hardly provide adequate and wholesome water to the
vulnerable communities who are human capital greatly contributing to the economy
and work force of Dhaka city.
The main objective of this thesis was to find out the health impacts of urban water
supply on the vulnerable communities of selected areas of Dhaka city. Major
conclusions from this study are summarized below:
The vulnerable community composed of people (73%) mainly from other districts
coming for economic reason.
There is a bimodal distribution of the patients of waterborne diseases for Dhaka city
with maximum number of patients reported immediate before and during the wet
season.
It was found that about 58%, 23% and 56% of HH members were affected by
diarrhoea, typhoid and eye infections respectively for last one year. According to
gender, it was seen that male were more vulnerable to the waterborne diseases
than those of female. It was also seen that female children <5 years (10%) suffer
from diarrhoea just double than male percentage (5%). Gender difference in the
family could be one of the main reasons.
125
It was seen that maximum number of HHs (65%) of vulnerable communities had
their supplied water of DWASA through private connections and the rest 35% had
their supplied water of DWASA through public connections. A high percentage of
diarrhoeal (74%), typhoid (60%) and eye infections (77%) incidences in case of
private connections were reported. This was because of the most of the private
connections (mostly for slum community) were made with sub-standard materials
and connecting pipes were leaky and drawn over the waste and wet lands.
Majority of vulnerable communities‟ HHs (47%) were having “Hand pump connected
to supply line”, 38% of HHs were having “Piped water supply without reservoir” and
rest 15% HHs were having “Piped water supply with reservoir”. So it was about 85%
(47%+38%) of the total HHs those were to rely on unsecured water availability.
Maximum slum community (61%) had hand pump connected to supply line with
private connection using sub-standard material. On the other hand maximum low-
income community (53%) had piped water supply without reservoir. It was found
that 53% of the total diarrhoeal incidences, 60% of the total typhoid incidences and
51% of the total eye infections incidences were alone from “Hand pump connected
to supply line” urban water supply option. But when percentage of exposure was
taken in consideration then it was seen that 91% of eye infections and 65% of
diarrhoeal incidences had come from “Piped water supply with reservoir”. Low level
maintenance of the reservoir could be one of the main reasons of such result.
Maximum percentage (77%) of the surveyed HHs were residing very close (<50 m)
to the sources thus taking very less time (around 5 minutes) to fetch water. On the
other hand, basing on the urban water supply options, 79% hand pumps connected
to supply line were located closer to <50m distance. The slum community (35%)
was to travel maximum distance to fetch water than that of low-income (6%).
Community residing at Gulshan, Tejgaon and Mirpur were to travel more. As per
exposure, for the longer the distance and time for collecting water, the more the
possibilities to be affected by the waterborne diseases. This could be conservative
use of water due to longer distance of water source from the HHs.
Overall 95% of HHs never had their demand fulfilled out of which only 55% could
mitigate their daily need by just half of their demand. Only 5% showed their
fulfillment of their demand as per as water availability are concerned. Slum people
126
had never their demand fulfilled rather maximum of them (74%) had 50% of their
demand fulfilled. On the other hand low-income community had better accessibility
of water (only 29% HHs had 50% demand of water fulfilled). Maximum HHs (55%)
having hand pump connected to supply line received only 50% of their demand of
water. Gulshan area (31%) faced maximum water scarcity, followed by Tejgaon and
Mirpur. However a negative correlation found between the quantities (demand) of
water with the number of diarrhoea incidences. Less accessibility to water might
force users to use contaminated water.
Overall 68% of HHs did not boil water for drinking purpose. However there was 76%
of low-income HHs who boiled water for drinking purpose but nil for slum. There
were about 31% of low-income HHs who boiled water for 5-15 minutes and rest
69% of HHs who boiled water for 15-30 minutes. No HHs were found boiling water
more than 30 minutes. 90% of HHs residing at Gulshan area, 80% of HHs at
Tejgaon, 50% of HHs at Badda and 40% of HHs at Mirpur did not boil water. Even
after boiling, poor hygiene practices in regard to storing, maintaining and even
associated with other factors like taking outside food from unhygienic places etc.
might be involved for high percentages of incidences.
This study identified mainly 4 types of storage container like drum, kolosh, patil and
water bottle. It was shown 55% of HHs alone accounted for kolosh type storage
system. The low-income community (82%) stored their water mostly in kolosh but
slum community stored their water equally in drum (35%), kolosh (35%) and water
bottle(30%). As per as storage of water was concerned, patil was not a good choice
for storing water since it produced the highest (80%) diarrhoeal incidences against
exposure. It was because it remained open and method of using water to and from it
was not hygienic.
Overall 45% of the population depended on community based pit latrine sanitation
system followed by septic tank system (32%). On the other hand, about 13% of
surveyed population went for unsanitary system and very small portion (5%) were
using sanitary sewer and hanging latrine system. The slum community had more pit
latrine system (64%) where low-income community based on septic tank system
(67%). 92% of HHs at Gulshan, 30% of HHs at Tejgaon and 40% at Mirpur used pit
latrine system. There were about 25% HHs of Badda found defecating in the field
127
(unsanitary system). High percentages of diarrhoeal and eye infections incidences
even after using sanitary options indicated low level personal hygiene and lack of
awareness about the consequences.
A large number (48%) of people of vulnerable community used nothing after
defecation which showed the lack of hygiene education among the community
members. It showed that 83% of slum HHs did not use any media to wash their
hands, on the contrary 100% low-income HHs were found very much aware about
use of media (in this case soap). It was found that 83% of HHs residing at Gulshan
and 50% at Badda did not use any medium to wash their hands in order to maintain
good health. Moreover a good number of people being affected by diarrhoea (55%)
and eye infections (41%), though they used the medium like soap. This could be the
result of improper rubbing of hands with medium used and/or effect of other
associated factors.
Overall state of aesthetic quality of water showed that 44% of the HHs were
experiencing occasional odorous water and 33% of the HHs were experiencing
water mixed with dirt/foreign materials. Communities at Tejgaon (70%) and Badda
(75%) complained their water to be odorous but the communities at Gulshan (50%)
and Mirpur (40%) were experiencing water mixed with foreign materials.
The physical parameters like turbidity was found within the Bangladesh Standard.
The pH values of samples were nearly satisfying the Bangladesh Standard of 6.5 to
8.5.
There were about 46% of samples those have chlorine values less than 0.05mg/l
and there were 58% of samples those have chlorine value less than the Bangladesh
Standard i.e. 0.2 mg /l.
Overall 89% samples were containing varying degree FC concentration and
maximum (67%) shown in the range of 100-300 cfu/100ml. A high level
concentration of FC found in “Piped water supply without reservoir” and followed by
“Hand pump connected to supply line”. A linear correlation (r2 = 0.7419) was found
between FC count and diarrhoea incidences in percentage against exposure.
Percentage of incidences for slum was high at higher level of FC concentration
128
(>200 cfu/100ml) whereas low-income community was found at lower concentration
(<200 cfu/100ml). Faecal coliform concentration was relatively more than that of
low-income community because the water carrying pipes by latter did not pass over
the wasteland and again the back ground level of immunity could be another reason
of this kind of result. Percentage of incidences for Gulshan and Mirpur were high at
higher level of FC concentration (>200 cfu/100ml) whereas Tejgaon and Badda
were high at lower concentration (<200 cfu/100ml). Percentage of incidences for
“Piped water supply with reservoir” was high at higher level of FC concentration
(>200 cfu/100ml) whereas “Piped water supply without reservoir” and “Hand pump
connected to supply line” were found high at lower concentration (<200 cfu/100ml).
During sanitary inspection it was found 7% very high, 45% high, 37% medium and
11% low risk grade associated with the water points. Based on SI Risk Grading, it
was clearly evident that slum water points were more vulnerable (SI risk score=7)
and susceptible to source related contamination than low-income community (SI risk
score=5.7). A linear correlation (r2= 0.9897) has been found between SI risk grade
and eye infections incidences against exposure in percentage. Again it was Gulshan
area (SI risk score=7.50 ) which is the most vulnerable area followed by Mirpur (SI
risk score=6.30), Tejgaon (SI risk score=6.10)and Badda(SI risk score=5.80)
respectively. As per as urban water supply options were concerned, the order
showed here are hand pumps connected to supply line(SI risk score=6.71), Piped
water supply without reservoir (SI risk score=6.65), Piped water supply with
reservoir(SI risk score=4.78).
Overall vulnerability of communities indicate that slum (Cumulative score =13.95)
had higher combined vulnerability scores for diarrhoea (CVSdiarrhoea = 5.86) and eye
infections (CVSeye infections = 6.67) than those of low-income community (Cumulative
score =11.59 ; CVSdiarrhoea = 5.58 and CVSeye infections = 4.34). However low-income
community had higher typhoid (CVStyphoid = 1.67) score than those of slum
community (CVStyphoid = 1.42).
Overall vulnerability of selected areas indicate that Gulshan area (Cumulative score
=16.42; CVSdiarrhoea = 6.55, CVStyphoid = 0.94 and CVSeye infections = 8.93) is the most
vulnerable area, followed by Tejgaon (Cumulative score =13.07; CVSdiarrhoea = 7.01,
129
CVStyphoid = 0.68 and CVSeye infections = 5.38), Mirpur (Cumulative score =9.43;
CVSdiarrhoea = 5.57, CVStyphoid = 1.67 and CVSeye infections = 2.19), and Badda
(Cumulative score =6.95; CVSdiarrhoea = 3.64, CVStyphoid = 0.80 and CVSeye infections =
2.51).
Overall vulnerability of urban water supply options indicate that high vulnerability
score against diarrhoea (CVSdiarrhoea = 6.45) for „Hand pump connected to supply
line‟, against typhoid (CVStyphoid = 2.00) for „Piped water supply without reservoir‟
and against eye infections (CVSeye infections = 7.04) for „Piped water supply with
reservoir‟. However overall „Piped water supply with reservoir‟ was the most
vulnerable option (cumulative score =13.09) followed by „Hand pump connected to
supply line‟ (cumulative score =13.03) and „Piped water supply without reservoir‟
(cumulative score =12.69).
Each non-reported diarrhoea incidence remains on average for 5.03 days with
standard deviation of 2.02 days. The direct, indirect and total costs were Tk. 759.39,
Tk. 762.48 and Tk. 1521.88 respectively. Again each typhoid incidence remains on
average for 17.4 days with standard deviation of 7.2 days. The direct, indirect and
total costs were about Tk. 3621.43, Tk. 1361.25 and Tk. 4982.68 respectively.
Finally eye infections‟ incidence remains on average for 6.3 days with standard
deviation of 1.5 days. The direct, indirect and total costs were Tk. 205, Tk. 711.58
and Tk. 916.58 respectively. The indirect cost is about 2.5 times more than that of
direct cost and it is because the individual remain absent from his work place due to
contagious nature of the disease. The total cost of diseases for selected areas is
from 87,138,383.05 Tk. to 149,892,036.19 Tk. and for slum areas of whole Dhaka
city is 5,653,819,097.66 Tk. or 81,726,208.41 USD.
There is an exponential correlation (CrSA= 0.866; CrDC=0.799) exist between number
of diarrhoea incidences of reporting cases with temperature of Dhaka city.
The thesis has pointed out that vulnerable people are more susceptible to the
diarrhoea (PRdiarrhoea = 480.95) than those of eye infections (PReye infections = 309.52)
and typhoid (PRtyphoid = 47.62). This could be - because of diarrhoea takes place not
only as a result of water usage but also due to contaminated food intake. Again it
was the males who were more vulnerable to diarrhoea (PRdiarrhoea = 266.67) and eye
130
infections (PReye infections = 190.48) than those of female. It is because the rate of
involvement by male with outside environment is more than that of female counter
part. The PR values of female children (PRdiarrhoea = 47.62 and PRtyphoid = 9.52) under
five are much higher than those of male children (PRdiarrhoea = 23.81 and PRtyphoid =
4.72). It gives us an insight that female children are more neglected due to gender
issue at this level. Moreover very high value of PR found for slum (PRdiarrhoea =
290.48, PRtyphoid = 38.10, PReye infections = 200.00) than low-income (PRdiarrhoea = 190.48,
PRtyphoid = 9.52, PReye infections = 109.52) community; for Gulshan area (PRdiarrhoea =
142.86, PRtyphoid = 14.29, PReye infections = 171.43) than other areas and “Hand pump
connect to supply line” (PRdiarrhoea = 257.14, PRtyphoid = 28.57, PReye infections = 157.14)
than other supply options.
6.2 Recommendations
In this study, due to high authenticity and rich data availability, the selection of areas
of Dhaka city was done based on the data of ICDDR,B only. However data from
other sources like DSH, Dhaka Medical College etc. could be synthesized in order
to find out exact state of Dhaka city.
Primary data collection time was from July 2010 to October 2010 (2nd peak) basing
on the bimodal distribution curve as developed using secondary data of ICDDR,B.
Data collected round the year would augment the analysis in future.
A suitable water safety plan could be developed according to geographical locations
and implemented on the communities and urban water supply systems based on the
findings of 12 factors used.
A comprehensive study can be made in future to check the correctness of the
correlation found between the demands of water with the number of non-reporting
diarrhoea incidences and between SI risk grades with eye infections incidences.
In future, a feasibility study can be undertaken to develop a forecasting tool using
correlation equation found between diarrhoea incidences of reporting cases with
temperature of Dhaka city.
131
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134
WELL, (1998), Guidance manual on water supply and sanitation programmes, Water Engineering and Development Centre (WEDC), Loughborough, UK White, G. F., Bradley, D.J. and White, A. U. (1972), Drawers of water: domestic water use in East Africa, University of Chicago Press, Chicago. WHO (2000), Health systems: improving performance, World Health Report, 2000, World Health Organization, Geneva, Switzerland. WHO (2004), Water, sanitation and hygiene links to health. Facts and figures. World Health Organization (WHO), Geneva. (http://www.who.int/water_sanitation_health/publications/facts2004/en/index.html.) WHO (2008), Guidelines for Drinking Water Quality- Incorporating the first and second addenda, Volume 1, Recommendations, World Health Organization, Geneva, Third Edition. WHO/UNICEF (2000), Global Water Supply and Sanitation Assessment 2000 Report, World Health Organization and United Nations Children's Fund. ISBN 92 4 1562021, pp 47.
135
Appendix A: QUESTIONNAIRES SURVEY FORM
Household Information Date:
Name: Sex: F M
Age: -----------Yrs. -------------months Occupation:
Address:
House No: Street: Ward (DCC) No:
Thana/Zone:
1. Are you from Dhaka City?
Yes No
2. If no, from where and when (please mention year) did you come to Dhaka? 3. What is the source of your water?
Supplied water through private connection.
Supplied water through public connection/Tape water.
Pond/lake/river water.
Well
4. What is the distance of water point from your house?
<50 metre
<100 (50-100) metre
<250 (100-250) metre
<500 (250-500) metre
>500 metre
5. How much time do you take to collect water from the source? 6. How much water do you receive everyday?
Full/As per demand 75% of Demand 50% of Demand 25% of Demand
Other ( _____% of Demand)
7. What is the general condition of supplied water?
Clean and fresh Odorous Turbid
136
Contains dirts and other foreign matterials
Other (mention):
8. Do you boil your drinking water?
Yes Partial No
9. How much time you boil your drinking water?
5-15 minutes 15-30 minutes > 30 minutes
10. Where do you store your drinking water? 11. What is the cost of your container to store the water? 12. Do you use lid to cover your container? If so what is the price of the lid? 13. What do you use to boil water?
Gas (Sufficient supply/ At par/ Not sufficient)
Electricity (Sufficient supply/ At par/ Not sufficient)
Tree wood/leaves (Sufficient supply/ At par/ Not sufficient)
Other (mention)(Sufficient supply/ At par/ Not sufficient):
14. How much hours you get electricity round the day?
3-4 hrs
11-15 hrs
5-10 hrs
>15 hrs
15. What do you use to wash your hands after defecation and before having main
meals?
Soap Soil Ash Nothing
16. How many family members do you have?
Member’s Age range Sex Number
< 5 Years F
M
5-14 years F
M
> 15 years F
M
Total:
17. What type of Sanitation System you use?
Sanitary sewer Septic tank system Pit
latrine
Unsanitar
yHanging latrine
137
18. How many members of your family suffered from following diseases last one yr:
Member’s Age
range Sex Dysentery
Diarrhoea /Cholera
Typhoid
Other waterborne diseases(skin rash, eye rash, stomach ache
etc.)
< 5 Years F
M
5-14 years F
M
> 15 years F
M
19. What is the general incidence rate of following diseases?
Dysentery Diarrhoea /Cholera
Typhoid
Other waterborne diseases
Every day / week / month/ year
Every day / week / month/ year
Every day / week / month/ year
Every day / week / month/ year
20. Did anybody die due to the above diseases last five years (mention the year)? 21. How many family members were hospitalized during last one yr?
Member’s Age range
Sex
Number of Family Members Hospitalized
Dysentery Diarrhoea /Cholera
Typhoid Other
waterborne diseases
< 5 Years
F
M
5-14 years
F
M
> 15 years
F
M
22. Where do you hospitalize (name the hospital/clinic/health complex etc) your family members during aforesaid diseases.
ICDDR,B DSH PG/BSMMU DMC Other (mention):
138
23. How much money (average) you are to expend for each time?
Home treatment:_________________Tk. (These are for extra fooding and/or
nursing)
Transportation Cost:_______________________Tk. (For
doctor/clinic/hospital/purchasing medicine at a long distance etc.)
Doctor's Fees:____________________Tk. ( Single doctor visit
charge:___________Tk)
Medical Expenses:____________________Tk. (These are expended after
visiting doctor)
Hospitalization Expenses:____________________Tk.(if any)
24. How many days (average no of days) required recovering from each case?
Dysentery Diarrhoea /Cholera
Typhoid
Other waterborne diseases
25. How much parents’ work-time are lost (i.e. if both/either of them is sick)? 26. How much parents’ work-time are lost in each case (i.e. parents are away from
work place due to look after of family members)? 27. How much parents’ leisure-time are lost in each case (i.e. parents could not take
rest for the diseases)? 28. How much money does your family earn per month altogether?
<3,000 Tk. 3,000-6,000 Tk. 6,000-10,000 Tk. >10,000 Tk.
139
Appendix B: SANITARY INSPECTION FORMS
(Piped water supply with reservoir)
Date of Survey:
Water Supply Option:
Community Type:
Ward No:
Water Point No: Water samples taken? …….. Sample Nos. ………
Lat: Long:
RISK QUESTIONS
Ser Risk Questions Risk
1. Is there any hanging/pit latrine within 10m of the water supply option?
Y/N
2. Is there any other source of faecal pollution 10m of the water supply option?
Y/N
3. Is there any visible leak in the water supply system from street main to underground reservoir near the collection point?
Y/N
4. Is there any visible leak in the water supply system from UGR to OHR?
Y/N
5. Is the tape loose /missing/faulty at the connection point? Y/N
6. Is there any visible crack on the underground reservoir? Y/N
7. Is there drainage system near the water points faulty inundating the area?
Y/N
8. Is there any way to contaminate the UGR from septic tank? Y/N
9. Is there any collection of water on the UGR from faulty drainage?
Y/N
10. Is there any visible sign of dirt, insects in the UGR/OHR? Y/N
Total Score of Risks ..../10
Comments:
140
SANITARY INSPECTION FORMS (Piped water supply without reservoir)
Date of Survey:
Water Supply Option:
Community Type:
Ward No:
Water Point No: Water samples taken? …….. Sample Nos. ………
Lat: Long:
RISK QUESTIONS
Ser Risk Questions Risk
1. Is there any hanging/pit latrine within 10m of the water supply option?
Y/N
2. Is there any other source of faecal pollution 10m of the water supply option?
Y/N
3. Is there any visible leak in the water supply system from street main to underground reservoir near the collection point?
Y/N
4. If water is collected by flexible rubber, PVC pipes does it go over dirty areas (waste dump, wasteland etc)?
Y/N
5. Is the tape loose /missing/faulty at the connection point? Y/N
6. Is there drainage system near the water points faulty inundating the area?
Y/N
7. Is the platform slope not properly designed facilitating poor drainage?
Y/N
8. Are the water collecting containers seen dirty? Y/N
9. Does the community lack hygiene practices? Y/N
10. Do the people reserve water temporarily in containers like drums?
Y/N
Total Score of Risks ..../10
Comments:
141
SANITARY INSPECTION FORMS (Hand pump connected to supply line/STW)
Date of Survey:
Water Supply Option:
Community Type:
Ward No:
Water Point No: Water samples taken? …….. Sample Nos. ………
Lat: Long:
RISK QUESTIONS
Ser Risk Questions Risk
1. Is there any hanging/pit latrine within 10m of the water supply option?
Y/N
2. Is there any other source of faecal pollution 10m of the water supply option?
Y/N
3. Are there cracks in the platform supporting infiltration of dirty water?
Y/N
4. Is the platform slope not properly designed facilitating poor drainage?
Y/N
5. Is the handpump loose /missing/faulty at the connection point? Y/N
6. Is there drainage system near the water points faulty inundating the area?
Y/N
7. Does the pump water go down and the community use dirty water for priming?
Y/N
8. Are the water collecting containers seen dirty? Y/N
9. Does the community lack hygiene practices? Y/N
10. Do the people reserve water temporarily in containers like drums?
Y/N
Total Score
Comments:
142
Appendix C: 15 YEARS (1996-2010) AVERAGED DIARROHEAL PATIENTS REPORTED
Table C.1: Average Number of Diarrhoeal Patients Reported to ICDDR,B (1996-2010)
Serial DMPA Thana Count Original Numbers
<5 Yrs 5-14 Yrs 15+ Yrs Total <5 Yrs 5-14 Yrs 15+ Yrs Total
1 Kotawali 23 5 28 56 1150 250 1400 2800
2 Sutrapur 34 7 29 70 1700 350 1450 3500
3 Motijheel 60 9 40 109 3000 450 2000 5450
4 Ramna 24 3 22 49 1200 150 1100 2450
5 Lalbag 51 10 48 109 2550 500 2400 5450
6 Shyampur 30 6 27 63 1500 300 1350 3150
7 Demra 102 17 62 181 5100 850 3100 9050
8 Shabujbag 37 5 24 66 1850 250 1200 3300
9 Dhanmondi 16 2 15 33 800 100 750 1650
10 Hazaribag 13 3 10 26 650 150 500 1300
11 Kamrangirchar 16 3 12 31 800 150 600 1550
12 Khilgaon 42 8 33 83 2100 400 1650 4150
13 Tejgaon 50 7 45 102 2500 350 2250 5100
14 Mohammadpur 46 10 43 99 2300 500 2150 4950
15 Badda 73 10 57 140 3650 500 2850 7000
16 Gulshan 83 13 62 158 4150 650 3100 7900
17 Kafrul 21 4 22 47 1050 200 1100 2350
18 Mirpur 99 18 102 219 4950 900 5100 10950
19 Uttara 35 6 30 71 1750 300 1500 3550
20 Cantonment 18 3 13 34 900 150 650 1700
21 Pallabi 10 3 15 28 500 150 750 1400
Source: ICDDR,B (2010) Notes:
1 x Count = 50 X patients reporting. So, 0 in any year does not necessarily mean “No(Nil)” patients reporting that year.
Upto 59 months = “<5 Yrs”, 60 to 179 months = “ 5-14 Yrs” and from 180 months = “15+ Yrs” have been considered.
Report based on earlier 21 thanas; No data on new divisions of thanas were maintained by ICDDR,B during the study time.
143
Appendix D: 11 YEARS MONTHLY AVERAGE (2000-2010) DIARRHOEAL PATIENTS REPORTED Table D.1: 11 Years’ Monthly Average (2000-2010) Diarrhoeal Patients Reported to ICDDR,B
Year Ser DMPA Thana Month Total
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
11 Y
ears
(20
00-2
010)
Avera
ge
1 Kotawali 150 200 200 400 300 150 200 250 250 350 200 150 2800
2 Sutrapur 150 200 300 450 350 300 300 250 300 300 200 200 3300
3 Motijheel 200 200 350 450 300 250 200 350 350 200 200 150 3200
4 Ramna 150 100 250 400 300 200 200 200 250 200 150 100 2500
5 Lalbag 250 250 450 550 450 250 400 450 400 300 350 200 4300
6 Shyampur 100 150 350 450 350 300 350 300 300 250 150 200 3250
7 Demra 500 450 800 1000 800 500 650 800 600 650 500 450 7700
8 Shabujbag 100 200 250 300 250 250 400 600 350 250 200 200 3350
9 Dhanmondi 100 100 150 250 150 200 150 150 100 150 100 100 1700
10 Hazaribag 100 50 100 200 150 100 200 100 150 150 100 50 1450
11 Kamrangirchar 100 100 200 150 200 150 100 150 100 150 150 150 1700
12 Khilgaon 250 250 450 450 350 300 350 650 500 300 250 250 4350
13 Tejgaon 250 300 600 650 400 350 450 550 500 450 400 250 5150
14 Mohammadpur 250 200 550 650 600 300 400 600 600 550 300 250 5250
15 Badda 300 350 600 800 700 450 550 1100 800 600 600 400 7250
16 Gulshan 450 450 550 800 600 450 500 650 600 550 500 400 6500
17 Kafrul 150 100 250 350 300 200 200 200 250 250 150 200 2600
18 Mirpur 450 500 850 1650 1150 950 850 1200 1150 900 650 500 10800
19 Uttara 250 200 300 400 400 350 300 300 300 400 250 350 3800
20 Cantonment 100 100 100 100 150 100 100 100 100 100 100 50 1200
21 Pallabi 50 100 150 150 200 150 150 200 100 100 150 100 1600
Average representative data of Dhaka City
250 250 400 550 450 300 350 450 400 350 300 250 4300
Average representative data of Selected Areas
363 400 650 975 713 550 588 875 763 625 538 388 7425
Source: ICDDR,B (2010)
144
Appendix E: THANAWISE ESTIMATED POPULATION OF DHAKA CITY FOR THE YEAR OF 2010 Table E.1: For the year of 2010
Serial Name Area
(Sq Km)
*BASE YEAR- 2001 Estimated Population
Pf=Pp(1+r)n Male Population
Female Population
Total Population (Pp)
1 Badda 49.85 198000 161000 359000 606523
2 Cantonment 14.36 70000 48000 118000 199359
3 Demra 31.1 238000 190000 428000 723097
4 Dhanmondi 6.23 147000 106000 253000 427439
5 Gulshan 10.29 107000 83000 190000 321002
6 Hazaribag 5.89 71000 57000 128000 216254
7 Kafrul 8.85 157000 133000 290000 489949
8 Kamrangirchar 3.68 76000 67000 143000 241596
9 Khilgaon 20.26 185000 152000 337000 569355
10 Kotawali 1.93 162000 92000 254000 429128
11 Lalbag 4.08 206000 140000 346000 584560
12 Mirpur 14.22 301000 250000 551000 930903
13 Mohammadpur 12.14 251000 205000 456000 770403
14 Motijheel 4.95 162000 108000 270000 456160
15 Pallabi 17.96 232000 200000 432000 729855
16 Ramna 7.71 149000 109000 258000 435886
17 Shabujbag 6.74 318000 131000 449000 758577
18 Shyampur 10.94 211000 165000 376000 635245
19 Sutrapur 3.99 206000 147000 353000 596387
20 Tejgaon 8.89 174000 128000 302000 510223
21 Uttara 58.85 188000 157000 345000 582871
*Source: BBS (2010)
145
Appendix F: DATA OF SELECTED CLIMATIC FACTORS FOR DHAKA STATION Table F.1: Average monthly data of climatic factors
Climatic Factors
Month
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Average Rainfall (mm ) (2000-2010)
6 17.2 61.6 120.9 258.4 379.1 415.4 307.2 357.4 193.0 26.5 5.5
Average Humidity ( % ) (2000-2010)
69.4 61.0 59.0 69.0 72.9 80.0 81.0 80.0 81.0 77.0 71.0 71.0
Average Temperature (0C) (1990-2010)
Max 24.7 28.2 32.2 33.8 33.3 32.5 31.7 32.0 32.0 31.6 29.5 26.4
Avg 18.5 22.0 26.2 28.5 28.8 29.0 28.7 29.0 28.6 27.4 24.0 20.1
Min 13.2 16.4 20.8 23.8 24.8 26.1 26.2 26.4 25.8 23.9 19.5 14.9
Average Temperature (0C ) (2000-2010)
Max 24.5 28.2 32.1 33.8 33.6 32.4 31.8 32.1 32.0 31.4 29.4 26.3
Avg 18.7 22.3 26.4 28.7 29.0 28.9 28.8 29.1 28.7 27.5 24.2 20.5
Min 13.6 16.9 21.1 24.1 24.8 26.0 26.1 26.3 25.7 24.0 19.6 15.7
Max. Temperature (0C) Recorded (1990-2010)
26.9 31.2 34.8 36.4 35.1 34.5 32.8 32.7 33.8 33.1 30.7 28.0
Source: BMD (2010)
146
Appendix G: RELEVANT DATA FROM QUESTIONNAIRES SURVEY
Table G.1: Relevant data of QSF
Seri
al o
f H
ou
seh
old
(H
H)
No
of
Fam
ily M
em
be
rs p
er
HH
No
of
pers
on
s i
n a
clu
ste
r
bein
g d
ire
ctl
y e
xp
osed
fo
r ea
ch
sam
ple
No
of
pers
on
s b
ein
g e
xp
osed
co
veri
ng
wh
ole
are
a f
or
sam
e
kin
d o
f w
ate
r
Th
an
a
Co
mm
un
ity t
yp
e
Ho
w m
uch
wate
r o
f d
em
an
d d
o
yo
u r
ec
eiv
e e
very
day?
Do
yo
u b
oil y
ou
r d
rin
kin
g
wate
r?
Wh
at
do
yo
u u
se t
o w
ash
yo
ur
han
ds a
fter
defe
cati
on
an
d
befo
re h
av
ing
main
meals
?
Wh
at
typ
e o
f S
an
itati
on
yo
u
use?
TO
TA
L A
ffecte
d b
y D
iarr
ho
ea
To
tal D
ire
ct
Co
st
for
Dia
rrh
oea
per
ep
iso
de
To
tal In
dir
ect
Co
st
of
Dia
rrh
oea
TO
TA
L A
ffecte
d b
y T
yp
ho
id
To
tal D
ire
ct
Co
st
for
Typ
ho
id
per
ep
iso
de
To
tal In
dir
ect
Co
st
of
Typ
ho
id
TO
TA
L A
ffecte
d b
y E
ye
Infe
cti
on
s
To
tal D
ire
ct
Co
st
for
Eye
Infe
cti
on
s p
er
ep
iso
de
To
tal In
dir
ect
Co
st
of
Ey
e
Infe
cti
on
s
1 6 100 100 Badda Slum. 50% N Nothing Unsanitary 2 700 385 1 7601 350 1 100 210
2 6 100 100 Badda Slum. 50% N Nothing Unsanitary 1 900 100 1 2852 175
3 7 35 2500 Badda Low income 75% Y Soap Septic tank 2 1850 150 2 300 250
4 3 40 2500 Badda Low income 50% Y Soap Sanitary sewer 1 1400 140 1 300 180
5 3 25 2500 Badda Low income 75% Y Soap Sanitary sewer 1 700 150 2 170 140
6 4 100 2000 Badda Slum. 50% N Nothing Septic tank 4 300 75 1 4706 300 1 265 30
7 5 100 2000 Badda Slum. 50% N Nothing Septic tank 1 450 125 1 175 50
8 8 100 1000 Badda Low income 50% Y Soap Septic tank 8 830 385 4 135 315
9 6 35 5500 Gulshan Slum. 75% N Nothing Pit latrine 6 850 455 6 200 385
10 3 35 5500 Gulshan Slum. 50% N Nothing Pit latrine 3 300 245
11 3 50 2000 Gulshan Slum. 75% N Nothing Unsanitary 1 650 240 3 125 250
12 6 60 2000 Gulshan Slum. 75% N Soap Pit latrine 6 200 315
13 5 10 1500 Gulshan Low income 50% Y Soap Pit latrine 2 850 120
14 4 80 500 Gulshan Slum. 50% N Nothing Pit latrine 1 1350 90
15 9 80 500 Gulshan Slum. 50% N Nothing Pit latrine 1 1800 245 2 1915 750
16 6 50 2000 Gulshan Slum. 75% N Nothing Pit latrine 6 350 220 6 200 75
17 2 50 2000 Gulshan Slum. 75% N Nothing Pit latrine 2 450 350
18 4 300 2500 Gulshan Slum. 50% N Nothing Pit latrine 4 230 90 4 100 50
19 3 300 2500 Gulshan Slum. 50% N Nothing Pit latrine 3 280 160 3 150 120
20 5 100 500 Gulshan Slum. 50% N Nothing Pit latrine 4 650 385 1 4120 210 5 270 210
147
Seri
al o
f H
ou
seh
old
(H
H)
No
of
Fam
ily M
em
be
rs p
er
HH
No
of
pers
on
s i
n a
clu
ste
r b
ein
g
dir
ectl
y e
xp
os
ed
fo
r e
ach
sam
ple
No
of
pers
on
s b
ein
g e
xp
osed
co
veri
ng
wh
ole
are
a f
or
sam
e
kin
d o
f w
ate
r
Th
an
a
Co
mm
un
ity t
yp
e
Ho
w m
uch
wate
r d
o y
ou
receiv
e
every
da
y?
Do
yo
u b
oil y
ou
r d
rin
kin
g
wate
r?
Wh
at
do
yo
u u
se t
o w
ash
yo
ur
han
ds a
fter
defe
cati
on
an
d
befo
re h
av
ing
main
meals
?
Wh
at
typ
e o
f S
an
itati
on
yo
u
use?
TO
TA
L A
ffecte
d b
y D
iarr
ho
ea
To
tal D
ire
ct
Co
st
for
Dia
rrh
oea
per
ep
iso
de
To
tal In
dir
ect
Co
st
of
Dia
rrh
oea
TO
TA
L A
ffecte
d b
y T
yp
ho
id
To
tal D
ire
ct
Co
st
for
Typ
ho
id
per
ep
iso
de
To
tal In
dir
ect
Co
st
of
Typ
ho
id
TO
TA
L A
ffecte
d b
y E
ye
Infe
cti
on
s
To
tal D
ire
ct
Co
st
for
Eye
Infe
cti
on
s p
er
ep
iso
de
To
tal In
dir
ect
Co
st
of
Ey
e
Infe
cti
on
s
21 6 16 2500 Mirpur Low income 100% Y Soap Pit latrine 2 2521 300
22 15 100 1000 Mirpur Low income 50% Y Soap Septic tank 8 450 60
23 5 50 5000 Mirpur Slum. 50% N Nothing Hanging latrine 1 400 420
24 10 10 1000 Mirpur Slum. 50% N Soap Pit latrine 4 650 75 1 50 175
25 3 60 1000 Mirpur Low income 75% Y Soap Septic tank 3 550 195
26 4 50 500 Mirpur Slum. 50% N Nothing Pit latrine 3 500 350 1 170 140
27 5 50 500 Mirpur Low income 50% Y Soap Pit latrine 4 450 120
28 6 30 2000 Mirpur Low income 75% Y Soap Septic tank 3 280 385
29 4 30 1000 Mirpur Low income 75% Y Soap Septic tank 1 850 105
30 6 50 1000 Mirpur Slum. 50% N Nothing Hanging latrine 6 450 120 1 225 100
31 5 20 500 Tejgaon Slum. 50% N Ash Pit latrine 3 800 240
32 6 20 500 Tejgaon Low income 75% N Soap Septic tank 2 200 70
33 8 25 250 Tejgaon Slum. 75% N Soap Pit latrine 2 1500 540 2 1733 450
34 5 20 250 Tejgaon Low income 100% N Soap Pit latrine 5 1300 420 3 200 210
35 6 35 400 Tejgaon Low income 75% Y Soap Septic tank
36 4 35 400 Tejgaon Low income 75% Y Soap Septic tank 4 1200 90 3 200 140
37 4 50 2500 Tejgaon Low income 75% N Soap Septic tank 1 700 125
38 3 50 2500 Tejgaon Low income 75% N Soap Septic tank 3 400 50
39 5 100 2500 Tejgaon Slum. 50% N Nothing Unsanitary 5 250 150
40 2 100 2500 Tejgaon Slum. 50% N Nothing Unsanitary 1 420 200
210 2651 67500 101 25060 7075 10 26170 2535 65 4715 4095
148
Appendix H: ANALYSIS OF SANITARY INSPECTION (SI) DATA Table H.1: Details of risk scores obtained during SI
Serial Thana
Ward
No
.
Place Name Community
Type Water Supply Option
Total Score of
Risks./10 Grade
1 Badda 2 Pasher Teck, Notun Bazar Slum Hand pump connected to supply line/STW 8 High
2 Badda 6 Shufi Sharoni Low-income Piped water supply without reservoir 6 High
3 Badda 8 Eid Gah Low-income Hand pump connected to supply line/STW 4 Medium
4 Badda 21 shha/60 Shadhinata Sharoni Low-income Hand pump connected to supply line/STW 5 Medium
5 Badda 5 CocaCola Tag Bari Slum Hand pump connected to supply line/STW 4 Medium
6 Badda 6 CocaCola Munshi Bari Low-income Hand pump connected to supply line/STW 6 High
7 Gulshan 20 IPS Bosti Slum Hand pump connected to supply line/STW 9 Very High
8 Gulshan 19 Beltola Bosti Slum Piped water supply without reservoir 8 High
9 Gulshan 19 Korail Bosti Low-income Piped water supply without reservoir 5 Medium
10 Gulshan 14 Gulshan Rd-18 Slum Piped water supply without reservoir 8 High
11 Gulshan 20 IPS Bosti Slum Hand pump connected to supply line/STW 8 High
12 Gulshan 20 T & T Bosti Slum Piped water supply with reservoir 4 Medium
13 Mirpur 12 Kalwalapara WGWSP WASA Ground Water Supply Pump 0 Low
14 Mirpur 12 Kalwalapara Slum Piped water supply without reservoir 4 Medium
15 Mirpur 12 Shalibag Low-income Piped water supply with reservoir 7 High
16 Mirpur 41 Agargaon Bosti Slum Piped water supply with reservoir 3 Medium
17 Mirpur 4 Purba Baishteki, Mirpur-13 Slum Hand pump connected to supply line/STW 8 High
18 Mirpur 7 Section 1 Low-income Piped water supply without reservoir 3 Medium
19 Mirpur 7 Section 1 Low-income Piped water supply without reservoir 6 High
20 Mirpur 7 Section 1 Slum Piped water supply without reservoir 9 Very High
21 Tejgaon 39 East Nakhal Para Slum Hand pump connected to supply line/STW 4 Medium
22 Tejgaon 37 Colony Bazar WGWSP WASA Ground Water Supply Pump 0 Low
23 Tejgaon 37 Lalmat Slum Hand pump connected to supply line/STW 7 High
24 Tejgaon 40 Panthapath WGWSP WASA Ground Water Supply Pump 0 Low
25 Tejgaon 50 South Panthapath Low-income Piped water supply without reservoir 8 High
26 Tejgaon 37 SOB Low-income Piped water supply with reservoir 4 Medium
27 Tejgaon 37 South Begunbari(Master Bari) Low-income Piped water supply without reservoir 6 High
149
Table H.2: Overall grading of vulnerable communities
Serial Community
Type
Total Score of Risks.
(Out of 10)
ix
Grade
Point
iy
Total Grade Point
ii yx
n
i
i
n
i
ii
y
yx
GPA
1
1 Grade
1
Slum
8 3 24
7 High
2 4 2 8
3 9 4 36
4 8 3 24
5 8 3 24
6 8 3 24
7 4 2 8
8 4 2 8
9 3 2 6
10 8 3 24
11 9 4 36
12 4 2 8
13 7 3 21
Total: 36 251
14
Low-income
6 3 18
5.7 Medium
15 4 2 8
16 5 2 10
17 6 3 18
18 5 2 10
19 7 3 21
20 3 2 6
21 6 3 18
22 8 3 24
23 4 2 8
24 6 3 18
Total: 28 159
150
Table H.3: Overall grading of selected areas
Thana Serial Community
Type
Total Score of Risks.
(Out of 10)
ix
Grade
Point
iy
Total Grade
Point
ii yx
n
i
i
n
i
ii
y
yx
GPA
1
1 Grade
Badda
1 Slum 8 3 24
5.8 Medium
2 Low-income 6 3 18
3 Low-income 4 2 8
4 Low-income 5 2 10
5 Slum 4 2 8
6 Low-income 6 3 18
Total: 15 86
Gulshan
7 Slum 9 4 36
7.5 High
8 Slum 8 3 24
9 Low-income 5 2 10
10 Slum 8 3 24
11 Slum 8 3 24
12 Slum 4 2 8
Total: 17 126
Mirpur
13 Slum 4 2 8
6.3 High
14 Low-income 7 3 21
15 Slum 3 2 6
16 Slum 8 3 24
17 Low-income 3 2 6
18 Low-income 6 3 18
19 Slum 9 4 36
Total: 19 119
Tejgaon
20 Slum 4 2 8
6.1
High
21 Slum 7 3 21
22 Low-income 8 3 24
23 Low-income 4 2 8
24 Low-income 6 3 18
Total: 13 79
151
Table H.4: Overall grading of urban water supply options
Serial Water Supply Option
Total Score of Risks.
(Out of 10)
ix
Grade Point
iy
Total Grade
Point
ii yx
n
i
i
n
i
ii
y
yx
GPA
1
1 Grade
1
Piped water supply with reservoir
7 3 21
4.78 Medium
2 4 2 8
3 3 2 6
4 4 2 8
Total: 9 43
4
Piped water supply without reservoir
4 2 8
6.65 High
5 8 3 24
6 8 3 24
7 5 2 10
8 8 3 24
9 6 3 18
10 6 3 18
11 3 2 6
12 6 3 18
13 9 4 36
Total: 28 186
14
Hand pump connected to supply line
4 2 8
6.71 High
15 7 3 21
16 9 4 36
17 8 3 24
18 4 2 8
19 5 2 10
20 8 3 24
21 8 3 24
22 4 2 8
23 6 3 18
Total: 27 181
152
Appendix I: ANALYSIS OF WATER QUALITY OF SELECTED AREAS Table I.1: Water quality of sample areas water
Th
an
a
Wa
ter
Po
int
No
Co
mm
un
ity
Ty
pe
Water Supply Option Color
(Pt-co) Odor
Turbidity(NTU)
pH Chlorine -Residual
(mg/l)
FC
(cfu
/10
0m
l)
Badda 15 Slum Hand pump connected to supply line 14.8 N 0.48 6.87 0.03 270
Badda 16 Low-income Piped water supply without reservoir 15 N 1.10 7.10 0.02 230
Badda 17 Low-income Hand pump connected to supply line 13.2 N 0.64 6.91 0.02 170
Badda 18 Low-income Hand pump connected to supply line 2 N 0.90 7.00 0.57 120
Badda 23 Slum Hand pump connected to supply line 1 N 1.00 6.67 0.88 80
Badda 24 Low-income Hand pump connected to supply line 2 N 1.00 6.66 0.6 170
Gulshan 10 Slum Hand pump connected to supply line 11 N 1.65 6.64 0.03 275
Gulshan 11 Slum Piped water supply without reservoir 34 N 0.71 6.81 0.18 150
Gulshan 12 Low-income Piped water supply without reservoir 22 N 0.49 6.71 0.94 70
Gulshan 14 Slum Piped water supply without reservoir 15.9 N 0.59 6.75 1.02 70
Gulshan 21 Slum Hand pump connected to supply line 1 N 1.00 6.62 0.01 220
Gulshan 22 Slum Piped water supply with reservoir 1 N 1.00 7.20 0.02 220
Mirpur 2 Slum Piped water supply without reservoir no color N 2.55 6.72 0.26 135
Mirpur 3 Low-income Piped water supply with reservoir no color N 1.05 7.18 0.17 150
Mirpur 13 Slum Piped water supply with reservoir no color N 1.06 7.12 0.28 150
Mirpur 19 Slum Hand pump connected to supply line 4 N 0.95 6.10 0.15 250
Mirpur 25 Low-income Piped water supply without reservoir 1 N 1.00 6.38 0.02 290
Mirpur 26 Low-income Piped water supply without reservoir 2 N 1.00 6.17 0.02 350
Mirpur 27 Slum Piped water supply without reservoir 1 N 1.00 6.10 0.02 300
Tejgaon 4 Slum Hand pump connected to supply line 20.2 N 2.91 7.46 0.81 80
Tejgaon 6 Slum Hand pump connected to supply line no color N 0.87 7.54 0.01 230
Tejgaon 8 Low-income Piped water supply without reservoir no color N 1.34 7.02 0.02 190
Tejgaon 9 Low-income Piped water supply with reservoir no color N 0.63 7.84 0.75 120
Tejgaon 20 Low-income Piped water supply without reservoir 2 N 1.00 6.22 0.27 240
153
Table I.2: Community wise water quality analysis
Community Description FC Count (cfu/100ml)
0 100 200 300 400
Slum
Number 0 2 4 7 0
Cumulative 0 2 6 13 13
Exceeding 13 11 7 0 0
% Exceeding the stated FC count 100 85 54 0 0
Low-income
Number 0 1 6 3 1
Cumulative 0 1 7 10 11
Exceeding 11 10 4 1 0
% Exceeding the stated FC count 100 91 36 9 0
Table I.3: Selected areas wise water quality analysis
Selected Areas
Description FC Count (cfu/100ml)
0 100 200 300 400
Gulshan
Number 0 2 1 3 0
Cumulative 0 2 3 6 6
Exceeding 6 4 3 0 0
% Exceeding the stated FC count 100 67 50 0 0
Tejgaon
Number 0 1 2 3 0
Cumulative 0 1 3 6 6
Exceeding 6 5 3 0 0
% Exceeding the stated FC count 100 83 50 0 0
Badda
Number 0 0 3 3 0
Cumulative 0 0 3 6 6
Exceeding 6 6 3 0 0
% Exceeding the stated FC count 100 100 50 0 0
Mirpur
Number 0 0 3 3 1
Cumulative 0 0 3 6 7
Exceeding 7 7 4 1 0
% Exceeding the stated FC count 100 100 57 14 0
154
Table I.4: Urban water supply options wise water quality analysis
Urban Water Supply Options Description FC Count (cfu/100ml)
0 100 200 300 400
Piped water supply with reservoir
Number 0 0 3 1 0
Cumulative 0 0 3 4 4
Exceeding 4 4 1 0 0
% Exceeding the stated FC count 100 100 25 0 0
Piped water supply without reservoir
Number 0 2 3 4 1
Cumulative 0 2 5 9 10
Exceeding 10 8 5 1 0
% Exceeding the stated FC count 100 80 50 10 0
Hand pump connected to supply line
Number 0 2 3 5 0
Cumulative 0 2 5 10 10
Exceeding 10 8 5 0 0
% Exceeding the stated FC count 100 80 50 0 0
155
Appendix J: OVERALL GRADING BASED ON VULNERABILITY SCORES Table J.1: Grading of vulnerable communities
Serial Criteria Slum Low-income
Diarrhoea Typhoid Eye
Infections Diarrhoea Typhoid
Eye Infections
1 Sources Of Water 5.72 2.20 8.50 6.20 2.27 5.10
2 Urban Water Supply Options 5.90 1.47 7.80 6.54 1.70 6.01
3 Distance from HH to Source 5.80 1.43 9.02 3.66 1.70 3.52
4 Time Required to Fetch Water 7.04 2.13 7.17 3.66 1.70 3.52
5 Demand 5.17 1.50 6.91 7.31 1.73 5.35
6 Boiling Practices 6.00 1.10 4.50 5.20 2.27 5.35
7 Storage Practices 5.23 1.63 5.34 6.11 1.36 2.93
8 Sanitary Practices 5.24 1.30 4.44 4.70 1.13 4.22
9 Hand-wash Practices 5.43 1.50 4.67 3.66 1.70 2.60
10 Water Quality 7.07 1.10 7.02 5.34 1.36 4.78
11 SI Risk 7.62 1.53 6.09 5.19 1.70 4.08
Combined Vulnerability Score (CVS) 5.83 1.42 6.67 5.61 1.67 4.34
LEGEND
Grade Point Average
Grade Color Code
>=8-10 Very high
>=6-<8 High
>=3-<6 Medium
>=0-<3 Low
156
Table J.2: Overall grading of selected areas of Dhaka city
Se
ria
l
Criteria
Gulshan Tejgaon Badda Mirpur
Dia
rrh
oea
Typ
ho
id
Ey
e
Infe
cti
on
s
Dia
rrh
oea
Typ
ho
id
Ey
e
Infe
cti
on
s
Dia
rrh
oea
Typ
ho
id
Ey
e
Infe
cti
on
s
Dia
rrh
oea
Typ
ho
id
Ey
e
Infe
cti
on
s
1 Sources Of Water 6.48 2.15 10.00 6.50 1.25 6.50 3.20 0.95 2.27 5.53 2.27 3.83
2 Urban Water Supply Options 9.16 1.43 10.00 7.90 0.83 6.48 3.33 0.63 2.48 6.00 1.70 1.60
3 Distance from HH to Source 7.80 0.73 10.00 6.57 0.00 4.88 2.40 0.63 1.70 4.12 1.70 0.80
4 Time Required to Fetch Water 7.73 1.43 8.89 6.57 0.83 4.88 2.40 0.63 1.70 4.12 1.70 0.80
5 Demand 6.51 0.73 8.89 7.92 0.83 5.23 3.36 0.63 2.84 4.64 1.70 2.88
6 Boiling Practices 5.62 1.10 8.00 8.63 1.25 6.82 4.85 0.95 3.53 5.84 2.27 3.83
7 Boiling Duration 2.67 0.00 0.00 8.00 0.00 5.63 3.87 0.00 2.87 5.64 2.27 3.33
8 Storage Practices 7.13 1.08 9.23 6.53 0.63 4.19 3.10 0.93 1.84 6.38 1.36 2.06
9 Sanitary Practices 2.60 0.44 7.27 5.86 0.50 4.07 3.53 0.84 2.64 4.64 1.13 2.20
10 Hand-wash Practices 4.68 0.73 8.89 7.11 0.83 3.72 3.88 0.63 2.65 5.18 1.70 1.50
11 Water Quality 5.99 1.08 8.00 7.22 0.63 6.69 5.07 1.05 2.94 5.47 1.36 1.66
12 SI Risk 8.10 0.73 10.00 5.70 0.83 5.42 3.84 1.40 2.72 7.70 1.70 2.23
Combined Vulnerability Score (CVS) 6.55 0.94 8.93 7.01 0.68 5.38 3.64 0.80 2.51 5.57 1.67 2.19
157
Table J.3: Overall grading of urban water supply options of Dhaka city
Se
ria
l
Criteria
Piped water supply with reservoir
Piped water supply without reservoir
Hand pump connected to supply line
Dia
rrh
oea
Typ
ho
id
Ey
e
Infe
cti
on
s
Dia
rrh
oea
Typ
ho
id
Ey
e
Infe
cti
on
s
Dia
rrh
oea
Typ
ho
id
Ey
e
Infe
cti
on
s
1 Sources Of Water 6.66 0.00 7.28 5.10 3.03 5.30 6.10 2.25 4.35
2 Urban Water Supply Options 6.50 0.00 9.10 4.90 2.70 5.50 6.30 2.10 5.10
3 Distance from HH to Source 5.61 0.00 7.81 3.35 2.28 2.75 7.80 1.37 7.08
4 Time Required to Fetch Water 7.65 0.00 7.81 3.35 2.28 2.75 6.49 1.37 7.23
5 Demand 7.25 0.00 7.81 7.60 2.28 5.07 5.53 1.50 5.15
6 Boiling Practices 6.55 0.00 8.93 4.75 3.03 5.34 6.98 1.05 5.05
7 Boiling Duration 5.30 0.00 5.63 5.20 2.27 2.60 8.80 0.00 3.33
8 Storage Practices 4.76 0.00 5.20 6.74 1.82 7.00 5.46 1.55 4.95
9 Sanitary Practices 6.12 0.00 6.25 5.95 0.54 6.53 5.66 1.32 4.41
10 Hand-wash Practices 5.61 0.00 7.81 3.88 2.28 4.45 6.21 1.50 4.43
11 Water Quality 6.38 0.00 6.94 6.20 1.82 5.15 5.92 1.13 4.47
12 SI Risk 5.55 0.00 6.07 7.37 2.28 4.86 7.60 1.50 7.08
Combined Vulnerability Score (CVS) 6.05 0.00 7.04 5.65 2.00 5.04 6.45 1.29 5.29
Note: “0” does not necessarily mean “No vulnerability” but “No data” observed at the time of survey.
158
Appendix K: ESTIMATED HEALTH IMPACT VALUATION OF WATERBORNE DISEASES OF DHAKA CITY
Table K.1: Estimated health impact valuation of vulnerable communities of selected areas of Dhaka city.
Thana
Co
mm
un
ity t
yp
e
To
tal N
um
ber
of
Fam
ily M
em
be
rs
No
of
pers
on
s b
ein
g
dir
ectl
y e
xp
os
ed
No
of
pers
on
s b
ein
g
ind
irectl
y e
xp
osed
Dis
ea
ses
Typ
e
To
tal M
em
be
rs o
f
aff
ecte
d F
am
ily
No
of
Fam
ily M
em
be
rs
aff
ecte
d
Rate
of
incid
en
ces
( i =
h/g
)
Lik
ely
no
. o
f p
ers
on
s
dir
ectl
y e
xp
os
ed
(j =
d X
i)
Lik
ely
no
. o
f p
ers
on
s
ind
irectl
y e
xp
osed
( k =
e X
i)
Mean
Co
st
of
Dis
ease
s
(Tk.)
Esti
mate
d C
ost
of
Dis
ea
ses
for
the S
ele
cte
d a
reas
( T
k.)
(j+
k)X
l
Pre
vale
nce r
ate
(in
1000)
No
of
pers
on
s l
ike
ly t
o
be e
xp
os
ed
bas
ed
on
Pre
vale
nce r
ate
( o
= n
Xe /1
000)
Esti
mate
d C
ost
of
Dis
ea
ses
bas
ed
on
Pre
vale
nce
rate
(T
k.)
( p
= o
X l)
(a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) (m) (n) (o) (p)
Gulshan
Slum 51 1140 25500
Diarrhoea 42 28 0.67 760 17000 1521.88 27,028,567.28 521.37 13295 20,233,378.49
Typhoid 14 3 0.21 245 5465 4982.68 28,451,086.49 68.38 1744 8,689,788.94
Eye Infections
36 36 1 1140 25500 916.58 24,417,575.38 358.97 9154 8,390,333.52
Low-income
5 10 1500
Diarrhoea 5 2 0.4 4 600 1521.88 919,214.79 430.11 646 983,133.70
Typhoid 0 0 0 0 0 4982.68 - 21.51 33 164,428.35
Eye Infections
0 0 0 0 0 916.58 - 247.31 371 340,049.57
Tejgaon
Slum 20 245 5750
Diarrhoea 20 11 0.55 135 3163 1521.88 5,019,156.25 521.37 2998 4,562,592.61
Typhoid 8 2 0.25 62 1438 4982.68 7,474,015.72 68.38 394 1,963,174.80
Eye Infections
0 0 0 0 0 916.58 - 358.97 2065 1,892,728.73
Low-income
28 210 6550
Diarrhoea 28 10 0.36 75 2340 1521.88 3,675,337.28 430.11 2818 4,288,654.43
Typhoid 0 0 0 0 0 4982.68 - 21.51 141 702,557.48
Eye Infections
18 11 0.61 129 4003 916.58 3,787,290.60 247.31 1620 1,484,852.56
Badda
Slum 21 400 4200
Diarrhoea 21 8 0.38 153 1600 1521.88 2,667,853.52 521.37 2190 3,332,914.55
Typhoid 16 3 0.19 75 788 4982.68 4,300,050.38 68.38 288 1,435,011.02
Eye Infections
15 3 0.2 80 840 916.58 843,249.60 358.97 1508 1,382,196.09
Low-income
21 200 8500
Diarrhoea 21 12 0.57 115 4858 1521.88 7,568,303.22 430.11 3656 5,563,988.85
Typhoid 0 0 0 0 0 4982.68 - 21.51 183 911,829.92
Eye Infections
21 9 0.43 86 3643 916.58 3,417,910.61 247.31 2103 1,927,558.60
159
Mirpur
Slum 25 160 7500
Diarrhoea 25 14 0.56 90 4200 1521.88 6,528,860.00 521.37 3911 5,952,067.94
Typhoid 0 0 0 0 0 4982.68 - 68.38 513 2,556,113.38
Eye Infections
20 3 0.15 24 1125 916.58 1,053,145.43 358.97 2693 2,468,338.24
Low-income
39 286 8000
Diarrhoea 39 16 0.41 118 3283 1521.88 5,175,909.76 430.11 3441 5,236,784.91
Typhoid 6 2 0.33 96 2667 4982.68 13,767,136.95 21.51 173 862,003.15
Eye Infections
6 3 0.5 143 4000 916.58 3,797,372.93 247.31 1979 1,813,903.22
Total: 210 2651 67500
149,892,036.19
87,138,383.05
Table K.2a: Estimated health impact valuation of vulnerable community of Dhaka city based on LGED (2005) statistics.
Total HHs HH Size
Estimated Slum
Population (No)
Diseases Type Mean Cost of
Diseases (Tk.)
Prevalence rate
(in 1000)
No of persons likely to be exposed based on Prevalence rate
(No)
Estimated Cost of Diseases based on
Prevalence rate (Tk.)
267,065 5.25 14,02,091
Diarrhoea 1521.88 480.95 674,340 1,026,263,741.82
Typhoid 4982.68 47.62 66,767 332,678,404.80
Eye Infections 916.58 309.52 433,981 397,776,418.11
Total Cost of Diseases In Taka 1,756,718,564.73
In Dollar [Exchange Rate 1 USD = 67.08 Tk. ;BBS (2010) for 2005-06] 26,188,410.33
Table K.2b: Estimated health impact valuation of vulnerable community of Dhaka city based on BBS (2011) statistics.
Estimated Population
(2011)
% of Total Population Living in Slums
Estimated Slum
Population (No)
Diseases Type Mean Cost of
Diseases (Tk.)
Prevalence rate
(in 1000)
No of persons likely to be exposed based on Prevalence rate
(No)
Estimated Cost of Diseases based on
Prevalence rate (Tk.)
1,18,75,000 38% 45,12,500
Diarrhoea 1521.88 480.95 2,170,298 3,302,930,489.58
Typhoid 4982.68 47.62 214,881 1,070,682,647.14
Eye Infections 916.58 309.52 1,396,727 1,280,205,960.94
Total Cost of Diseases In Taka 5,653,819,097.66
In Dollar [Exchange Rate 1 USD = 69.18 Tk.; BBS (2010) for 2009-10] 81,726,208.41
160
Appendix L: CALCULATION OF PREVALENCE RATE OF WATERBORNE DISEASES OF SELECTED AREAS OF DHAKA CITY Table L.1: Prevalence rate of diarrhoea
Definition
Ag
e G
rou
p
(Ye
ars
)
Ge
nd
er
Su
rve
ye
d
Po
pu
lati
on
Nu
mb
er
of
Inc
ide
nce
s
Prevalence Rate (PR) Per 1000 Population
Based on Surveyed Age Group and Gender (PIG)
Based on Surveyed Gender (PGT)
Based on Total Surveyed Population (PTP)
Children < 5 years <5
F 16 10
625.00
104.17
47.62
M 17 5
294.12
43.86
23.81
Children at 5 years to 14 years
5-14
F 20 9
450.00
93.75 42.86
M 26 18
692.31
157.89
85.71
Aging > 15 years >15
F 60 26
433.33
270.83
123.81
M 71 33
464.79
289.47 157.14
Female Prevalence F 96 45
468.75
214.29
Male Prevalence M 114 56
491.23
266.67
For Entire Sample Both
Gender 210 101
480.95
161
Table L.2: Prevalence rate of typhoid
Definition Age
Group (Years)
Gender Surveyed
Population Number of Incidences
Prevalence Rate (PR) Per 1000 Population
Based on Surveyed Age
Group and Gender (PIG)
Based on Surveyed
Gender (PGT)
Based on Total Surveyed Population
(PTP)
Children < 5 years <5 F 16 2 125.00 20.83 9.52
M 17 1 58.82 8.77 4.76
Children at 5 years to 14 years
5-14 F 20 1 50.00 10.42 4.76
M 26 1 38.46 8.77 4.76
Aging > 15 years >15 F 60 3 50.00 31.25 14.29
M 71 2 28.17 17.54 9.52
Female Prevalence F 96 6 62.50 62.50
Male Prevalence M 114 4 35.09 35.09
For Entire Sample Both Gender 210 10 47.62
162
Table L.3: Prevalence rate of eye infections
Definition Age
Group (Years)
Gender Surveyed
Population Number of Incidences
Prevalence Rate (PR) Per 1000 Population
Based on Surveyed Age
Group and Gender (PIG)
Based on Surveyed
Gender (PGT)
Based on Total Surveyed Population
(PTP)
Children < 5 years <5 F 16 3 187.50 31.25 14.29
M 17 7 411.76 61.40 33.33
Children at 5 years to 14 years
5-14 F 20 8 400.00 83.33 38.10
M 26 9 346.15 78.95 42.86
Aging > 15 years >15 F 60 14 233.33 145.83 66.67
M 71 24 338.03 210.53 114.29
Female Prevalence F 96 25 260.42 119.05
Male Prevalence M 114 40 350.88 190.48
For Entire Sample Both Gender 210 65 309.52
163
Table L.4: Prevalence rate of waterborne diseases of community
Community Surveyed
Population
Diarrhoea Typhoid Eye Infections
Number of Incidences
PRGT PRTP Number of Incidences
PRGT PRTP Number of Incidences
PRGT PRTP
Slum 117 61 521.37 290.48 8 68.38 38.10 42 358.97 200.00
Low-income 93 40 430.11 190.48 2 21.51 9.52 23 247.31 109.52
Total: 210 101 10 65
Table L.5: Prevalence rate of waterborne diseases at different selected areas
Selected Areas
Surveyed Population
Diarrhoea
Typhoid
Eye Infections
Number of Incidences
PRGT PRTP Number of Incidences
PRGT PRTP Number of Incidences
PRGT PRTP
Gulshan 56 30 535.71 142.86 3 53.57 14.29 36 642.86 171.43
Tejgaon 48 21 437.50 100.00 2 41.67 9.52 11 229.17 52.38
Badda 42 20 476.19 95.24 3 71.43 14.29 12 285.71 57.14
Mirpur 64 30 468.75 142.86 2 31.25 9.52 6 93.75 28.57
Total: 210 101 10 65
Table L.6: Prevalence rate of waterborne diseases with respect to urban supply options
Urban Water Supply Options
Surveyed Population
Diarrhoea Typhoid Eye Infections
Number of Incidences
PRGT PRTP Number of Incidences
PRGT PRTP Number of Incidences
PRGT PRTP
Piped water supply with reservoir
37 20 540.54 95.24 0 0.00 0.00 10 270.27 47.62
Piped water supply without reservoir
77 27 350.65 128.57 4 51.95 19.05 22 285.71 104.76
Hand pump connected to supply line
96 54 562.50 257.14 6 62.50 28.57 33 343.75 157.14
Total: 210 101 10 65
164
Appendix M: CORRELATION BETWEEN DIARRHOEAL INCIDENCES AND CLIMATIC FACTORS Table M.1: Data of diarroheal incidences and climatic factors for both selected areas and Dhaka (2000-2010)
Item Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Std Dev
Rainfall(mm) 6 17.2 61.6 120.9 258.4 379.1 415.4 307.2 357.4 193.0 26.5 4.5 152.10
Temperature(°C) 18.7 22.3 26.4 28.7 29 28.9 28.8 29.1 28.7 27.5 24.2 20.5 3.56
Humidity (%) 69.4 61.2 59.4 68.5 72.9 80.2 81.2 80.0 81.0 77.3 70.9 70.9 7.17 No. of
Patients Tejgaon 250 300 600 650 400 350 450 550 500 450 400 250 124.93 Badda 300 350 600 800 700 450 550 1100 800 600 600 400 215.50
Gulshan 450 450 550 800 600 450 500 650 600 550 500 400 105.74 Mirpur 450 500 850 1650 1150 950 850 1200 1150 900 650 500 337.89
Avg No. of Patients (Selected areas)
363 400 650 975 713 550 588 875 763 625 538 388 183.03
Avg No. of Patients (Dhaka)
250 250 400 550 450 300 350 450 400 350 300 250 90.91
Table M.2: Data conversion for Microsoft Excel output using regression analysis formula for exponential/logarithmic growth
Item Values Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Avg No. of Patients (Selected areas)
Ysa 363 400 650 975 713 550 588 875 763 625 538 388
y = Log10(Ysa) 2.56 2.60 2.81 2.99 2.85 2.74 2.77 2.94 2.88 2.80 2.73 2.59
Avg No. of Patients (Dhaka)
Ydk 250 250 400 550 450 300 350 450 400 350 300 250
y = Log10(Ydk) 2.40 2.40 2.60 2.74 2.65 2.48 2.54 2.65 2.60 2.54 2.48 2.40
165
Table M.3: Correlation between temperature and diarrhoeal patients of selected areas
n
Temperature
(°C)
Average No. of Patients
(Selected areas)
x
y
1 18.7 7.37 54.3169 2.56 0.21 0.0451 1.5648
= 0.8665
2 22.3 3.77 14.2129 2.60 0.17 0.0290 0.6415
3 26.4 -0.33 0.1089 2.81 -0.04 0.0017 0.0134
4 28.7 -2.63 6.9169 2.99 -0.22 0.0470 0.5701
5 29.0 -2.93 8.5849 2.85 -0.08 0.0065 0.2369
6 28.9 -2.83 8.0089 2.74 0.03 0.0010 -0.0902
7 28.8 -2.73 7.4529 2.77 0.00 0.0000 -0.0078
8 29.1 -3.03 9.1809 2.94 -0.17 0.0288 0.5144
9 28.7 -2.63 6.9169 2.88 -0.11 0.0122 0.2901
10 27.5 -1.43 2.0449 2.80 -0.02 0.0006 0.0338
11 24.2 1.87 3.4969 2.73 0.04 0.0017 0.0775
12 20.5 5.57 31.0249 2.59 0.18 0.0336 1.0215
∑
312.8
152.2668 33.27
0.2071 4.8662
26.07
2.77 x
22),(
)()(
))((
yyxx
yyxxCr yx
166
Table M.4: Correlation between temperature and diarrhoeal patients of Dhaka city
n
Temperature
(°C)
Average No. of Patients (Dhaka)
x
y
1 18.7 7.37 54.3169 2.40 0.14 0.0203 1.0513
= 0.7992
2 22.3 3.77 14.2129 2.40 0.14 0.0203 0.5378
3 26.4 -0.33 0.1089 2.60 -0.06 0.0038 0.0203
4 28.7 -2.63 6.9169 2.74 -0.20 0.0399 0.5254
5 29.0 -2.93 8.5849 2.65 -0.11 0.0127 0.3300
6 28.9 -2.83 8.0089 2.48 0.06 0.0040 -0.1796
7 28.8 -2.73 7.4529 2.54 0.00 0.0000 0.0095
8 29.1 -3.03 9.1809 2.65 -0.11 0.0127 0.3412
9 28.7 -2.63 6.9169 2.60 -0.06 0.0038 0.1617
10 27.5 -1.43 2.0449 2.54 0.00 0.0000 0.0050
11 24.2 1.87 3.4969 2.48 0.06 0.0040 0.1187
12 20.5 5.57 31.0249 2.40 0.14 0.0203 0.7946
∑
312.8
152.2668 30.49
0.1420 3.7158
26.07
2.54
x
22),(
)()(
))((
yyxx
yyxxCr yx
167
Table M.5: Projected data for diarrhoeal patients of selected areas and Dhaka city basing on temperature
Temperature(°C)
x
Selected Areas ( y = 0.032x + 1.9392 ) Dhaka (y = 0.0244x + 1.9045)
Ysa = 10y
Likely to be Affected
( YSA± 183) Ydk = 10
y
Likely to be Affected (YDK± 91)
Monthly Average Lower bound Higher bound Monthly Average Lower bound Higher bound
18 328 145 511 221 130 312
19 353 170 536 234 143 325
20 380 197 563 247 156 338
21 409 226 592 262 171 353
22 440 257 623 277 186 368
23 474 291 657 293 202 384
24 510 327 693 310 219 401
25 549 366 732 327 236 418
26 591 408 774 346 255 437
27 636 453 819 366 275 457
28 685 502 868 387 296 478
29 737 554 920 410 319 501
30 793 610 976 434 343 525
31 854 671 1037 459 368 550
32 919 736 1102 485 394 576
33 990 807 1173 513 422 604
34 1065 882 1248 543 452 634
35 1147 964 1330 574 483 665
36 1234 1051 1417 607 516 698
37 1329 1146 1512 642 551 733
38 1430 1247 1613 679 588 770
39 1539 1356 1722 718 627 809
40 1657 1474 1840 760 669 851
168
Appendix N: CRITERIA WISE HEALTH IMPACTS OF THE SELECTED COMMUNITIES, AREAS AND URBAN WATER SUPPLY OPTIONS
Figure N.1: State of health impacts of selected community based on water source’s connection
Figure N.2: State of health impacts of selected areas based on water source’s connection
0
10
20
30
40
50
60
70
80
90
100
Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections
private connection public connection/Tap water
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Slum Low-income
0
10
20
30
40
50
60
70
80
90
100
Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections
private connection public connection
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Source Connection
Gulshan Tejgaon Badda Mirpur
169
Figure N.3: State of health impacts of urban water supply options based on water source’s connection
Figure N.4: State of overall health impacts of water sources’ connection
0
10
20
30
40
50
60
70
80
90
100
Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections
private connection public connection
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
0
10
20
30
40
50
60
70
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Private Connection Public Connection/Tap Water
170
Figure N.5: State of health impacts of selected community based on urban water supply options
Figure N.6: State of health impacts of selected areas based on urban water supply options
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Piped water supply with reservoir Piped water supply withoutreservoir
Hand pump connected to supplyline
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Slum Low-income
0
10
20
30
40
50
60
70
80
90
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Piped water supply with reservoir Piped water supply withoutreservoir
Hand pump connected to supplyline
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Gulshan Tejgaon Badda Mirpur
171
Figure N.7: Overall state of health impacts based on urban water supply options
Figure N.8: State of health impacts of selected community based on distance between HHs and sources
of water
0
10
20
30
40
50
60
70
80
90
100
Piped water supply with reservoir Piped water supply withoutreservoir
Hand pump connected to supplyline
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Diarrhoea Typhoid Eye Infections
0
10
20
30
40
50
60
70
80
90
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
<50m <100 (50-100)m <250 (100-250) m
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Distance between HH and Source of Water
Slum Low-income
172
Figure N.9: State of health impacts of selected areas based on distance between HHs and sources of water
Figure N.10: State of health impacts of urban water supply options based on distance between HHs and sources of water
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
<50m <100 (50-100)m <250 (100-250) m
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Distance between HH and Source of Water
Gulshan Tejgaon Badda Mirpur
0
10
20
30
40
50
60
70
80
90
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
<50m <100 (50-100)m <250 (100-250) m
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
173
Figure N.11: Overall state of health impacts of urban water supply options based on distance between
HHs and sources of water
Figure N.12: State of health impacts of selected community based on time required fetching water from
its source.
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
<50m <100m (50m-100m) <250m (100m-250m)
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
5 minutes 5-15 minutes 15-30 minutes
% o
f in
cid
ence
aga
inst
Exp
osu
re
Time to Fetch Water from Source
Slum Low-income
174
Figure N.13: State of health impacts of selected areas based on time required fetching water from its source.
Figure N.14: State of health impacts of urban water supply options based on time required fetching water
from its source.
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
5 minutes 5-15 minutes 15-30 minutes
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Gulshan Tejgaon Badda Mirpur
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
5 minutes 5-15 minutes 15-30 minutes
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
175
Figure N.15: Overall state of health impacts of urban water supply options based on time required
fetching water from its source.
Figure N.16: State of health impacts of selected community based on demand of water
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
5 minutes 5-15 minutes 15-30 minutes
0
10
20
30
40
50
60
70
80
90
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Full/As per demand 75% of demand 50% of demand
% o
f in
cid
ence
aga
inst
Exp
osu
re
Slum Low-income
176
Figure N.17: State of health impacts of selected areas based on demand of water
Figure N.18: State of health impacts of urban water supply options based on demand of water
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Full/As per demand 75% of demand 50% of demand
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Demand to meet
Gulshan Tejgaon Badda Mirpur
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Full/As per demand 75% of demand 50% of demand
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Demand to meet
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
177
Figure N.19: State of overall health impacts due to demand of water
Figure N.20: State of health impacts of selected community based on boiling practices
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Full/As per demand 75% of demand 50% of demand
0
10
20
30
40
50
60
70
80
Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections
Yes No
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Boiling Practices
Slum Low-income
178
Figure N.21: State of health impacts of selected areas based on boiling practices
Figure N.22: State of health impacts of urban water supply options based on boiling practices
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections
Yes No
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Boiling Practices
Gulshan Tejgaon Badda Mirpur
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections
Yes No
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Boiling Practices
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
179
Figure N.23: Overall state of overall health impacts due to boiling practices
Figure N.24: State of health impacts of selected community based on boiling duration
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Yes No
0
10
20
30
40
50
60
70
80
Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections
5-15 minutes 15-30 minutes
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Boiling Duration
Slum Low-income
180
Figure N.25: State of health impacts of selected areas based on boiling duration
Figure N.26: State of health impacts of urban water supply options based on boiling duration
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections
5-15 minutes 15-30 minutes
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Gulshan Tejgaon Badda Mirpur
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections Diarrhoea Typhoid Eye Infections
5-15 minutes 15-30 minutes
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
181
Figure N.27: State of overall health impacts due to boiling duration
Figure N.28: State of health impacts of selected community based on storage practices
0
10
20
30
40
50
60
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
5-15 minutes 15-30 minutes
0
20
40
60
80
100
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Drum Kolosh Patil Water Bottle
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Storage Practices
Slum Low-income
182
Figure N.29: State of health impacts of selected areas based on storage practices
Figure N.30: State of health impacts of urban water supply options based on storage practices
0
20
40
60
80
100
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Drum Kolosh Patil Water Bottle
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Storage Practices
Gulshan Tejgaon Badda Mirpur
0
20
40
60
80
100
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Drum Kolosh Patil Water Bottle
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Storage Practices
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
183
Figure N.31: Overall state of health impacts based on storage practices
Figure N.32: State of health impacts of selected community based on sanitary practices
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Drum Kolosh Patil Water Bottle
0
20
40
60
80
100
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Sanitary sewer Septic tank system Pit latrine Hanging latrine Unsanitary
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Slum Low-income
184
Figure N.33: State of health impacts of selected areas based on sanitary practices
Figure N.34: State of health impacts of urban water supply options based on sanitary practices
0
20
40
60
80
100
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Sanitary sewer Septic tank system Pit latrine Hanging latrine Unsanitary
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Gulshan Tejgaon Badda Mirpur
0
20
40
60
80
100
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Sanitary sewer Septic tank system Pit latrine Hanging latrine Unsanitary
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
185
Figure N.35: Overall state of health impacts based on sanitary practices
Figure N.36: State of health impacts of selected community based on hand-wash practices
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Sanitary sewer Septic tank system Pit latrine Hanging latrine Unsanitary
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Nothing Ash Soap
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Slum Low-income
186
Figure N.37: State of health impacts of selected areas based on hand-wash practices
Figure N.38: State of health impacts of urban water supply options based on hand-wash practices
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Nothing Ash Soap
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Gulshan Tejgaon Badda Mirpur
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Nothing Ash Soap
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
187
Figure N.38: Overall state of health impacts based on hand-wash practices
Figure N.39: State of health impacts of selected community based on water quality
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Nothing Ash/soil Soap
0
20
40
60
80
100
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
0-100 100-200 200-300 300-400
% o
f in
cid
en
ce a
gain
st E
xpo
sure
FC Count (cfu/100ml)
Slum Low-income
188
Figure N.40: State of health impacts of selected areas based on water quality
Figure N.42: State of health impacts of urban water supply options based on water quality
0
20
40
60
80
100
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
0-100 100-200 200-300 300-400
% o
f in
cid
en
ce a
gain
st E
xpo
sure
FC Count (cfu/100ml)
Gulshan Tejgaon Badda Mirpur
0
20
40
60
80
100
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
Dia
rrh
oe
a
Typ
ho
id
Eye
Infe
ctio
ns
0-100 100-200 200-300 300-400
% o
f in
cid
en
ce a
gain
st E
xpo
sure
FC Count (cfu/100ml)
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
189
Figure N.43: Overall state of health impacts based on water quality
Figure N.44: State of health impacts of selected community based on SI risk grade
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
0-100 100-200 200-300 300-400
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Medium High Very High
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Slum Low-income
190
Figure N.45: State of health impacts of selected areas based on SI risk grade
Figure N.46: State of health impacts of urban water supply options based SI risk grade
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Medium High Very High
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Gulshan Tejgaon Badda Mirpur
0
20
40
60
80
100
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Diarrhoea Typhoid EyeInfections
Medium High Very High
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Piped water supply with reservoir Piped water supply without reservoir Hand pump connected to supply line
191
Figure N.47: Overall state of health impacts based SI risk grade
0
20
40
60
80
100
Diarrhoea Typhoid Eye Infections
% o
f in
cid
en
ce a
gain
st E
xpo
sure
Medium High Very High
192
Appendix O: THEMATIC MAPS OF DHAKA CITY
Figure O.1: Water bodies and distribution DWASA DTWs in selected areas of DMPA
Figure O.2: Distribution of water points
Figure O.3: Distribution of FC concentration to the sample points
193
Figure O.4: Sample point wise diarrhoeal incidences
Figure O.5: Sample point wise typhoid incidences
Figure O.6: Sample point wise eye infections’ incidences
194
Figure O.7: Vulnerability state of selected areas according to diarrhoea
Figure O.8: Vulnerability state of selected areas according to typhoid
Figure O.9: Vulnerability state of selected areas according to eye infections’ incidences