ANALYSIS OF SURVEILLANCE

DATADr. Ronnie D. Domingo

Design

formField data

gathering

Dataencodin

g

Data Analysi

s

ReportWritin

g

Data Processing

Data

pro

cess

ing

• Sorting• Coding• Editing • Summarizing

Data analysis

Data processing

• A series of steps undertaken to transform collected raw data into a form suitable for statistical analysis (Sanchez et al, 1989)

Data sorting method

• Types of data sheets• Numbering system for

data sheets (especially for surveys)

• The physical “container” for these raw data

Sorting

Coding

Editing

Summarizing

Data Coding• Examples

Data Possible codes

“Yes” answer Y or 1

“No” answer N or 2

No response 999 or U for unknown

Does not know 888 or D

Sorting

Coding

Editing

Summarizing

Data editing/ validation

Examine the data for four things: C.A.T.S.• Completeness• Accuracy• Traceability• Standard format

Sorting

Coding

Editing

Summarizing

Spreadsheet from Hell

By Daniel W. Byrne

Spreadsheet from Heaven

By Daniel W. Byrne

GIGO• Garbage In, Garbage Out

Form Level Validation:

• At the stage of filling up the online or printed form.

• Mandatory vs optional fields• INC entries= “SUBMIT” failD

ata

Vali

dat

ion

Field Level Validation:

• Field= space where you write the answer

• “Farmer’s Name” field = Fernan@do Cruz

• Date: 03-02-2016• Provide a list of possible

answers• Other fields auto appear or

disappear

Dat

a Va

lid

atio

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Data Saving Validation:

• Option: keep the record as a draft copy vs “Submit” as final copy

• User with time to review and revise entries

Dat

a Va

lid

atio

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Validation of Continuous Variables

• Continuous variables: age, height, weight, feed consumption, size of lesion, egg per gram of feces, temperature, etc.

• Check the following: – Minimum value– maximum value– mean– median

Vari

able

s

Validation techniques

Sample bar chart of lung score of pigs from several farm sources. The expected lung scores should range from 0-55. Note “farmer117” registered an erroneous lung score of 60.

Farmer1

11

Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

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Farmer1

290

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Validation of Categorical Variables

• Categorical Variables –– nominal (sick, healthy)– ordinal (+,++, +++)

• Techniques:– Frequency checks– Cross Tabulations

Vari

able

s

Cross-check variables to detect awkward combinations.

Example a male dog positive for metritis.

Data Verification

• Comparing the output of two encoders

• Comparing the data on the screen against the original paper document.

• Comparing the print out of the computer database and the original printed document.

Summarizing the data

6400 records6002 usable398 rejected4565 from Bulacan1835 from Pampanga

83 other places2 files Abat.xls Farm.xls

Sorting

Coding

Editing

Summarizing

Design

formField data

gathering

Dataencodin

g

Data Analysi

s

ReportWritin

g

Data Processing

Data analysis

Data analysis: Tools

• Install statistical and graphics software packages

• Examples: SAS, SPSS, STATA, Epi Info, R software, Open Epi, Win Epi, QGIS

• Check the provider for newer software packages.

Type of Statistical Analysis

Descriptive statistics

Measures Descriptive StatisticsMeasures of central tendency

Mean, median, mode

Measures of variation Range, variance, standard deviation, standard error, confidence limits

Frequency distribution Counts or proportions in different groups; use frequency tables, histograms and other graphs for visual presentation

Rates and ratios Incidence, prevalence, etc.

Inferential statistics

Tests for difference Tests for Association

See next page Cohort study= Relative risk, attributable riskCase-control study = Odds ratioExperimental study = Protective valueCorrelation and regression analysis = linear relationship, non-linear relationship

From your sample, make inferences about the larger

population

Inferential statistics(deduce, generalize, extrapolate)

• Uses the theory of probability to make inferences about larger populations from your sample.

• The pattern seen in the analyzed sample is extrapolated to the target population.

Tests

Sample flow chart to select the appropriate statistical test

Essential components of a common report in veterinary

practice

Generate information from collected data.

Name the comic hero who caught this criminal?

The Phantom

Who visited this place?

Calling?

Every disease leaves a distinct

mark

Two premises of modern epidemiology:

Diseases in populations do not occur

in random fashion

Diseases in populations do have multiple determinants

Disease patterns are described based on three main epidemiologic variables:

Reasons for the Epi Triad:

• The three = most important;• The result= significant

information• The process= systematic• The by-product= hypothesis;• The output = transferable to

the stakeholders.

Information is processed data

Basic Activities: CDC

Count Aggregate the cases in the line listing by characteristic (e.g., place, animal, time)

Divide Divide the number of cases by the relevant denominator

Compare

Compare incidence across groups

Forms of analysis output

• Textual• Tabular• Graphical

Data Presentation: Graphical (Horizontal bar graph)

SFB

BFB

PFB

RFB

PGF

AAF

RDF

SCF

0 10 20 30 40 50 60 70 80 90

Proportion of positive samples (%)

Farm

Cod

e

Figure 1. Bar Graph of the proportion of Mycolasma hyopneumonia positive samples per farm of origin as detected by LAMP technique

Qualitative data

Data Presentation: Graphical (Vertical bar graph)

Aurora Bataan Bulacan N.Ecija Pampanga Tarlac Zambales -

50,000

100,000

150,000

200,000

250,000

300,000

350,000

Figure 1. Estimated dog population in the different provinces of Region III, 2013)

Qualitative data

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 20130

50

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150

200

250

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350

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450

500

Data Presentation: Graphical (Line graph)

Figure 2. Secular trend of animal rabies in Central Luzon, 2002 to 2013.

ContinuousQuantitative

data

Data Presentation: Graphical (Pie Graph)

Bulacan20%

Nueva Ecija15%

Tarlac10%

Pampanga30%

Zambales7%

Aurora6%

Bataan12%

Figure 3. Rabies vaccine allotment to different provinces in Central Luzon, 2013

AnimalWhich type of animals are prone to develop the disease and which

type tends to be spared?

Common groupings employed in epidemiology

AgeSex

SpeciesBreed

Use

Disease patterns are described based on three main epidemiologic variables:

AgeSex

SpeciesBreed

Use

Classification of time trends

• Short term• Cyclical• Seasonal• Long-term

Graphs of endemic and sporadic diseases

January February March April May June July August September October November December0

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25

Seasonal distribution of animal rabies in Central Luzon, 2002-2011

Month

Inci

denc

e co

unt o

f ani

mal

rabi

es

Disease patterns are described based on three main epidemiologic variables:

AgeSex

SpeciesBreed

Use

Short termCyclicalSeasonalLong-term

Surra Prevalence – CATT Percent Positive by Municipality

Source: EAHMI, based on data provided by PAHC and RADLs.

Types of Thematic Maps

1. Qualitative maps= maps that show non-measurable characteristics (e.g. Low and high rainfall).

2. Quantitative maps= maps that depict areas with measured variations

Qualitative Map

Geographic distribution of Japanese encephalitis

Types of quantitative maps: (a) Dot maps (b) Choropleth maps (c) Isopleth maps(d) Proportional symbol maps

Dot Maps

Choropleth maps

• Geographic areas are shaded or colored according to a prearranged key, each shading or color type corresponding to a range of values

• Commonly used in showing population density information

Isopleth Map

from iso meaning “equal” and pleth meaning “lines.”

Dot maps Choropleth maps Isopleth maps Proportional symbol maps