use of statistics in epidemiology

7/29/2019 Use of Statistics in Epidemiology

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USE OF STATISTICS IN EPIDEMIOLOGY

QUANTIFYING DISEASE BURDEN

Submitted by: Group F Submitted to:

Birav Pradhan (13) Mr. Anil

Khadka

Khil B. Thapa (16)

Nisha Shrestha (23)

Reecha Piya (27)

Santoshi Poudel (08)


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CONTENTS

INTRODUCTION

Background

Objective of the study

METHODOLOGY

FINDINGS AND DISCUSSIONS

Rate, Ratio and proportions

Measures of Central Tendency

Measures of Dispersion

Hypothesis Testing

CONCLUSION


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INTRODUCTION

is the study of the distribution and determinants of

health related states or events in a specified population and the

application of this study to the control of health problems.

Two types: Analytical epidemiology

Descriptive epidemiology


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Continued

Makes use of various statistical tools to draw valuable inferences

on the health related issues

Calculating statistics helps us to:- Describe risk

- Make comparisons among communities and smaller

definable groups

- Identify high-risk groups

- Develop hypotheses about the cause(s) of disease


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Continued Disease burden needs to be measured because of the following

reasons:

- Prioritizing actions in health and the environment

- Planning for preventive action

- Assessing performance of healthcare systems

- Comparing action and health gain

- Identifying high-risk populations

- Planning for future needs

- Setting priorities in health research


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OBJECTIVE OF OUR STUDY

- To determine the uses of biostatistics in epidemiology for quantifying the

disease burden

- To identify different statistical tools used in epidemiology

- To know about the applications of rate, ratio and proportion in epidemiology

- To know the uses of central tendency (mean and median) in epidemiology.

- To know about the application of Dispersion (Standard Deviation)

- To summarize the application of estimation and hypothesis testing inepidemiology.


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METHODOLOGY

- The study was conducted from September 14- September 22nd, 2012.

- Our study is Descriptive cross-sectional type.

- Data was collected through the internet, journals and text books.

- Data was processed via MS-Word 2007 and MS-PowerPoint 2007.

- The data presented in our study is secondary data.

- Our study is solely based on secondary data.


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FINDINGS AND DISCUSSIONS

A)

- An expression of the frequency with which an event occurs in a defined

population during a specified time.

- Mathematically, expressed in the form of (x/y)*k

- Three types:

actual observed rates such as birth and death rates

actual observed rates due to specific causes

to compare the health status of two or more places

in terms of mortality


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Crude Rate :

- Number of deaths (from all causes) per 1000 estimated

mid-year population in one year, in a given place. Calculated as:

CDR = Number of death during the year X 1000

Mid-year population


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Continued

:

- Ratio of total live births to total population in a specified community

or area over a specified period of time.

- Birth rate often expressed as number of live births per 1,000 of the

population per year; also called natality.

- Calculated by following formula:

Total number of live birth during a year X 1000

Population at midyear or average population


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Specific rates

- Number of death of child under one year age out of 1000 live birth

during a year in a given place.


Number of death of child under one year age X 1000

Total live birth during the same year


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Continued

:

- Proportion of death of children below 5 years of age in per 1000

population of children of same age

- Calculated as:

No. of children death of the age group 1 to 5 years in a year X 1000Total no. of children of the age group 1 to 5 years during the same year


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Continued

- Number of death of pregnant and postnatal (42 days) mother due

to pregnancy related cause (not death by other cause i.e. accident,

injury etc) out of per 100000 live birth.


Number of deaths of pregnant and postnatal mother X100000

Total live birth during the same year


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Other Rates include:

Cause Specific Death Rate (CSDR)

Case Fatality Rate (CFR)

Age Specific Death Rate (ASDR) Still Birth Rate (SBR)

Perinatal mortality rate (PNMR)

Neonatal Mortality Rate (NNMR) Post Neonatal Mortality Rate (PNNMR)

Under Five Mortality Rate (U5MR)


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- No. of new cases of a disease that occur during a specified time

period among the population, who are at the risk of developing the

disease.


Total new cases of a disease that occur during sp. period of time X 100

Total population at risk during that period


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Continued

- Form of incidence that measures the proportion of persons in a

population who experience an acute health event during a limited

period (e.g., during an outbreak).

- Two types of attack rate: Primary and Secondary

- Calculated as:

No. of new cases of a health problem during an outbreak X 100

Population size at the beginning of the period


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Continued :

- Proportion of people in a population who have a particular disease at a

specified point in time, or over a specified period of time.

- Calculated as:

Numbers of existing or current cases X 100

Population at that time or average population

Two types of Prevalence rate


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Continued :

- Total number of all current/existing cases (new and old) of a disease in the

defined population in one point of time.

- Calculated by cross-sectional survey as one time study.

:

- Total number of all current cases (new and old) of a disease during a defined

period of time in a specified population (i.e. annual prevalence).

- Less commonly used measure of prevalence and calculated by surveillance,

several time studies.


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- Expression of the relationship between numerator and denominator.

- Mathematically, Ratio =X\Y *k

Where, X=no of events

Y=total no of events

- Measurement of association

Incidence in exposed group

Incidence in non-exposed groupOdds of cases exposed or AD/BC

Odds of control exposed


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- It is a type of ratio in which the numerator is always included in

the denominator.

- Mathematically, it is expressed in the form of(x/x+y)*100.


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- The mean (or average) is the most popular and well known measure of

central tendency. It can be used with both discrete and continuous data, although its

use is most often with continuous data.

The median is the middle score for a set of data that has been arranged in

order of magnitude. It divides the series into two equal parts. Median is the

positional average.

- The position of median in a series is such that 50% of the observation lies

above the median and another 50% lies below the median.


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Measures of Dispersion

:

- Standard deviation is an improvement over mean deviation as a

major of dispersion and is used most commonly in statistical

analysis.

- A large standard deviation shows that the measurements of the

frequency distributions are widely spread whereas small standard

deviation means the observations are closely spread.


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Hypothesis Testing

They are the procedures for making rational decisions about the reality

of effects.

Hypothesis may be defined simply as a statement about population

parameter. The hypothesis that there were no effects is called null hypothesis (Ho).

The Alternative hypothesis (H1), is a statement of what a statistical

hypothesis is set up to establish.

Statistical hypothesis testing is used to determine whether an experimentconducted provides enough evidence to reject a proposition.


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A :

A statistical test used to determine whether two population

means are different when the variances are known and the

sample size is large.


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B) T-TEST

A statistic test used to determine whether there are differences

between two means or between a target value and a calculated

mean.

It is commonly used when the variances of two normal

distributions are unknown and when an experiment uses a small

sample size.


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C) ANOVA

A statistical method for making simultaneous comparisons between two or

more means.

Used to determine the impact independent variables have on the

dependent variable in a regression analysis.There are two types of ANOVA:

One way ANOVA : a technique used to compare means of two or more

samples (using the F distribution).

Two way ANOVA : statistical test to study the effect of two categorical

independent variables on a continuous outcome variable.


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D) CHI-SQUARE TEST

A statistical test commonly used for testing independence and

goodness of fit.

The data used in calculating a chi square statistic must be random,

raw, mutually exclusive, drawn from independent variables and be

drawn from a large enough sample.

The chi-square test is most widely used to conduct tests of

hypothesis that involve data that can be presented in a 2 table.


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CONCLUSIONBiostatistics is applied in wide range of topics (health related states and

events) in epidemiology in quantifying disease burden.

Different statistical tools are frequently used for measuring the pattern,

frequency and distribution of health related problems in epidemiology.

Biostatistics is the backbone for epidemiology in quantifying diseaseburden.


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THANK YOU

use of statistics in epidemiology

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