An updated presentation on the basics of epidemiology

1. National Institute of Health & Family Welfare
Basics of Epidemiology
Dr. Dipayan Banerjee
DHA final year

2. Definition of Epidemiology
The study of the distribution and
determinants of disease or health related
states and events in specified populations,
and the application of the knowledge for
disease prevention and control.

3. Clinical Practice Epidemiologist
What is wrong with this
patient?
What are disease in the
population?
How common are they?
Who is most affected?
History and Examination Population based surveys
Why is this person ill? What are the risk factors
for the condition of the
population?

4. Investigations Epidemiological studies
How shall I treat the
patient
What control strategies
are needed to reduce this
disease in population?
Medication /Surgeries/
Nothing
Intervention Studies
Patients comes to you You have to got to
Population or Source of
data about the population
Clinical Practice Epidemiologist

5. Components of Epidemiology
 Studies of Disease frequency
 Studies of the distribution.
 Studies of determinants.

6. Disease Frequency
 The basic measure of disease frequency is rate or
ratio.
 These are essential for comparing disease frequency in
different populations or subgroups of the same
population in relation to suspected casual factors.
 Such comparisons may yield clues to disease etiology-
which in turn is a vital step in the development of
strategies for prevention or control of health problem.

7. Distribution of Disease
 It occurs in patterns in a community.
 The distribution patterns in various subgroups
of the population should be studied by time,
place and person.
 This study helps in formulation of etiological
hypothesis .

8. Determinants of disease
 Identifying the underlying causes (or risk
factors ) of disease.
 It helps in developing scientifically sound
health programmes, interventions and policies
 It also helps in understanding the chronic
disease causation .

9. Disease Causation – Triad
Agent
• Biologic,
Chemical,
• Physical (injury,
trauma)
• Social /
Psychological
Host
• Genotype
• Nutrition
• Immunity
• Behavior
Environment
• Sanitation
• Weather
• Pollution
• Socio-Cultural
• Political
An interaction of
these three factors
is required to start
disease process in
human beings.

10. Epidemiological Approach
 Asking Questions and making comparisons
 Related to health Events
a. What is the problem?/ and Magnitude?
b. Where did it happen?
c. When did it happen?
d. Who are affected?
e. Why did it happen?

11. Cont.……
 Questions Related to Health Action
a. What can be done to reduce the problem?
b. How can it be prevented?
c. What action should be taken by the community? By
the Health Services? By other sectors?
d. What resources are required?
e. How are the activities to be organized?
f. What difficulties may arise in implementation?

12. Epidemiology and the Public's Health
Descriptive Data
Hypotheses
Test Hypotheses
Develop Interventions
Test Interventions
Intervene
Surveillance
Observational
Studies
Surveillance
Intervention
Studies

13. Measurements in Epidemiology
Is very broad and unlimited and includes the following :
 Measurement of Mortality
 Measurement of Morbidity
 Measurement of disability
 Measurement of presence ,absence of disease or
distribution of disease.
 Measure of medical needs ,health care needs ,health
care facilities.

14. Tools of measurement
Basic tool of measurement are:
 Rates: It measures the occurrence of some
particular event in a population during a given
period of time.
 Ratios: A relation in size between two random
quantities.
 Proportions: It is a ratio indicting the relation in
magnitude of a part of the whole.

15. Measures of disease frequency
Prevalence All current cases (old & new) existing
at a given point in time, or over a period of time in a
given population.
Incidence: Number of new cases, episodes or
events occurring over a defined period of time.

16. Incidence
Incidence may change genuinely (increase or
decrease) with the following factors:
• Introduction of a new risk factor (e.g., contraceptive
and increase in Thromboembolism, food additives
and cancer);
• Changing habits.
• Changing virulence of causative organisms.
• Changing potency of treatment or intervention
programs.
• Selective migration of susceptible persons to an
endemic area, which increase the incidence of the
disease.

17. Prevalence
These rates are typically obtained from cross –sectional
studies; occasionally, they are based on registers of
specific disease.
Prevalence depends on two main factors:
- previous incidence ,and
- Duration or chronicity of disease.
When both incidence and during of a specific disease are
relatively stable,
Prevalence (P) = incidence (I) X duration (D)

18. Prevalence may change over time in response to:
• Changes in incidence,
• Changes in disease duration and chronicity (e.g., some
disease may become shorter in duration or more acute
because of high recovery rate or high case fatality rate),
• Intervention (preventive ) programs,
• Selective attrition (e.g., selective migration of cases ,or of
susceptible or immune persons ), and
• Changing classification of what constitutes an “active ” case
and whether an “ arrested” case is counted or not.

19. Measures of Central Tendency
 Mean: It is the sum of all the observations divided
by the number of observations
 Median: It is that value of the variable which divides
the distribution into two equal parts, one part
containing values greater than the median and the
other one containing values less than the median
 Mode: it the most occurring value

20. Data presentation
Data can be
 Categorical or Qualitative- Male/Female ,
 Numerical or Quantitative
-Discrete data- observations in question can take
only certain numerical values. e.g. Pulse rate – 80, 74,
64
-Continuous data- E.g. Weight of children in kg: 11.0,
10.8,

21. Ways of Data Presentation
For Qualitative data
 Bar chart
 Pie chart
For Continuous data
 Histogram
 Frequency polygon
 Cumulative Frequency curve

22. Results of Screening for diabetes on incidence rate
5 died
5 migrated
5 recovered
25 cases
40 cases
960 free
20 cases
940 free
1000
women
Screening
31DEC77
1 January
1978
31 December
1978
Incident cases
during 1978
Prevalent cases
on 31 December
Attrition

23. Describing the Occurrence of events
 Vital statistics -- births and deaths &
marriages
 Disease prevalence
 Disease incidence
 Rates, ratios and proportions
 Indicators

24. Introduction to data triangulation
 Health programs generate data from multiple sources.
 But, different sections under the same program do review of
the performance/service data separately.
 Thus fail to see the full picture and to correlate.
 Plan actions piecemeal
 Leading to incomplete achievements.
 DATA TRIANGULATION FACILITATES DECISIONS AND BETTER
IMPLEMENTATION

25. Gather data from
multiple sources
Refine
strategies for
action
Examine data
quality&
interpret
Planning
Triangulation
Conducting
Triangulation
Communicating
Results (for Action)
A visual representation of the triangulation process

26. Steps in Data Triangulation
 Specify the questions
 Identify data sources, organize the data and identify data gaps
 Conduct data quality and validation checks
 Decide on data outlier and/or missing data
 Refine/revisit the questions chosen for data triangulation
 Analyze data from different sources for each question
 Do data triangulation & draw conclusions
 Summarize findings
 Plan strategies based on findings

27. DESCRIPTIVE EPIDEMIOLOGY
 Studies concerned with observing the distribution of disease
or health related characteristics in human populations and
identifying the characteristics with which the disease in
question seems to be associated.
 These studies basically ask the following three questions
1. When is the disease occurring? – Time distribution
2. Where is it occurring? – Place distribution
3. Who is getting the disease? – Person distribution

28. Time distribution
 Three kind of time trends or fluctuations have been
identified
1. Short term fluctuations
2. Periodic fluctuations
3. Long term or secular trends
Short term fluctuations
The best known Short term fluctuation in the occurrence
of a disease is an epidemic

29. Types of Epidemics
a. Common Source of Epidemics
These epidemics originate from a single source of infection or
disease producing agent. Two Common Source epidemics are
described below:
(I) Point source or Single Exposure Epidemic
 The agent responsible for the causation of disease is exposed to the
agent population at risk at one point of time and only once.
 For instance, a marriage party may get an epidemic of food poisoning
due to eating of contaminated food, the point source of the epidemic.
The cases will occur within its incubation period. The time after which
half the number of cases occur is know as the median incubation
period.
 A single exposure epidemic may also be caused by a chemical
(Bhopal Gas Tragedy) or a pollutant (Chernobyl nuclear holocaust).

30. Epidemic Curves
0
1
2
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12
Days
Cases
Common source: point exposure (e.g., salmonella)

31. (ii) Continuous or Multiple Exposure Epidemics
 The source of infection for the causation of an epidemic may be
continuous. In such a case the epidemic shall not cease to exist till
the source is removed.
 A well with contaminated water becomes a regular source of infection
to the people using it and the epidemic may continue till the time the
water is treated and made potable.
b. Propagated Epidemics
 Infectious Epidemics
 The propagated epidemics are generally of infectious origin and the
transmission of infection is from person to person.
 Vector transmission may also be there in diseases like malaria,
cholera, gastroenteritis and conjunctivitis etc. The speed of spread
depends on herd immunity, secondary attack rate and opportunities
for contacts. These epidemics tend to show radial spread with the
generation of a case.

32. Epidemic Curves
0
1
2
3
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11 12
Days
Cases
Common source: Intermittent exposure (e.g.,
contaminated well water)

33. Epidemic Curves
0
1
2
3
4
5
6
7
8
9
10
1 2 3 4 5 6 7 8 9 10 11 12
Week
Cases
Propagated source: secondary and tertiary cases (e.g.,
hepatitis A)

34. Seasonal Epidemics
 Infection diseases and some non-infectious diseases
both tend to have an increased incidence during the
summer months and similarly the respiratory infections
during the winter months.
 Road traffic accidents are more frequent in rainy months
and asthma in spring. These diseases take an epidemic
dimension only during specific seasons.

35. Cyclical Epidemics
 Some epidemics tend to occur in cycles which may
repeat themselves in weeks, months or years.
 Measles tends to present epidemics in a cycle of every
2-3 years. To break it, there is a need to cerate herd
immunity.
 If the herd immunity is already there in the community,
there is every likelihood that the diseases would not take
epidemic form.

36. Uses of Epidemiology
 Establishing the magnitude and distribution
of need
 Identifying high risk groups
 Health Situation Analysis/Health Status
Assessment
 Planning provision of health care services
 Evaluate the impact of current services

37. Uses of Epidemiology
 Identify factors , if they could be removed,
would prevent the disease or modify its course
 Knowing which is the most effective way of
delivering a curative or preventive measure
 Determine cost and expected effectiveness of a
proposed strategy

38. How did we identify
smoking as a cause of
lung cancer?
(How did we find a new
cause of disease?)

39. Numbers of Lung Cancer Deaths, United States, By
Year
1937
1938
1939
1940
1950
7,356
8,121
8,633
9,543
18,313

40. Cancer Death Rates By Site, U.S., 1930-1950
Males Females
Rates are per 100,000 and adjusted to the 1970 U.S.
Census Population

41. Tobacco Smoking and Lung Cancer: A Case-Control Study
Smoker
Non-smoker
597
8
Case
666
114
Control
Source: Wynder and Graham, 1950

42. Never
1-14
15-24
25+
0.07
0.57
1.39
2.27
Tobacco Smoking and Lung Cancer: British Physicians Study
Level of Smoking:
# Cigarettes/day
Annual Death Rate
(per 1,000)
Source: Doll and Hill, 1964.