The document discusses the fundamentals of epidemiology, its methodologies, and the comparative roles of clinicians and epidemiologists. It outlines the steps of the epidemiological approach, including descriptive, analytical, and experimental epidemiology, with case studies and examples of how to investigate health issues and interpret data. It also details various measures and data presentation techniques used in epidemiology, emphasizing the importance of analyzing health-related events within populations.

1. Epidemiological approach
Dr D Dutt
Professor

3. • John Snow (1813-1853)
• London Cholera epidemic 1854
• Broad street pump
• 32 Years before discovery of V. cholerae

4. Definition of epidemiology
Epidemiology is the study of the distribution
and determinants of health-related events or
states in population groups and the application
of this study to the control of health problems
(Last JM ed. Dictionary of Epidemiology, Oxford University Press, 1995)

5. Comparing the job of a clinician
and the job of an epidemiologist
The clinician
• Deals with patients
• Takes a history
• Conducts a physical
• Makes a diagnosis
• Proposes a treatment
• Follows up the patient
The epidemiologist
• Deals with populations
• Frames the question
• Investigates
• Draws conclusions
• Gives recommendations
• Evaluates programmes

6. Epidemiolgy
• Events do not occur due to chance
• Definition ( Quoted by Morris) : “a means of
learning or asking questions ..and getting
answers that leads to more questions.
• When- where-whom –why-how- so what?

7. Reasoning
Previous to scientific revolution (17th Century)
• Logic
• Philosophy
Scientific method
• Observation
• Measurement
• Experimentation

8. Epidemiological approach
• Hypothetical deductive reasoning
1. Theory /observation
2. Review existing information
3. Define/refine hypothesis
4. Design study
5. Collect and analyze data
6. Test hypothesis
7. Formulate conclusion

9. Epidemiological approach
• Descriptive epidemiology: Ask questions
 What is the problem?
 Who is involved? ( Person)
 Where does the problem occurs? (Place)
 When does the problem occurs? (Person)

10. • Analytical epidemiology: Compare
 Examine associations
 Attempts to analyze the causes or determinants of disease
• Intervention or experimental epidemiology:
Experiment
 Prove associations
 Clinical or community trials to answer questions about
effectiveness of control measures

11. Count, divide and compare:
The basis of epidemiology
1. Count the number of new AIDS cases in two cities
No. of new of AIDS cases
City A 58
City B 35

12. New AIDS cases
Number Year Population
City A 58 2004 25,000
City B 35 2004-5 7,000
2. Divide the number of cases by the population
City A: 58/25,000/ 1 year
City B: 35/7,000/ 2 years
Count, divide and compare:
The basis of epidemiology

13. City A: 232/100,000/ year
City B: 250/100,000/ year
3. Compare indicators
Count, divide and compare:
The basis of epidemiology

14. Agent host, environment
VECTOR
AGENT
HOST ENVIRONMENT
Biologic,
Chemical,
Physical (injury, trauma)
Social
Psychological
Genotype
Nutrition
Immunity
Behaviour
Sanitation
Weather
Pollution
Socio-Cultural
Political

15. • Related to health action

16. SENARIO I
• The EMR Dept has instructed you to
investigate a rumor of increased cases of
blindness in infants in 2 districts in Uttar
Pradesh . It is being thought that possibly it
is arsenic toxicity while in utero that has
caused the blindness. Discuss the way you
will approach the problem and investigate

17. Problem investigation
• Ascertain the problem.
• Review the literature.
• Use descriptive epidemiology (available data) for
the problem under study/ review;
 Chronology /history (Time)
 Geographic distribution (Place)
 Demographic characteristics (persons)
• Use indicators of :
 Mortality
 Morbidity (incidence, prevalence)
 Disability, etc.

18. • General a hyphothesis.
• Test the hypothesis using analytic designs:
 Cross – sectional
 Case – control
 Cohort
• Design Experiment in animals /humans if
possible
• Draw conclusions and take action

19. SENARIO II
• News paper has reported that mobile users
are at increased risk of nasopharyngeal
carcinoma quoting a study that has found 20
cases among 1023 persons using mobile
phones. Media is demanding legislation
regarding banning of mobile use. Being the
head of the Public Health Dept you are asked
to advise the government on the matter.
Outline your approach to the problem

20. Process of inference
• Assess the existence of bias or artifacts
• Review possible alternative explanations due to confounding
through indirect associations.
• Evaluate the association as to causal significance using the
criteria for judgment:
 Time sequence
 Strength
 Specificity
 Dose response
 Coherence
 Consistency

21. Process of inference
• Provide an appropriate explanation for the
association.
• Conclude and recommend

22. SENARIO III
• Several persons have died due to diarrhea
dehydration in your district. Investigate the
possibility of a cholera epidemic .

23. Approach to investigating an epidemic
• Define the problem. What is the etiologic
agent?/confirm the diagnosis. Is it an
epidemic?
• Appraise existing data. Determine the date
and hour of onset; make an epidemic curve.
Prepare a spot map of cases; consider home,
work and places of recreation and special
meetings. Where did exposure occur?
Calculate attack rates if possible.

24. • Formulate a hypothesis.
• Test the hypothesis. Search for added cases;
evaluate all of the data
• Draw conclusions and devise practical
applications. Write a report. Undertake
long-term surveillance and prevention.

25. The basic principles of
descriptive epidemiology
• Time
 When did the event happen?
• Place
 Where did the event happen?
• Person
 Who was affected?

26. 0
5
10
15
20
25
30
35
40
45
1/1/04
1/3/04
1/5/04
1/7/04
1/9/04
1/11/04
1/13/04
1/15/04
1/17/04
1/19/04
1/21/04
1/23/04
1/25/04
1/27/04
1/29/04
1/31/04
2/2/04
2/4/04
2/6/04
2/8/04
2/10/04
2/12/04
2/14/04
2/16/04
2/18/04
2/20/04
2/22/04
2/24/04
2/26/04
2/28/04
3/1/04
3/3/04
3/5/04
3/7/04
Number
of
cases
and
deaths
Cases
Deaths
Investigation
started
Strike
Cases of acute hepatitis by date of
onset, Baripada, January-March 2004
Time

27. Attack rate of acute hepatitis by zone of
residence, Baripada, Orissa, India, 2004
0 - 0.9 / 1000
1 - 9.9 / 1000
10 -19.9 / 1000
20+ / 1000
Attack rate
Underground water supply
Pump from river bed
Place

28. Attack rate of acute hepatitis by age and
sex, Baripada, Orissa, India, 2004
Cases Population Attack rate
per 1000
Age 0-4 1 1012 0.1
5-9 11 21802 2
10-14 37 74004 5
15-44 416 51358 81
45+ 73 56153 13
Sex Male 341 102683 3.3
Female 197 101646 1.9
Person

29. Uses of epidemiology
1. Examine causation
2. Study natural history
3. Description of the health status of
population (Community diagnosis)
4. Determine the relative importance of
causes of illness, disability and death
5. Planning & Evaluation of interventions
6. Identify risk factors

30. 1. Examine causation
Genetic
factors
Environmental factors
(Biological, chemical,
physical, psychological
factors)
Good health Ill health
Life style
related factors

31. 2. Study natural history
Good health Sub-clinical
disease
Clinical
disease
Recovery
Death

32. Prevalence of anemia among adolescent girls,
Mandla, MP, India 2005
Age in years
Hemoglobin <12 g%
Total
Number (%)
12-13 71 93.4 76
14-15 88 93.6 94
16-17 71 97.3 73
18-19 27 77.1 31
Total 257 93.8 274
3. Description of the health status of
population

33. Disease DALYs*
(000)
Mortality
(000)
Included in IDSP
Tuberculosis 7577 421 Yes
Measles 6471 190 Yes
Malaria 577 20 Yes
* Disability-adjusted life years
4. Determine the relative importance of
causes of illness, disability and death

34. 5. Evaluation of interventions
Good Health Ill Health
Treatment,
Medical care
Health promotion
Preventive measures
Public health services

35. 6. Identify those sections of the
population which have the greatest risk
from specific causes of ill health
Characteristics
Univariate
odds ratio
(95% CI)
Adjusted odds
ratio
(95% CI)
Hookworm infestation 12 (5-29) 10 (4-24)
Consumption of IFA < 90 days 4.1 (2-8) 2.7 (1-7)
Education below middle school * 4 (3-7) 2.3 (1-4)
Number of pregnancy > 2 3.6 (2-6) 1.9 (1-4)
* Middle school = Seventh class in Orissa
Factors associated with
anemia among pregnant women, Orissa, 2004

36. = 5 / 2 = 2.5/1
A ratio places in relation two quantities
that may be unrelated
• The quotient of two numbers
• Numerator NOT necessarily INCLUDED in the
denominator
• Allows to compare quantities of different
nature

37. Examples of ratio
• Number of beds per doctor
 85 beds for 1 doctor
• Number of participants per facilitator
• Sex ratio:
 Male / Female

38. 2 / 4 = 0.5=50%
A proportion measures a
subset of a total quantity
• The quotient of two numbers
• Numerator NECESSARILY INCLUDED
in the denominator
• Quantities have to be of the same nature
• Proportion always ranges between 0 and 1
• Percentage = proportion x 100

39. Example of proportion
• Tuberculosis cases in a district:
 400 male cases
 200 female cases
• Question
 What is the proportion of male cases among all
cases?
 What is the proportion of female cases among all
cases?

40. A rate measures the speed of occurrence
of health events
• The quotient of two numbers
• Defined duration of observation
• Numerator
 Number of EVENTS observed for a given time
• Denominator (includes time)
 Population at risk in which the events occur
2
----- = 0.02 / year
100
Observed in 2004

41. Example of rate
• Mortality rate of tetanus in country X in 1995
 Tetanus deaths: 17
 Population in 1995: 58 million
 Mortality rate = 0.029/100,000/year
• Rate may be expressed in any power of 10
 100, 1,000, 10,00, 100,000

42. Measures of disease frequency
• Prevalence
 Number of cases of a disease in a defined
population at specified point of time
• Incidence
 Number of new cases, episodes or events occurring
over a defined period of time

43. Prevalence
Number of people with
the disease or condition
at a specified time
Total population at risk
X Factor
P =

44. Incidence rate
Number of people who get
the disease or condition
in a specified time
Total population at risk
X Factor
I =

45. Case fatality ratio
• Divide
 Number of deaths
 Number of cases
• Example: Measles outbreak
 3 deaths
 145 cases
 Case fatality ratio: 2.1%

46. BASIC EPIDEMIOLOGY
MR. S. Hazra
Deptt. of Epidemiology
AIIH & PH
Kolkata

47. Presenting health information
• Tables
• Graphs
 Histograms
 Line diagrams
 Bar chart
 Pie chart
 Scatter plot
 Map

48. Tables
• Data presented in columns and rows by one
or more classification variable
• Title- Concise, self explanatory explaining
clearly all information being presented
• Rows and columns should be clearly labeled
• Categories should be clearly shown

49. Age distribution of a sample of
100 villagers
Example of one way table:
Data tabulated by one variable
Age group (years) Number
0-4 19
5-14 25
15-44 40
45+ 16
Total 100

50. Example of two way table:
Data tabulated by two variable
Age group (years) Male Female Number
0-4 10 9 19
5-14 12 13 25
15-44 20 20 40
45+ 7 9 16
Total 49 51 100
Age and sex distribution of a sample of 100 villagers

51. Graphs
• Charts based on length
• Bar charts (horizontal, vertical, grouped, stacked)
• Charts based on proportion
• Pie chart
• Geographic co-ordinate charts (maps)
• Spot map
• Area map

52. Malaria in Kurseong block, Darjeeling
District, West Bengal, India, 2000-2004
0
5
10
15
20
25
30
35
40
45
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
2000 2001 2002 2003 2004
Months
Incidence
of
malaria
per
10,000
Incidence of malaria
Incidence of Pf malaria
Line graph for time series

53. Histogram to display a frequency
distribution
• Graphic representation of the frequency distribution
of a continuous variable
• Rectangles drawn in such a way that their bases lie
on a linear scale representing different intervals
• Areas are proportional to the frequencies of the
values within each of the intervals
• No spaces between columns
• No scale breaks
• Equal class intervals
• Epidemic curve is an example of histogram with
time on the x axis

54. 0
20
40
60
80
0-19.9 20-49.9 50-99.9 100-300 > 300
Urinary Iodine Excretion levels (µg/L)
Percentage
Histogram
Urinary iodine excretion status, 24 N
Parganas, West Bengal, India, 2004

55. Acute hepatitis by week of onset in 3
villages, Bhimtal block, Uttaranchal, India,
July 2005
0
10
20
30
40
50
60
70
80
90
1st
week
2nd
week
3rd
week
4th
week
1st
week
2nd
week
3rd
week
4th
week
1st
week
2nd
week
3rd
week
4th
week
1st
week
2nd
week
3rd
week
4th
week
1st
week
May June July August September
Week of onset
Number
of
cases
Epidemic curve

56. Proportions of a total presenting
selected characteristics
• Breakdown of a total in proportions:
 Pie chart
• Breakdown of more than one total into
proportion:
 Juxtaposed bar charts cumulated to 100%

57. Road
10%
Fall
32%
Bites
16%
Burns
7%
Minor injuries
35%
Types of unintentional injuries,
Tiruchirappalli, Tamil Nadu, India, 2003
Incidence:
9.6 per 100 person-month
(95% C.I. 8-11
Pie chart for the breakdown of a total in proportions

58. Estimated and projected proportion of
deaths due to non-communicable
diseases, India, 1990-2010
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1990 2000 2010
Year
Proportion
(%)
Injuries
Communicable
diseases
Non communicable
diseases
Cumulated bar chart for the breakdown
of many totals in proportions

59. Comparing proportions across groups
• No logical order: Horizontal bar chart
 Sort according to decreasing proportions
• Logical order: Vertical bar chart
 Not a continuous variable: Do not display axis
 Continuous variable: Display axis

60. Causes of non vaccination as reported by the
mothers, Bubaneshwar, Orissa, India, 2003
0% 20% 40% 60% 80% 100%
Lack of money
Lack of facility
Lack of time
Lack of motivation
Irregularity by health staff
Child sick
Lack of awareness
India FETP
Horizontal bar chart

61. 0
10
20
30
40
50
60
70
30-39 40-49 50-59 60-69 70 +
Age group (years)
%
Male
Female
Prevalence of hypertension by age and
sex, Aizawl, Mizoram, India, 2003
Vertical bar chart

62. Cholera cases by residence, Kanchrapara,
N-24 Parganas, West Bengal, India, 2004
Spot map

63. 20-49
50-99
100+
1-19
0
Attack rate per
100,000
population
Pipeline crossing
open sewage drain
Open drain
Incidence of acute hepatitis by block,
Hyderabad, AP, India, March-June 2005
Hypothesis generated:
Blocks with hepatitis are those
supplied by pipelines crossing
open sewage drains
Incidence by area