This document provides an overview of descriptive epidemiology. It defines descriptive epidemiology as the study of disease occurrence and distribution. The objectives are to evaluate disease trends, provide a basis for health planning and services, and identify problems to test with analytical methods. Key procedures described include defining the population and disease, describing disease characteristics over time, place and person, measuring disease occurrence, and formulating hypotheses. Common descriptive study designs are ecological studies, case reports, case series, and cross-sectional studies. These are used to estimate disease prevalence, understand disease distributions, generate hypotheses, and plan health services.

1. DESCRIPTIVE
EPIDEMIOLOGY
Dr. SEEMA VERMA
Department of Community medicine
PGIMS Rohtak
Haryana INDIA

2. Contents
Epidemiology definition
Epidemiological study designs.
Descriptive epidemiology
Objectives of descriptive epidemiology
Procedures to be followed in descriptive
epidemiology
Descriptive epidemiological study designs

3. Epidemiology
The study of anything that happens to people
“That which befalls man”
Epi
Upon, on,
befall
Demos
People,
population,
man
Logos
the Study of

4. What is epidemiology?
 The study of
FREQUENCY, DISTRIBUTION
And DETERMINANTS
of health related states or events in specified populations
&
the application of this study to control of health problems.
-JOHN M.LAST(1988)

5. Epidemiological study designs
Descriptive
Populations
Corelational
studies /
Ecological
Individual
Case report
Case series
Cross
sectional
studies
Analytical
Case control /
Cohort
Experimental /
Interventional
RCT
Community
trial
Field trial

6. Epidemiological study designs
• Study of the occurrence and
distribution of disease
• Hypothesis is formulated
Descriptive
• Further studies to test a
hypothesis concerning the
occurrence of disease.
Analytic
• Deliberate manipulation of the
causative sequence and
comparing the outcome. Confirm
the hypothesis.
Experimental/
Interventional

7. Objectives of Descriptive
Epidemiology
 To evaluate trends in health and disease and allow
comparisons among countries and subgroup within countries.
 To provide a basis for planning, provision and evaluation of
services (for allocation of resources)
 To identify problems to be studied by analytic methods and
to test hypotheses related to those problems. {for
epidemiologist this is the first step in risk factor
determination}

8. Descriptive Epidemiology
Concerns with
 observation of the distribution of the disease or any health
related events in human populations
&
 the identification of the characteristics with which the
disease or condition under study seems to be associated.
 Describes the pattern of occurrence of disease or a condition
relative to other characteristics of the population with
respect to time, place & person

9. Steps
Defining the population to be studied.
Defining the disease under study.
Describing the disease in terms of person,
place & time.
Measurement of the disease.
Comparing with known indices.
Formulating an etiological hypothesis

10. Defining the population to be
studied
Total
population in
a geographic
area
Representative
sample taken
from that
population
DEFINED
POPULATION
 Population to be studied is defined in terms of total number
and composition of the individuals

11. Defining the population to be
studied
 The population – large enough.
 The population selected should always remain stable,
without any migration
 Community participation.
 Clear who belongs to community or not, visitors & relatives.
 Presence of health facility in close proximity to the
community.
 Importance: it forms the population at risk, which provide
the denominator for calculating the rates.

12. Defining the disease under
study
 The epidemiologist needs an
operational definition
 With which the disease or condition can be
identified & measured in the defined population
with a degree of accuracy.
 It clearly indicates the criteria by which the disease
can be measured. e.g. Tonsilitis, Measles, Dengue.

13. Describing the disease under
study

14. Time distribution

15. Short term fluctuations
Epidemic
The occurrence of cases of an illness
or other health related events in a
region or a community clearly in
excess of normal expectancy.

16. Short term fluctuations
Epidemic
Common
source
Propagated
Slow or
modern

17. Common source epidemic
Single exposure
 Aka point source epidemic
 Exposure - brief , simultaneous.
 Clustering of cases
 Examples
 Food poisoning
 Bhopal gas tragedy
 Minamata disease in Japan
Multiple exposure
 Aka continuous epidemic
 Exposure - prolonged,
continuous, repeated,
intermittent.
 Examples
 A prostitute – Gonorrhoea
 Common contaminated drinking
water source (cholera)
 Respiratory illnesses
 Legionnaire disease (USA1976)

18. Common source epidemic
Single exposure
 Epidemic curve features
 Sharp rise and fall
 No secondary waves
 Clustering in narrow interval of
time
 All cases develop within one
incubation period.
Multiple exposure
 Epidemic curve features
 No secondary waves
 Cases develop beyond one
incubation period.

19. Propagated epidemic
Person to
person
Arthropod
vector
Animal
reservoir

20. Propagated epidemic
 The epidemic usually shows a gradual rise and tails off over
a much longer period of time.
 Transmission continues
 until the number of susceptible is depleted
 or susceptible individuals are no longer exposed to infected
person or intermediary vectors.
 The speed of spread depends upon herd immunity,
opportunities for contact and secondary attack rate.

21. Periodic fluctuations
 Seasonal trends
 Cyclic trends

22. Seasonal trends
 Seasonal trend is a well-known characteristic of many
communicable diseases.
 The seasonal variations of disease occurrence may be related
to environmental conditions (e.g.
 temperature
 Humidity
 Rainfall
 Overcrowding
 life cycle of vectors etc.
which directly or
indirectly favour disease
transmission

23. Seasonal trends
For example
 Measles and varicella - early spring.
 URTI - seasonal rise during winter month.
 Bacterial GIT infections are prominent in summer.
 Non- infectious conditions like sunstroke, hay fever, snakebite also
follow seasonal trends.

24. Cyclic trends
 Cyclic trend: refers to shorter term increases and decreases in disease
occurrence over a period of years, or within a year. E.g.
 In pre vaccination era Measles appeared in cycles- 2-3 years & Rubella
every 6-9 years. This was due to naturally occurring variation in herd
immunity. A build of susceptibles is again required in the “herd” before
another attack.
 Influenza pandemics - 7-10 years, ( antigenic variation).
 Non- infectious condition - periodic fluctuation, e.g.Automobile
accidents in US are more frequent Saturdays.
 A knowledge of cyclicity of disease is useful in that it may enable
communities to defend themselves

25. Secular trends
 Changes in disease frequency that occur gradually over a
long period of time.
 Consistent change in particular direction
 Example: CHD, lung cancer and DM – consistent upward
trend in the developed countries during the past 50 years.
 While polio, diphtheria and typhoid fever – decline trend.

26. Interpretation of time trends
By surveillance or
monitoring of time
trends, epidemiologist
seeks which diseases
are
increasing/decreasing
Emerging health
problems
Effectiveness of
measures to control
older one.
Formulate etiological
hypothesis

27. Place distributions
 THE GEOGRAPHIC PATTERN OF DISEASE PROVIDE
CLUES ABOUT THE ETIOLOGY OF DISEASE.
INTERNATIONAL
VARIATIONS
NATIONAL
VARIATIONS
RURAL-URBAN
VARIATIONS
LOCAL
DISTRIBUTIONS

28. International variations
 Infectious and chronic diseases show great variation
from one country to another. E.g.
 Ca. Stomach- common in Japan, but unusual in US.
 Ca. oral cavity and uterine cervix- common in India Vs
industrialized countries.
 These differences may be attributed to:
 Climate
 Cultural factors
 Diet
 Genetics

29. National variations
 Variation in diseases occurrence may also exist within a
country.
 E.g. the distribution of endemic goiter, lathyrism, fluorosis,
leprosy, kala-azar, malaria etc.
 These differences may be attributed to:
 Climate
 Geology
 Latitude
 Environmental pollution
 Race/ ethnicity

30. Rural – Urban variations
In rural
 Skin diseases
 Zoonotic diseases
 Soil transmitted helminths inf.
 Death rate specially IMR &
MMR – higher.
In urban
 Ch. Bronchitis
 Accidents
 Lung cancers
 CVS diseases
 Mental illness
 Drug dependence
These variation may be attributed to physical activity, housing conditions,
crowding (Spread of infection), pollution, uneven distribution of medical
care, level of sanitation, education and environmental factors

31. Local distributions
 Inner and outer city variation
 Some localized differences in disease occurrence may be
attributed to:
 Carcinogenic exposure (e.g. radon)
 Geologic formations (e.g. water hardness)
 Lifestyles
 Best studied with spot map or shaded map showing high or
low frequency areas and boundaries and patterns.
 Just as John Snow did in his spot map of the Golden Square
area of London.

32. Migrant studies
Those of their
kin who have
stayed at home.
The local
population of the
host country.
Comparing the rate of occurrence of disease in migrants
with
Comparison of genetically
similar groups living under
different environmental
conditions.
• If rate of disease occurrence is
similar to adoption country
• Environmental factor
Comparison of genetically
different groups living in a
similar environment.
• If rate of disease occurrence is
similar to country of origin
• Genetic factors

33. Person distribution
• Measles, Cancer,
Atherosclerosis
Age
• Hodgkin’s disease,
leukaemia, Ca breast
Bimodality

34. Person distribution
• Sex specific morbidity and
mortality rates,
• hyperthyroidism, DM, obesity in
females
• CAD, Ca. Lung more in males.
• Variation – biological difference, s
ex linked genetic inheritance,
cultural and behavioural
difference
Gender

35. Person distribution
• Due to genetic & environmental
factors
Ethnic
group
• Silicosis (coal miners), Heart
disease (sedentary occupation)
• May alter habits (sleep, night shift,
alcohol, smoking, drug addiction
Occupation

36. Person distribution
• Mortality rates lower for married
• Ca cervix – rare in nuns
Marital
status
• Smoking & alcohol, drug abuse,
sedentary life, over eating,
• Most important risk factor in modern
day disease (CAD, Obesity, Accidents)
Behaviour

37. Measurement of disease
Done in two terms:
Mortality Morbidity
Expressed in terms
of
Incidence,
longitudinal study
Prevalence , cross
sectional study

38. Comparing with known indices
By making comparison between
different populations & subgroups of
the same population
Possible to reach a conclusion
regarding possible disease etiology .
To identify subgroups at increased
risk for certain disease.

39. Formulation of an etiological
hypothesis
Population
Specific
cause
Expected
outcome
Dose -
response
relationship
Time -
response
relationship

40. Descriptive study designs
Descriptive
Populations
Corelational
studies /
Ecological
Individual
Case report
Case series
Cross sectional
studies

41. Ecological study
 Aka Corelational study
 Unit of study –POPULATION (group of people) & not
individual.
 Relate whether a specific population with high rate of
particular disease also have high frequency of suspected
exposure?
 E.g. Avg. intake of fat in particular state (Punjab) & the
incidence of CAD in that population. Is there any association
between them? Generate hypothesis.

42. Ecological study
 E.g. Colon cancer
incidence Vs daily
meat consumption
in different
countries.
 Disadvantage –Ecological fallacy means making false
conclusion at individual level on the basis of population
derived .e.g. Biology score of class excellent.

43. Case Report
 DOCUMENTATION of detailed presentation of a single
patient, by a practitioner or clinician (physician, Surgeon,
gynec, radiologist, radiotherapist etc.)
 About NEW DISEASE or condition.
 Rare or sparsely reported condition.
 UNUSUAL/ODD PRESENTATION of a common disease.
 About NEW TREATMENT.
 Unexpected complication during treatment.
 Unexplained Outcome while treating other condition.

44. Case Report
 E.g. Short wave radiotherapy for Pneumothorax
 Eye injury in extreme weather in ultra marathon runner.
Generate hypothesis
about
Patho-physiological mechanisms

46. Case series
 Similar to case report, but relatively done on large no. of
patients.
 All patients are similar in disease pattern, symptoms or
treatment.
 Case series or report can lead to big change.
 e.g. in 1982 clustering of cases of Kaposi sarcoma and
Pneumocystis carini in homosexual gays (which were very
uncommon in those day)

47. Case series

48. Case series

49. Uses & Limitations
• Clinicians become aware of
unusual or rare clinical
presentations of the diseases.
• Such studies help to formulate
hypothesis.
Uses
• There are no comparison groups
Limitations

50. Cross-sectional studies
 Aka Prevalence studies or Snap shot studies.
 Observation of cross-section of population at single point of
time.
 Unit of observation & analysis – INDIVIDUAL.
 Collect information about disease burden – Prevalence.
 Recruitment of study participants can be whole population or
sample
 One or more outcome and one or more exposure can be
studied simultaneously

51. Cross-sectional studies
Advantages
Easy to
perform
Fairly
quick
Less
expensive
Examples
CENSUS,NFHS.
Prevalence of hypertension in a population
Prevalence of smoking in adolescents.
Prevalence of depression in elderly population
Health services utilization pattern prevalence
Prevalence of anaemia in pregnant females

52. Cross-sectional studies
Limitations
 No information about causality (etiology).
 No information about time course of variation (chicken – egg
story)(Temporal sequence).
 Not suitable to study rare diseases.
 Don’t tell about natural history of disease.
 Can’t calculate Incidence of disease.

53. Descriptive studies
Uses
Estimate prevalence of diseases and their risk
factors.
To know distribution of health problems & to plan
health care services accordingly.
Set priorities for disease control (for proper
investment of health resources)
To generate hypothesis
To check effectiveness of particular
intervention.(new drugs for malaria/TB)
To examine evolving trends of diseases

54. Evidence Hierarchy
RCT
Cohort
Case control
Cross sectional studies
Ecological
Case series
Case report

55. Take home message
 Case report and Case series are helpful to document
uncommon clinical manifestations.
 Ecological studies can be used to relate group level data & to
generate hypothesis.
 Cross sectional studies help to measure burden & magnitude
of health problem.

56. THANK YOU!!