basics of epidemiology

1. Epidemiology

2. Epidemiology
• Epi --------- upon Study of what comes
• Demos --------- people upon people
• Logos --------- study
• “Epidemiology is the study of the distribution and
determinants of health related states or events in
specified populations and the application of this study
to the control of health problems"

3. Epidemiology has 3 main aims:
1. To describe the distribution and size of disease/
health problems in human population
2. To identify aetiology and the pathogenesis of
diseases
3. To provide the data essential for:
management prevention
evaluation for control of diseases
planning of health services treatment /health problem
To fulfill these aims, different classes of
epidemiological studies are needed

4. Epidemiological Studies
Observational Interventional
(experimental)
Descriptive Analytical Individual Group
Group Individual
Ecological Case report Case Cohort RCT Field
Case series Control trials
CSS

5. Sources of Data
A- Routine statistics
1. population statistics: e.g. Age, sex, geographical, mainly used
for calculation of rate/ratio
2. Mortality statistics: e.g. Death registers
3. Morbidity statistics: e.g. notification of disease
B- Surveys
• Mortality statistics:
The simplest use is to provide Crude Death Rate (CDR)
No of Deaths in a given period
CDR = * 1000
population at risk

6. Standardization
It is a process that permits comparisons among sets that show
different compositions for factors like age and sex.
Standardization helps to avoid biases that could arise as a
result of differences in the composition of the population as
regarding to age and sex.
Standardization is aimed to calculate the standardized mortality
ratio (SMR):
SMR = observed deaths / expected deaths * 100
The expected deaths can be calculated by two methods:
1. Direct (using a standard population)
2. Indirect (using a standard ASDR)

7. Population statistics
• Morbidity statistics:
- count events and not directly identify No. of people at risk
- people entering hospital at number of times  increase statistics
patients spells
- does not, in any way, provide definite answer to a particular problem, but
only some background information.
Types:
- Hospital discharge data
- Abortion statistics
- Cancer registration
- Congenital abnormalities statistics
- Infectious diseases
- Mental health

8. Rates and ratios
No. of New cases of a disease in the population
during a specified period of time
• Incidence rate = *1000
population at risk of developing the disease
during that period of time
No. of all cases of a disease (new & old) in the
population at a specified time
• Prevalence rate = *1000
population at risk of developing the disease
at that period of time
Prevalence rate is of two types: 1- Point prevalence 2- Period prevalence

9. Limitation of hospital statistics
1. Undiagnosed cases: (ice-berg phenomenon)
2. Milder cases not reported
( treated elsewhere)
3. Catchments area not defined  Denominator is lacking rates
can not be calculated
4. Selection of patients
5. Deaths occur outside hospital

10. Epidemiological Studies
. Observational Studies –
examine associations between risk factors and outcomes
the researchers do not interfere or manipulate any of the factors under study. They
record their observations of what’s going on, and explain what they observe
with measures of associations
1. Descriptive - patterns and frequency of disease
2. Analytical - determinants and risk of disease
• Intervention Studies –
explore the association between interventions and outcomes.
researchers actually manipulate those factors they think have something to do with
causing some outcome.

11. Epidemiological Studies
Observational Interventional
(experimental)
Descriptive Analytical Individual Group
Group Individual
Ecological Case report Case Cohort RCT Field
Case series Control trials
CSS

12. Epidemiological Studies
Time
Past Present Future
A
B
C
I
A = Descriptive B = Case-control study C = Cohort study
I= Intervention study

13. Descriptive studies
• Shows prevalence of disease/condition
• Describe association with suspected risk
factors
• Generate BUT NOT assess hypothesis
• Do not have a comparison group
• Traditionally focused on person, place
&time
• Now focused on 5 Ws: Who ,Why, When,
Where &What

14. Descriptive on group
Ecologic(correlation) study
Simplest type
Information collected on group of people eg. schools, countries
Outcome-------support or not the hypothesis
May --------------show strength of association
Gives very few information about confounding factors.
Most cross sectional in nature…..Multi group studies
Some longitudinal in nature…….. Time series studies
Like CSS ….…distribution of particular outcome
Like CSS…… not suitable to test causal association.

15. Descriptive on Individual
• Case Report
• Case series
• Cross Sectional Studies(CSS)
Cross Sectional Studies(CSS)
• They yield information which is of immediate relevance to the
planning of medical services and to disease classification and
natural history.
• Sometimes  specific hypothesis e.g.
• More frequently  indicate problems that demand further
studies, e.g. variation in cancer incidence between countries
• In infectious diseases  to understand inter relationship
between environment, disease agent and human host.

16. Cross Sectional Studies(CSS)

17. Principles involves in Cross-sectional studies
1. Define aim
2. Choice of study population
3. Categorizing data to be calculated
4. Sampling
why to do sampling? Not possible in
- the only feasible way - data should be collected from total
- financial reasons population
- produce quick results - rare events
- accuracy increase in certain surveys - sampling  discrimination
- response rate may be higher - 75% sample  take 100%
Sampling should be: Random and Representative
5. Response rate

18. Advantages & disadvantages of Cross-sectional
studies
• Simple
• Quick
• Useful to quantify the health status of a population
* Because done at a point of time:
1- unable (usually) to test causal relationship
2- extremely different to test the influence(s) of aetiological
factors
3- (1 & 2) make cross-sectional study unable to test Hypotheses.

19. Problems in Cross-sectional studies
1. Importance of accurate data: the data collected should be Reliable
and Valid
Reliability: extent of agreement between repeated measurement. This
consist of the sum of variation in the item being assessed and the error
introduced by the observer collecting information.
Validity: is the extent to which a method provides a true assessment of that
which it purposed to measure.
2. Introduction of biases
3. Accuracy of subjects responses
4. Accuracy of examination findings
5. Accuracy of investigation results
6. Bias introduced by non-response

20. s
• Reasons behind conducting sampling include:
• financial.
• produce quicker results.
• getting higher response rate in some studies.
• being the only feasible way.
• Cross-sectional studies are:
• useful to quantify health status of a population.
• useful to test causal relationship..
• easy.
• quick.
• unable to estimate incidence rate.

21. Case-Control Study
• Often called Retrospective studies
• Are common first approach to test causal
hypothesis
• Have three distinct features:
1. Both exposure and outcome have occurred before the
start of the study
2. The study proceeds backwards from effect to cause; and
3. It uses a control or comparison group to support or
refute an inference.

22. Case-Control Study
Study Population
Time
DISEASED non-DISEASED
(Cases) (Controls)
exposed non-exposed exposed non-exposed

23. Selection of cases and controls
1. Selection of cases
• Case definition
• Source of cases: hospitals, outpatient clinics and general population.
2. Selection of controls
• Controls must be as similar to the cases as possible, except for the absence of
the disease under study.
• Sources of controls: hospital, relatives, neighborhood, general population.
*MATCHING

24. CASE-CONTROL STUDY
• ADVANTAGES…
– Simple to conduct
– cost/time effective
– Able to look at multiple exposure at one time
– good for studying rare diseases, and diseases with long latency
period like cancers
– can use smaller sample sizes

25. CASE-CONTROL STUDY
• DISADVANTAGES…
– Highly subjective to bias (ex: selection and recall)
– can’t calculate incidence
– Not good for rare exposures
– selecting appropriate controls can be challenging
– Clinical cases are selective survivors

26. Measuring the risk in Case-Control study
• The incidence rate among the
people exposed can’t be
calculated, so we can’t calculate
the risk directly. However an
approximation of the relative risk
can be derived which is termed
the Odds Ratio “OR”
OR = a*d / b*c
• OR=1  exposure is not related to the
disease
• OR > 1  exposure is positively related
• OR < 1 exposure is negatively related
Cases
(Diseased)
Control
(not diseased)
Exposed a b
Not
exposed c d

27. Cohort Study
• Follow up study, prospective study, longitudinal study,
incidence study.
• The term “cohort” is defined as a group of people who
share a common characteristic or experience within a
defined time period (e.g. age, occupation, exposure to a
drug or vaccine, pregnancy, etc)
• The cohort are identified prior to the appearance of the
disease under investigation
• The study proceeds forward from cause to effect

28. Cohort Study
Time Study Population
Free from the disease under study
EXPOSED not EXPOSED
disease no disease disease no disease

29. Cohort Study
• Advantages:
- Gold standard for studying the association between a risk
factor and outcome
- Useful for studying incidence, risk factors, natural history
or prognosis
- Useful for studying multiple outcomes
- Useful for looking at multiple exposures and their
interactions
- No recall bias, less likely for selection bias

30. Cohort Study
• Disadvantages:
- Expensive
- Often Long-time for follow-up
- Large sample size need
- Not good for low-incidence (rare) diseases
- Not good for chronic diseases with long latency
- Attrition – “loss to follow-up”

31. Measuring the risk in Cohort study
• As cohort study provide the data needed to
calculate the incidence rate of the disease among
exposed and among the non-exposed, so we can
calculate the Relative risk “RR” and Attributable
risk “AR”
RR= Incidence in exposed / incidence in non exposed
RR = a / a+b /c / c+d
• RR = 1 : No evidence for any association bet exposure and risk of disease
• RR > 1 : evidence of positive association and may be causal
• RR< 1 : evidence of negative association and may be causal

32. Attributable risk: the amount or proportion of disease incidence (or disease
risk) that can be attributed to a specific exposure.
AR= Incidence in exposed - incidence in non exposed
AR= a / a+b - c / c+d
Attributable Risk Percent (AR%) :
AR% = AR / incidence among exposed * 100 = AR / a/a+b * 100

33. Interventional (Experimental) Studies
• These studies involve an active attempt to change a
variable in one or more groups of people.
• Same design as a cohort study with one vital difference,
that the exposure status of the study population has been
deliberately changed by the investigator.
• We observe how this change in exposure alters the
incidence of disease or other features of the natural
history.
• They have all the advantages and disadvantages of the
usual prospective cohort studies plus the additional
problems of cost and ethics.

34. Interventional Studies
Individual..... (Randomized Controlled Trial)
(RCT)
• Group………(Field trial)

35. The Randomized Controlled Trial
(RCT)
• the ultimate study design; the "gold standard" against which all
other designs are compared.
• The subjects are usually chosen from a large number of
potential subjects using a set of inclusion and exclusion
criteria.
• an informed consent is obtained from each participant.
• Randomization is then done to allocate subjects to either the
treatment group or the placebo group.
• Once randomization is done, intervention is begun.
• After the intervention, the key outcomes that are being studied
need to be measured by and analysis involves looking for
differences in the outcome rates in the two arms of the trial.

36. CHD
CHD
CHD CHD
CHD
now
I
I
I
I
I
I
I
I
I
I
I
I
I
C
C
C
C
C
C
C
C
C
C
randomly
allocate
Control group
Intervention group
future
Intervention studies

37. • RANDOMIZATION:
- It is the heart of an RCT
- It is an attempt to eliminate “bias” and allow for comparability.
- It ensure that the investigator has no control over allocation of participants
to either study or control group thus eliminating what is known as
“selection bias”
• BLINDING:
Is done to ensure that the assessment of outcomes is done objectively away
from bias
- Single blind trial
- Double blind trial
- Triple blind trial

38. • Field trials:
- in contrast to clinical trials, involve people who are disease-free but
presumed to be at risk
- Data collection takes place in the field
- because probability of disease is small, a large number of subjects are
needed
- One of the largest field trials ever undertaken was that of the Salk vaccine
for the prevention of poliomyelitis, which involved over one million
children.

39. Validity of measurements
• Validity is the sensitivity and specificity of a test
• Sensitivity: is the ability of the test to diagnose
correctly the positives out of the total who should be
positives
• Specificity: is the ability of the test to diagnose
correctly the negative out of the total who should be
negative

40. Validity of measurements
• Sensitivity [a / (a+c)]
• Specificity [d / (b+d)]
• Predictive value of a
positive test (PPV)
[a / (a+b)]
• Predictive value of a
negative test (NPV)
[d /(c+d)]
Gold Standard
Disease
+
No disease
-
a b
c d
+ -

41. Validity of measurements
• Sensitivity
= [95 / (100)]=95%
• Specificity
= [50 / 100] = 50%
• Predictive value of a positive
test (PPV)
= [95 / 145] = 65.5%
• Predictive value of a negative
test (NPV)
= [50 /55] =91%
Typhoid Fever
Culture
+
Culture
-
95 50
5 50
+ -