Easy description on Epidemiology, risk, rate, ratio, odd ratio

1. TOPICS NAME
1. EPIDEMIOLOGY
2. Prevalence
3. Incidence
4. Risk
5. Ratio
6. Rate

2. GROUP-3
NAME ROLL
Md. Emdadul Haque ASH1708025M
Rakibul Hasan ASH1708027M
Md. Abdullah Al Mamun ASH1708029M
Shuvu Kumar Kundu ASH1708030M
Sofiul Alam ASH1708031M
Shuvro Ghosh ASH1708034M
Md. Iftekhar Uddin Ayesh ASH1708036M
Mahjerin Sumaiya BFH1708037F

3. EPIDEMIOLOGY
Epidemiology is the basic science of prevention
and social Medicine.
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.

4. Types of Epidemiology:
1.DESCRIPTIVE Epidemiology
2.ANALYTIC Epidemiology

5. DESCRIPTIVE EPIDEMIOLOGY:
It is the first step or initial enquiry into a new topic, event,
disease or condition.
Examining the distribution of a disease in a population, and
observing the basic features of its distribution in terms of
time, place, and person.
The 5W’s of descriptive epidemiology:
1. What = health issue of concern
2. Who = person
3. Where = place
4. When = time
5. Why/how = causes, risk factors, modes of transmission

6. Advantages of Descriptive Epidemiology
1. It is generally relatively quick, easy and
cheap to conduct.
2. Exposure data often only available at the
area level.
3. It is more easily examined.
4. Utilization of geographical information
systems to examine the spatial framework
of disease and exposure.

7. Disadvantages of Descriptive Epidemiology
1. Are time-consuming and costly
(especially prospective studies);
2. Can study only those risk factors
measured at the beginning of the study;
3. Can be used only for common diseases;
4. May have losses to follow-up.

8. ANALYTIC Epidemiology:
 Analytic epidemiology is concerned with the
search for causes and effects, or the why and
the how.
 Analytic epidemiology provides sufficient
evidence to take appropriate control and
prevention measures.
 Epidemiologists use analytic epidemiology to
quantify the association between exposures
and outcomes and to test hypotheses about

9. Advantages of Analytic Epidemiology
 Allows the study of several different
etiological factors(smoking, physical
activity and personality etc.)
 Risk factors can be identified.
 Rational prevention and control program
can be established.
 Suitable for investigate diseases which is
little known.

10. Disadvantages of Analytic
Epidemiology
 Change to bias.
 Expensive and time
consuming.
 Selection of an appropriate
group may be difficult.
 Possible to one or multiple
outcome.

11. Endemic describes a disease that is
present permanently in a region or
population.
e.g., chickenpox, malaria, dengue etc.
 Dengue, first appeared in the Americans and Caribbea
 Chickenpox in the UK.
 Malaria that is endemic to Africa.

12. Epidemic is an outbreak that affects many
people at one time and can spread
through one or several community.
e.g., obesity.
 Rise in obesity globally.
 Zoonotic disease(moving from animals to human).
 A genetic change (mutation) in the infectious
agent (bacteri, fungi or parasite) .

13. Pandemic is the term used
to describe an epidemic
when the spread is global.
e.g., corona virus disease.

14. Prevalence :
Prevalence is the number of new cases that have
occurred in a given time period over the number
of total people. It measures of disease burden.
Prevalence (a proportion): [(Cases of disease /
Total people) *100]

15. For example : In a population of Noakhali
1000 people where 75 people are
affected by COVID-19 disease.
So what is the prevalence of this disease
in this population?
The mathematical way to calculate this
would be:
(Cases of disease /Total people )* 100
So, 7.5% of population is affected by
COVID-19 in Noakhali

16. Incidence :
Incidence is the number of new cases that
have occurred in a given time period over
the number of people at risk in that given
time period. It measures of disease rate.
Incidence (a rate) : (New cases /people at
risk) *1000
in a given time frame

17. Let's see the example of a fictitious
population of ten women free from
disease. Four of these women develop
uterine Cancer during a given years.
So what is the incidence of this disease in
this population?
The mathematical way to calculate this
would be:
(New cases, 4,/people at risk,10, )*1000
So, incidence rate of 400 case per 1000
population per year.

18. Risk:
In epidemiology the definition of
risk is purely one of probability or
chance, as measured by the
occurrence of new cases of disease
in a defined population over a
defined period.
Risk = number of (new) observed
cases/number at risk (disease free)
at the start

19. Ratio: A ratio can be written as one number divided by
another (a
fraction) of the form a/b
 Both a and b refer to the frequency of some event
or occurrence.
A proportion is a ratio in which the numerator is a
subset (or
part) of the denominator and can be written as a/(a+b)
 A rate is a ratio of the form a*/ (a+b)
 a* = the frequency of events during a certain time

20. Example
R = number of hospitals / (population
size)
„ R may be multiplied by k = 10,000
„ Units = hospitals per 10,000 people
„ Suppose
− R = 4 hospitals/20,000 people
= 0.0002 hospitals per person
− R*k = 0.0002 * 10,000
= 2 hospitals per 10,000 people
− Units = hospitals per 10,000
people]

21. Rate:
Rate is a proportion with the
specification of time. Rate must
include the unit of time used in final
expression.
(𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑛𝑒𝑤 𝑐𝑎𝑠𝑒𝑠 𝑜𝑓 𝑑𝑖𝑠𝑒𝑎𝑠𝑒 𝑖𝑛 𝑎 𝑔𝑖𝑣𝑒𝑛 𝑡𝑖𝑚𝑒 𝑝𝑒𝑟𝑖𝑜𝑑
)/(𝑡𝑜𝑡𝑎𝑙 𝑝𝑒𝑟𝑠𝑜𝑛−𝑡𝑖𝑚𝑒 𝑎𝑡 𝑟𝑖𝑠𝑘 𝑑𝑢𝑟𝑖𝑛𝑔 𝑡ℎ𝑒 𝑓𝑜𝑙𝑙𝑜𝑤 𝑢𝑝 𝑝𝑒𝑟𝑖𝑜𝑑)
Rate =
For example, if there had been 500 new cases of an
illness in a population of 30,000 in a year, the incidence
rate would be:
500/30000×1000=16.7/1000 per year

22. Proportion:
A proportion is a specific type of ratio in
which the numerator is included in the
denominator, and the result value is
expressed as a percentage. A proportion
may be expressed as a decimal, a fraction,
or a percentage.
(𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑒𝑟𝑠𝑜𝑛𝑠 𝑜𝑟 𝑒𝑣𝑒𝑛𝑡𝑠 𝑤𝑖𝑡ℎ 𝑎 𝑝𝑎𝑟𝑡𝑖𝑐𝑢𝑙𝑎
𝑟 𝑐ℎ𝑎𝑟𝑎𝑐𝑡𝑒𝑟𝑖𝑠𝑡𝑖𝑐)/(𝑡𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑒𝑟𝑠𝑜𝑛𝑠 𝑜
𝑟 𝑒𝑣𝑒𝑛𝑡𝑠 )×(10)^n
Proportion=

23. For example, the proportion of all births
that were male is:
(𝑚𝑎𝑙𝑒 𝑏𝑖𝑟𝑡ℎ𝑠)/(𝑚𝑎𝑙𝑒 𝑏𝑖𝑟𝑡ℎ𝑠+𝑓𝑒𝑚𝑎𝑙𝑒 𝑏𝑖𝑟𝑡ℎ𝑠)
= (179×〖10〗^4)/((179+170)×〖10〗^4
)×100
=51.3%
Absolute risk:
The absolute risk of an event is the
likelihood of occurrence of that event
in the population at risk.

24. Absolute risk = (𝑝𝑒𝑟𝑠𝑜𝑛𝑠 𝑤ℎ𝑜 𝑎𝑐𝑡𝑢𝑎𝑙𝑙𝑦 𝑒𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒 𝑡ℎ
𝑒 𝑒𝑣𝑒𝑛𝑡)/(𝑡𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑝𝑒𝑟𝑠𝑜𝑛𝑠 𝑒𝑥𝑝𝑜𝑠𝑒𝑑 𝑡𝑜 𝑡ℎ𝑒 𝑟𝑖𝑠
𝑘 𝑜𝑓 𝑡ℎ𝑎𝑡 𝑒𝑣𝑒𝑛𝑡 )
For example, 100,000 women using third
generation progestin's (desogestrel,
norgestimate), 30 people developed a VTE(venous
thromboembolic event) per year. So,
Absolute risk = 30 per 100,000 women per year
(.03%)

25. RELATIVE RISK
•It is the Ratio of incidence rate of disease
in exposed individuals to the incidence
rate of disease in non-exposed individuals
(from a cohort/prospective study)

28. So, Relative risk is
=
Incidence rate of disease among those with high BP
Incidence rate of disease among those with normal BP
=
𝑎
𝑎+𝑏
÷
𝑐
𝑐+𝑑
=
90/493
70/1271
= 3.31
It means that there is a positive association because,
RR > 1.
This means that people those with high BP is 3.31
times more likely to develop disease than those with
normal BP.

29. Attributable risk:
Attributable risk is the difference in the
probability of disease in exposed people
and the probability of disease in
unexposed people.
 Attributable risk is a measure of how
much disease risk is attributed to a
certain exposure.
 Attributable risk is useful in
determining how much disease can be
prevented.
 It is useful for Public Health guidelines
and planning.

30. FORMULA FOR CONTINGENCY TABLES
Where,
a= Exposed cases
b= Exposed controls
c= Not Exposed cases
d= Not Exposed controls

31. Calculation:
Attributable Risk (AR) =
dc
c
ba
a




33. ODDS RATIO (OR)
•It is a measure of association between an exposure
and an outcome
•It compares odds of exposure in cases to odds of
exposure in controls
ODDS: It means the of event chances occurring
divided by chance of event not occurring.

36. Example: A study looking at
osteoporosis in women
compared cases with non-
cases, and found that 45/100
cases did not use calcium
supplements compared with
55/100 of the non-cases.

37. 1. Develop a table to display the
data.
2. Calculate the odds of exposure
in cases and non-cases.
3. Calculate the odds ratio using
the cross-product ratio.

39. 2. The odds of exposure in:
Cases group: a/c= 55/45 =
1.22
Controls group: b/d= 45/55 =
0.82

40. 3) The Odds Ratio:
Odds of exposure in cases
Odds of exposure in controls
1.22
0.82
=1.49
It means that the chances of osteoporosis on
women is 1.49 times more among the women
those are not used calcium supplemented.

41. Interpretation of odds ratio (OR):
1. OR of >1 indicates that the exposure is
associated with an increased risk of developing
the disease.
2. OR of <1 indicates that the exposure is
associated with the reduced risk of developing the
outcome.
3. The OR=1 exposure does not affect odds of
disease.

42. Uses of OR:
1.OR are appropriate measure of RR in case
control studies.
2.OR are commonly used in meta-analysis.
3.OR are the output of logistic regression
analysis.

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