Samenvatting
EPIDEMIOLOGY &
PUBLIC HEALTH
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Chapter 1: introduction to epidemiology and public health
Chapter 2: measures of occurrence
Chapter 3: measures of assocation and random error
Chapter 4: causality and systematic error
Chapter 5: ethics
Chapter 6: diagnostic testing
Chapter 7: study design – cohorts – case-control
Chapter 8: clinical trials
Chapter 9: molecular epidemiology
Chapter 10-11: genomic epidemiology in Africa
1
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Chapter 1: introduction to epidemiology & public health
1. Epidemiology and public health
Definitions
• Epi = “upon”
• Demos = “people”
• Logos = “study”
"Epidemiology is a method of reasoning about disease that deals with biological inference derived from observations of
disease phenomena in population groups." (David E. Lilienfeld, 1978)
A systematic review identified 102 definitions between 1978-2017, with 93 related to human health and 9 to veterinary
health. (Frérot et al., 2018)
"Often considered the core science of public health, epidemiology involves 'the study of the distribution and determinants
of disease frequency'," or more simply, "the study of the occurrence of illness." (K. Rothman, 2012)
Scientific research
To fill knowledge gaps and improve society. Epidemiologic research specifically aims to improve public health
Epidemiological research
• Main Strength: Assessing disease burden & relationship (association) between exposure and disease in a
population.
• Method: Counting within groups and comparing.
• Challenges: Defining who to count, when to count, and how to compare.
Key Questions in Epidemiological Research:
1. What is the burden of disease?
2. What is the prognosis of a disease?
3. What are the risk factors/exposures causing a disease?
Types of Epidemiology:
1. Descriptive Epidemiology: Non-causal analyses describing observed data (e.g., surveillance). Crucial for
developing analytic epidemiology. 31
2. Predictive (Prognosis) Epidemiology: Using observed data to make predictions (e.g., in clinical epidemiology).
3. Causal (Etiologic) Epidemiology: Investigating the causal effects of risk factors/exposures on disease.
Surveillance:
The ongoing, systematic collection, analysis, and interpretation of health-related data, essential for planning,
implementation, and evaluation of public health practice. It includes timely dissemination of data to those responsible for
prevention and control.
2
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Exposure-oriented epidemiology Outcome-oriented epidemiology
Environmental epidemiology Infectious disease epidemiology
Occupational epidemiology Cancer epidemiology
Pharmacoepidemiology Mental health epidemiology
Nutritional epidemiology Neurologic diseases epidemiology
Genetic epidemiology Reproductive epidemiology
Molecular epidemiology Respiratory disease epidemiology
Social epidemiology Dental epidemiology
Clinical epidemiology
Chronic disease epidemiology
What is public health?
Definitions:
"The art and science of preventing disease, prolonging life and promoting health through the organized efforts of society."
"The community effort to protect, maintain, and improve the health of a population by organized means, including
preventive programs, hygiene, education, and other interventions." (Rothman, 2012)
Role of Public Health:
• Establish health objectives and priorities.
• Health promotion.
• Disease prevention.
• Health protection.
• Health services.
Public Health Approach: Surveillance → Risk Factor
Identification → Intervention → Evaluation → Implementation
Purposes of Epidemiology in Public Health Practice:
• Discover agent, host, and environmental factors affecting health.
• Determine the relative importance of causes of illness, disability, and death.
• Identify population segments at highest risk for specific health problems.
• Evaluate the effectiveness of health programs and services.
What is public health?
1. Surveillance: continu verzamelen van gegevens om prioriteiten en doelen te stellen
2. Health services: plannen & beoordelen van de zorg → kwaliteit van diensten en effectiviteit van diagnosetesten
evalueren
3. Disease prevention:
• Primary: voorkomen dat ziekte ontstaat (bv. vaccinatie)
• Secundary: vroege opsporing via screening (bv. bevolkingsonderzoek)
• Tertiary: beperken v/d schade bij bestaande ziekte (bv. revalidatie)
3
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
4. Health promotion: mensen helpen de controle over hun eigen gezondheid te vergroten (bv. gezonde steden,
gezondheidsvaardigheden)
5. Health protection: blootstelling aan gevaren
minimaliseren (bv. voedselveiligheid,
milieubescherming)
Epidemiology = multidisciplinary field!
2. History
Pioneers of epidemiology and publich health
• Hippocrates (460-377 BC): shifted focus from supernatural to environmental factors (airs, waters, places)
through observation and reason
• Avicenna (980-1037): used quantification and empirical evidence; proposed diseases spread via contagion1 and
advocated for quarantine
• Fracastoro (1497-1553): Proposed "seminaria" (seeds) as the cause of contagion; identified transmission via
direct/indirect contact and air/water
• John Graunt (1620-1674): First epidemiologist/demographer; analyzed "Bills of Mortality" to study population
dynamics and disease trends
• Bernardino Ramazzini (1633-1714): Pioneer of occupational medicine, identifying health risks in various trades
• William Farr (1807-1883): Systematized data collection (General Register Office) and linked occupations to
mortality
• John Snow (1813-1858): Founding father; proved cholera was water-borne (London 1854) and pioneered study
design
• Ignaz Semmelweis (1818-1865): Discovered that handwashing drastically reduced maternal mortality from
puerperal fever
• Florence Nightingale (1820-1910): Used data visualization to show that poor hygiene/nutrition caused more
soldier deaths than battle wounds
• Janet Lane-Claypon (1877-1967): Conducted first cohort and modern case-control studies (breast cancer);
identified recall bias
• Wade Hampton Frost (1880-1938): First Professor of Epidemiology (Johns Hopkins); studied yellow fever
outbreaks
1
the communication of disease from one person or organism to another by close contact.
4
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Chapter 2: measures of occurrence
Epidemiology is defined as a method of reasoning about disease that involves biological inference derived from
observations of disease phenomena in population groups. It is often considered the core science of public health.
Epidemiology involves the study of the distribution and determinants of disease frequency. More simply, it can be
described as "the study of the occurrence of illness"
1. Concepts
The epidemiologic fraction
!
Fraction = ratio " → we use 3 types of fractions to measure occurrence:
! !
1. Proportion: # = !$"
With: - N = population
! ! - x = people with a characteristic
2. Odds: #&! = "
- y = N-x (people without a characteristic)
!
3. Rate: # ∗ ( =
' !
- t = time
(!$")∗(
Proportion: represents the fraction of a population that has a specific characteristic or experiences an event
Odds: represent the ratio of the number of individuals with an event to the number of individuals without the event
Rate: measures the frequency of an event in a population over a specific period, taking into account the total person-time
at risk.
Cohort
= a group of people typically followed through time.
Closed cohort Open cohort
A cohort where all individuals A cohort that may include
begin observation at the same new individuals over time.
point in time. No new The population size can
individuals are added after the fluctuate during the follow-
start up period.
Prevalence and incidence
• Prevalence: Describes the proportion of a population with an existing disease or exposure at a specific point in
time or over a period.
o It combines incidence and duration of the factor
• Incidence: Measures the number of new disease events (cases) in a population over a defined period.
o It focuses on the occurrence of new cases
5
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
2. Measures of occurrence
Prevalence
Prevalence measures the proportion of a population with an existing disease or exposure. It can be measured at a single
point in time or over a perio
Time and prevalence
Point prevalence Period prevalence
Measures the proportion of cases at a specific Measures the proportion of cases over a defined, longer period
point in time or over a very short period (e.g., (e.g., month, year) 28 30. It's crucial to always mention the time period
minutes, days) when reporting prevalence unless it's clear from context
Different types of prevalence
• Prevalence Counts: The absolute number (𝑛) of existing cases in a population. This is simple but often lacks
context without a denominator.
• Prevalence Proportion: The proportion of the population with the disease or exposure.
, -./0/
o 𝑝𝑟𝑒𝑣𝑎𝑙𝑒𝑛𝑐𝑒 𝑝𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛 = (1(.2 31342.5(1,
6
o Example: For diabetes mellitus in a population of 100, with 5 cases: 𝑝𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛 = '77 = 0,05 = 5%
• Prevelance odds: The odds of having the disease or exposure compared to not having it.
, -./0/ , -./0/
o 𝑃𝑟𝑒𝑣𝑎𝑙𝑒𝑛𝑐𝑒 𝑜𝑑𝑑𝑠 = 31342.(51,&, -./0/ = , ,1,&-./0/
o Example: For ADHD diagnosis where 70 out of 100 children screened high and were diagnosed: 𝑜𝑑𝑑𝑠 =
87 87
= 97 = 2,3 or 7: 3
'77&87
Acute event like the flu (lasts ± a week) Chronic disease: prevalence counts of diabetic
patients (lasts longer)
Prevalence proportion vs. prevalence odds
• When the prevalence proportion is low (typically < 10%), the prevalence proportion and prevalence odds are very
close in value
• When the prevalence proportion is high, the prevalence odds will overestimate the prevalence proportion 55.
o Example:
§ Diabetes (low prevalence): Proportion = 0.05, Odds = 0.053
§ ADHD (higher prevalence): Proportion = 0.70 (70/100), Odds = 2.3 (70/30)
6
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Prevalence summary
• Prevalence Proportion: Generally, when the term "prevalence" is used without qualification, it refers to the
prevalence proportion.
• Prevalence Count: Useful but needs context (denominator) for comparison
• Prevalence Odds: Less useful than proportion for general interpretation but used in measures of association (like
Odds Ratio)
Summary: pros vs. cons
Pros Cons
Counts - Easy to understand - You cannot compare two counts
- Communicates public health unless the denominator is the
importance same
- Needs context (denominator)
Proportions - Easy to understand Interpretation is conditional on
- Communicates public health recurrent outcomes; Does not
importance account for variable follow-up
lengths
Odds - Use in measures of - Not easy to interpret
association (OR) - Can overstate the proportion if
- Similar to the proportion the outcome is common
when the outcome is rare
Incidence: counts, proportions, odds, rates
Incidence measures how many new cases of a disease arise over a specified period of time within a population at risk.
Individuals already having the factor at the start (𝑡7 ) are excluded from the population at risk.
Different types of incidences
1. Incidence Counts: The number of new cases during a fixed period
o Example: 3.9 million new cancer cases in Europe in 2018 means none were diagnosed earlier. Requires
area context for risk assessment
2. Incidence Proportion (Risk or Cumulative Incidence): The proportion of the population at risk who develop the
disease during a specified period.
,0: -./0/ ;4<5,= . >5!0; 30<51;
o 𝑖𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑝𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛 =
31342.(51, .( <5/? ;4<5,= >5!0; 30<51;
o Interpretation: Represents the probability (risk) of developing the disease over the specified time
@
o Example: If 10 people are at risk and 6 develop the disease over 10 years: 𝑟𝑖𝑠𝑘 = '7 = 0,6 = 60%, this is
the 10-year risk of becoming a case
o Challenges:
a) Loss to follow-up: Participants dropping out can bias results if those lost differ systematically.
Example: Antimalarial treatment study where participants traveling to forests miss diagnoses.
7
,EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
b) Competing risks: Outcomes that prevent the study outcome (e.g., death from stroke preventing
cancer recurrence).
Example: In a 5-year dementia study, deaths unrelated to dementia must be accounted for,
otherwise dementia risk may be overestimated.
c) Recurrent outcomes: Diseases like the flu that can occur multiple times pose challenges for
simple incidence proportion calculations.
d) Time: Variable lengths of follow-up can
complicate interpretation
3. Incidence odds: The odds of developing the disease compared to not developing it within the period.
5,-5;0,-0 3<131<(51,
o 𝑖𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑜𝑑𝑑𝑠 = '&5,-5;0,-0 3<131<(51,
o Example: Using the survival curve data, the risk of death at age 40 was 0.07 (7%): 𝑖𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑜𝑑𝑑𝑠 =
7,78 7,78
'&7,78
= 7,B9 = 0,075 or 7: 93
o Comparison to Risk: Similar to prevalence odds, incidence odds are close to risk when the risk is low
(<10%) but overestimate risk when it's high.
4. Incidence rate (or incidence density): Measures the rate at which new cases occur in relation to the total person-
time at risk.
,0: -./0/ ;4<5,= >5!0; 30<51;
o 𝐼𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑟𝑎𝑡𝑒 = 30</1,&(5C0 .( <5/? ;4<5,= >5!0; 30<51;
o Person-time: The sum of the time intervals each individual was
observed while at risk of the outcome 88. Example: 10 people followed
for 2 months = 10 ∗ 2 = 20 𝑝𝑒𝑟𝑠𝑜𝑛 − 𝑚𝑜𝑛𝑡ℎ𝑠
o Interpretation: Expressed as events per person-time (e.g., cases per
person-year). This measure accounts for variable follow-up times and is useful for comparing populations
with different follow-up durations.
o Example: Lung cancer metastasis study: 100 patients, 60 developed metastasis by 2008. 30 developed it
after 5 years, 30 after 10 years.
@7
§ 10-year risk: '77 = 0,6 = 60%
§ Incidence Rate: Assuming no loss to follow-up, person-time is calculated considering
when each case occurred: 𝑝𝑒𝑟𝑠𝑜𝑛𝑡𝑖𝑚𝑒 = (30 𝑝𝑎𝑡𝑖𝑒𝑛𝑡𝑠 ∗ 5𝑦) + (30 𝑝𝑎𝑡𝑖𝑒𝑛𝑡𝑠 ∗ 10𝑦) +
(40 𝑝𝑎𝑡𝑖𝑒𝑛𝑡𝑠 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑚𝑒𝑡𝑎𝑠𝑡𝑎𝑠𝑖𝑠 ∗ 10𝑦) = 850 person-years
@7 -./0/
𝐼𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑟𝑎𝑡𝑒 = = 0,071 cases per person-year
D67
o Time Units: Consistency in time units (days, months, years) is crucial.. Conventions within a field should
be followed, or units chosen based on the condition studied (e.g., hospital-days for infections)
8
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
o Person-time Issues: Concepts like "pack-years" for
smoking illustrate cumulative exposure over time,
analogous to person-time.
Measure What is measured units range Synonyms
Counts Number of new cases Count 0 to infinity /
Proportions Averige probability of new None (snapshot of 0 to 1 Cumulative incidence
(risk) disease occurrence time)
Rate Average rate of new disease Inverse time 0 to inifinity Incidence density,
occurrence (events/person-time) person-time rate
Odds Ratio of events to non-events / 0 to infinity /
Summary: pros vs. cons
Pros Cons
Counts - Easy to understand - You cannot compare two counts unless the
- Communicates public health denominator is the same
importance - Needs context (denominator)
Proportions - Easy to understand - Interpretation conditional for recurrent
- Communicates public health outcomes
importance - Does not account for variable lengths of
follow-up between individuals
- Loses information compared to the survival
curve
Rate - Use all information available - Not easy to interpret
- Allows comparison of occurrence - Person time-units: interchangeable?
between populations or studies
with different follow-up periods
Odds - Use in measures of association (OR) - Not easy to interpret
- Similar to the risk when the - Can overstate the risk if the outcome is
outcome is rare common
3. Relationship between measures of occurrence
Incidence and prevalence
• Prevalence measures are similar to incidence measures when the duration of the disease is short 120.
• Incidence measures are better for quantifying occurrence when the duration of the disease is long 120.
• Prevalence combines incidence and duration of the disease 37 120.
• If the prevalence is low (<10%), prevalence odds and incidence odds are close
9
EPIDEMIOLOGY &
PUBLIC HEALTH
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Chapter 1: introduction to epidemiology and public health
Chapter 2: measures of occurrence
Chapter 3: measures of assocation and random error
Chapter 4: causality and systematic error
Chapter 5: ethics
Chapter 6: diagnostic testing
Chapter 7: study design – cohorts – case-control
Chapter 8: clinical trials
Chapter 9: molecular epidemiology
Chapter 10-11: genomic epidemiology in Africa
1
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Chapter 1: introduction to epidemiology & public health
1. Epidemiology and public health
Definitions
• Epi = “upon”
• Demos = “people”
• Logos = “study”
"Epidemiology is a method of reasoning about disease that deals with biological inference derived from observations of
disease phenomena in population groups." (David E. Lilienfeld, 1978)
A systematic review identified 102 definitions between 1978-2017, with 93 related to human health and 9 to veterinary
health. (Frérot et al., 2018)
"Often considered the core science of public health, epidemiology involves 'the study of the distribution and determinants
of disease frequency'," or more simply, "the study of the occurrence of illness." (K. Rothman, 2012)
Scientific research
To fill knowledge gaps and improve society. Epidemiologic research specifically aims to improve public health
Epidemiological research
• Main Strength: Assessing disease burden & relationship (association) between exposure and disease in a
population.
• Method: Counting within groups and comparing.
• Challenges: Defining who to count, when to count, and how to compare.
Key Questions in Epidemiological Research:
1. What is the burden of disease?
2. What is the prognosis of a disease?
3. What are the risk factors/exposures causing a disease?
Types of Epidemiology:
1. Descriptive Epidemiology: Non-causal analyses describing observed data (e.g., surveillance). Crucial for
developing analytic epidemiology. 31
2. Predictive (Prognosis) Epidemiology: Using observed data to make predictions (e.g., in clinical epidemiology).
3. Causal (Etiologic) Epidemiology: Investigating the causal effects of risk factors/exposures on disease.
Surveillance:
The ongoing, systematic collection, analysis, and interpretation of health-related data, essential for planning,
implementation, and evaluation of public health practice. It includes timely dissemination of data to those responsible for
prevention and control.
2
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Exposure-oriented epidemiology Outcome-oriented epidemiology
Environmental epidemiology Infectious disease epidemiology
Occupational epidemiology Cancer epidemiology
Pharmacoepidemiology Mental health epidemiology
Nutritional epidemiology Neurologic diseases epidemiology
Genetic epidemiology Reproductive epidemiology
Molecular epidemiology Respiratory disease epidemiology
Social epidemiology Dental epidemiology
Clinical epidemiology
Chronic disease epidemiology
What is public health?
Definitions:
"The art and science of preventing disease, prolonging life and promoting health through the organized efforts of society."
"The community effort to protect, maintain, and improve the health of a population by organized means, including
preventive programs, hygiene, education, and other interventions." (Rothman, 2012)
Role of Public Health:
• Establish health objectives and priorities.
• Health promotion.
• Disease prevention.
• Health protection.
• Health services.
Public Health Approach: Surveillance → Risk Factor
Identification → Intervention → Evaluation → Implementation
Purposes of Epidemiology in Public Health Practice:
• Discover agent, host, and environmental factors affecting health.
• Determine the relative importance of causes of illness, disability, and death.
• Identify population segments at highest risk for specific health problems.
• Evaluate the effectiveness of health programs and services.
What is public health?
1. Surveillance: continu verzamelen van gegevens om prioriteiten en doelen te stellen
2. Health services: plannen & beoordelen van de zorg → kwaliteit van diensten en effectiviteit van diagnosetesten
evalueren
3. Disease prevention:
• Primary: voorkomen dat ziekte ontstaat (bv. vaccinatie)
• Secundary: vroege opsporing via screening (bv. bevolkingsonderzoek)
• Tertiary: beperken v/d schade bij bestaande ziekte (bv. revalidatie)
3
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
4. Health promotion: mensen helpen de controle over hun eigen gezondheid te vergroten (bv. gezonde steden,
gezondheidsvaardigheden)
5. Health protection: blootstelling aan gevaren
minimaliseren (bv. voedselveiligheid,
milieubescherming)
Epidemiology = multidisciplinary field!
2. History
Pioneers of epidemiology and publich health
• Hippocrates (460-377 BC): shifted focus from supernatural to environmental factors (airs, waters, places)
through observation and reason
• Avicenna (980-1037): used quantification and empirical evidence; proposed diseases spread via contagion1 and
advocated for quarantine
• Fracastoro (1497-1553): Proposed "seminaria" (seeds) as the cause of contagion; identified transmission via
direct/indirect contact and air/water
• John Graunt (1620-1674): First epidemiologist/demographer; analyzed "Bills of Mortality" to study population
dynamics and disease trends
• Bernardino Ramazzini (1633-1714): Pioneer of occupational medicine, identifying health risks in various trades
• William Farr (1807-1883): Systematized data collection (General Register Office) and linked occupations to
mortality
• John Snow (1813-1858): Founding father; proved cholera was water-borne (London 1854) and pioneered study
design
• Ignaz Semmelweis (1818-1865): Discovered that handwashing drastically reduced maternal mortality from
puerperal fever
• Florence Nightingale (1820-1910): Used data visualization to show that poor hygiene/nutrition caused more
soldier deaths than battle wounds
• Janet Lane-Claypon (1877-1967): Conducted first cohort and modern case-control studies (breast cancer);
identified recall bias
• Wade Hampton Frost (1880-1938): First Professor of Epidemiology (Johns Hopkins); studied yellow fever
outbreaks
1
the communication of disease from one person or organism to another by close contact.
4
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Chapter 2: measures of occurrence
Epidemiology is defined as a method of reasoning about disease that involves biological inference derived from
observations of disease phenomena in population groups. It is often considered the core science of public health.
Epidemiology involves the study of the distribution and determinants of disease frequency. More simply, it can be
described as "the study of the occurrence of illness"
1. Concepts
The epidemiologic fraction
!
Fraction = ratio " → we use 3 types of fractions to measure occurrence:
! !
1. Proportion: # = !$"
With: - N = population
! ! - x = people with a characteristic
2. Odds: #&! = "
- y = N-x (people without a characteristic)
!
3. Rate: # ∗ ( =
' !
- t = time
(!$")∗(
Proportion: represents the fraction of a population that has a specific characteristic or experiences an event
Odds: represent the ratio of the number of individuals with an event to the number of individuals without the event
Rate: measures the frequency of an event in a population over a specific period, taking into account the total person-time
at risk.
Cohort
= a group of people typically followed through time.
Closed cohort Open cohort
A cohort where all individuals A cohort that may include
begin observation at the same new individuals over time.
point in time. No new The population size can
individuals are added after the fluctuate during the follow-
start up period.
Prevalence and incidence
• Prevalence: Describes the proportion of a population with an existing disease or exposure at a specific point in
time or over a period.
o It combines incidence and duration of the factor
• Incidence: Measures the number of new disease events (cases) in a population over a defined period.
o It focuses on the occurrence of new cases
5
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
2. Measures of occurrence
Prevalence
Prevalence measures the proportion of a population with an existing disease or exposure. It can be measured at a single
point in time or over a perio
Time and prevalence
Point prevalence Period prevalence
Measures the proportion of cases at a specific Measures the proportion of cases over a defined, longer period
point in time or over a very short period (e.g., (e.g., month, year) 28 30. It's crucial to always mention the time period
minutes, days) when reporting prevalence unless it's clear from context
Different types of prevalence
• Prevalence Counts: The absolute number (𝑛) of existing cases in a population. This is simple but often lacks
context without a denominator.
• Prevalence Proportion: The proportion of the population with the disease or exposure.
, -./0/
o 𝑝𝑟𝑒𝑣𝑎𝑙𝑒𝑛𝑐𝑒 𝑝𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛 = (1(.2 31342.5(1,
6
o Example: For diabetes mellitus in a population of 100, with 5 cases: 𝑝𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛 = '77 = 0,05 = 5%
• Prevelance odds: The odds of having the disease or exposure compared to not having it.
, -./0/ , -./0/
o 𝑃𝑟𝑒𝑣𝑎𝑙𝑒𝑛𝑐𝑒 𝑜𝑑𝑑𝑠 = 31342.(51,&, -./0/ = , ,1,&-./0/
o Example: For ADHD diagnosis where 70 out of 100 children screened high and were diagnosed: 𝑜𝑑𝑑𝑠 =
87 87
= 97 = 2,3 or 7: 3
'77&87
Acute event like the flu (lasts ± a week) Chronic disease: prevalence counts of diabetic
patients (lasts longer)
Prevalence proportion vs. prevalence odds
• When the prevalence proportion is low (typically < 10%), the prevalence proportion and prevalence odds are very
close in value
• When the prevalence proportion is high, the prevalence odds will overestimate the prevalence proportion 55.
o Example:
§ Diabetes (low prevalence): Proportion = 0.05, Odds = 0.053
§ ADHD (higher prevalence): Proportion = 0.70 (70/100), Odds = 2.3 (70/30)
6
, EPIDEMIOLOGY & PUBLIC HEALTH 2025-2026
Prevalence summary
• Prevalence Proportion: Generally, when the term "prevalence" is used without qualification, it refers to the
prevalence proportion.
• Prevalence Count: Useful but needs context (denominator) for comparison
• Prevalence Odds: Less useful than proportion for general interpretation but used in measures of association (like
Odds Ratio)
Summary: pros vs. cons
Pros Cons
Counts - Easy to understand - You cannot compare two counts
- Communicates public health unless the denominator is the
importance same
- Needs context (denominator)
Proportions - Easy to understand Interpretation is conditional on
- Communicates public health recurrent outcomes; Does not
importance account for variable follow-up
lengths
Odds - Use in measures of - Not easy to interpret
association (OR) - Can overstate the proportion if
- Similar to the proportion the outcome is common
when the outcome is rare
Incidence: counts, proportions, odds, rates
Incidence measures how many new cases of a disease arise over a specified period of time within a population at risk.
Individuals already having the factor at the start (𝑡7 ) are excluded from the population at risk.
Different types of incidences
1. Incidence Counts: The number of new cases during a fixed period
o Example: 3.9 million new cancer cases in Europe in 2018 means none were diagnosed earlier. Requires
area context for risk assessment
2. Incidence Proportion (Risk or Cumulative Incidence): The proportion of the population at risk who develop the
disease during a specified period.
,0: -./0/ ;4<5,= . >5!0; 30<51;
o 𝑖𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑝𝑟𝑜𝑝𝑜𝑟𝑡𝑖𝑜𝑛 =
31342.(51, .( <5/? ;4<5,= >5!0; 30<51;
o Interpretation: Represents the probability (risk) of developing the disease over the specified time
@
o Example: If 10 people are at risk and 6 develop the disease over 10 years: 𝑟𝑖𝑠𝑘 = '7 = 0,6 = 60%, this is
the 10-year risk of becoming a case
o Challenges:
a) Loss to follow-up: Participants dropping out can bias results if those lost differ systematically.
Example: Antimalarial treatment study where participants traveling to forests miss diagnoses.
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b) Competing risks: Outcomes that prevent the study outcome (e.g., death from stroke preventing
cancer recurrence).
Example: In a 5-year dementia study, deaths unrelated to dementia must be accounted for,
otherwise dementia risk may be overestimated.
c) Recurrent outcomes: Diseases like the flu that can occur multiple times pose challenges for
simple incidence proportion calculations.
d) Time: Variable lengths of follow-up can
complicate interpretation
3. Incidence odds: The odds of developing the disease compared to not developing it within the period.
5,-5;0,-0 3<131<(51,
o 𝑖𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑜𝑑𝑑𝑠 = '&5,-5;0,-0 3<131<(51,
o Example: Using the survival curve data, the risk of death at age 40 was 0.07 (7%): 𝑖𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑜𝑑𝑑𝑠 =
7,78 7,78
'&7,78
= 7,B9 = 0,075 or 7: 93
o Comparison to Risk: Similar to prevalence odds, incidence odds are close to risk when the risk is low
(<10%) but overestimate risk when it's high.
4. Incidence rate (or incidence density): Measures the rate at which new cases occur in relation to the total person-
time at risk.
,0: -./0/ ;4<5,= >5!0; 30<51;
o 𝐼𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑟𝑎𝑡𝑒 = 30</1,&(5C0 .( <5/? ;4<5,= >5!0; 30<51;
o Person-time: The sum of the time intervals each individual was
observed while at risk of the outcome 88. Example: 10 people followed
for 2 months = 10 ∗ 2 = 20 𝑝𝑒𝑟𝑠𝑜𝑛 − 𝑚𝑜𝑛𝑡ℎ𝑠
o Interpretation: Expressed as events per person-time (e.g., cases per
person-year). This measure accounts for variable follow-up times and is useful for comparing populations
with different follow-up durations.
o Example: Lung cancer metastasis study: 100 patients, 60 developed metastasis by 2008. 30 developed it
after 5 years, 30 after 10 years.
@7
§ 10-year risk: '77 = 0,6 = 60%
§ Incidence Rate: Assuming no loss to follow-up, person-time is calculated considering
when each case occurred: 𝑝𝑒𝑟𝑠𝑜𝑛𝑡𝑖𝑚𝑒 = (30 𝑝𝑎𝑡𝑖𝑒𝑛𝑡𝑠 ∗ 5𝑦) + (30 𝑝𝑎𝑡𝑖𝑒𝑛𝑡𝑠 ∗ 10𝑦) +
(40 𝑝𝑎𝑡𝑖𝑒𝑛𝑡𝑠 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑚𝑒𝑡𝑎𝑠𝑡𝑎𝑠𝑖𝑠 ∗ 10𝑦) = 850 person-years
@7 -./0/
𝐼𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑟𝑎𝑡𝑒 = = 0,071 cases per person-year
D67
o Time Units: Consistency in time units (days, months, years) is crucial.. Conventions within a field should
be followed, or units chosen based on the condition studied (e.g., hospital-days for infections)
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o Person-time Issues: Concepts like "pack-years" for
smoking illustrate cumulative exposure over time,
analogous to person-time.
Measure What is measured units range Synonyms
Counts Number of new cases Count 0 to infinity /
Proportions Averige probability of new None (snapshot of 0 to 1 Cumulative incidence
(risk) disease occurrence time)
Rate Average rate of new disease Inverse time 0 to inifinity Incidence density,
occurrence (events/person-time) person-time rate
Odds Ratio of events to non-events / 0 to infinity /
Summary: pros vs. cons
Pros Cons
Counts - Easy to understand - You cannot compare two counts unless the
- Communicates public health denominator is the same
importance - Needs context (denominator)
Proportions - Easy to understand - Interpretation conditional for recurrent
- Communicates public health outcomes
importance - Does not account for variable lengths of
follow-up between individuals
- Loses information compared to the survival
curve
Rate - Use all information available - Not easy to interpret
- Allows comparison of occurrence - Person time-units: interchangeable?
between populations or studies
with different follow-up periods
Odds - Use in measures of association (OR) - Not easy to interpret
- Similar to the risk when the - Can overstate the risk if the outcome is
outcome is rare common
3. Relationship between measures of occurrence
Incidence and prevalence
• Prevalence measures are similar to incidence measures when the duration of the disease is short 120.
• Incidence measures are better for quantifying occurrence when the duration of the disease is long 120.
• Prevalence combines incidence and duration of the disease 37 120.
• If the prevalence is low (<10%), prevalence odds and incidence odds are close
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