Epidemiology:Principles and Methods

Prof. dr. Bhisma Murti, MPH, MSc, PhD

Department of Public Health, Faculty of Medicine, Universitas Sebelas Maret

Definitions in Epidemiology

1. Definition and aims of epidemiology2. Study designs used in epidemiology3. Measures of Disease Frequency

– Incidence (Cumulative Incidence and Incidence Density) – Prevalence

4. Measures of Association5. Bias6. Confounding7. Chance8. Causal Inference

Epidemiology• A study of the distribution of disease frequency in human

population and the determinants of that distribution• Epidemiologists are not concerned with an individual’s

disease as clinicians do, but with a population’ distribution of the disease

• Distribution of disease by person, place, time• Assumption:

– Disease does not occur randomly – Disease has identifiable causes

• which can be altered and therefore • prevent disease from developing

Definition of Epidemiology• The study of the distribution and determinants of

health-related states or events in specified population, and the application of this study to control of health problems. [source: Last (ed.) Dictionary of Epidemiology, 1995]

• Determinants: physical, biological, social, cultural, and behavioral factors that influence health.

• Health-related states or events: health status, diseases, death, other implications of disease such as disability, residual dysfunction, complication, recurrence, but also causes of death, behavior, provision and use of health services.

Aims of Epidemiologic Research

1. Describe the health status of a population

2. To assess the public health importance of diseases

3. To describe the natural history of disease,

4. Explain the etiology of disease5. Predict the disease occurrence6. To evaluate the prevention and

control of disease7. Control the disease distribution

Descriptive epidemiology

Analytic epidemiology

Applied epidemiology

Descriptive and Analytical Epidemiology

1. Descriptive epidemiology• Describes the occurrence of disease (cross-

sectional)

2. Analytic epidemiology:• Observational (cohort, case control, cross-

sectional, ecologic study) – researcher observes association between exposure and disease, estimates and tests it

• Experimental (RCT, quasi experiment) – researcher assigns intervention (treatment), and estimates and tests its effect on health outcome

Epidemiologic Study Designs

Epidemiologic Study Designs

Study Design and Its Strength of Evidence

1. Systematic review, meta-analysis: secondary data analysis

2. Randomized Controlled Trials (RCT)3. Cohort: prospective or retrospective

Quasi experiment

4. Case control: prospective or retrospective5. Cross sectional 6. Case Reports / Case Series

Strongest evidence

Weakest evidence

• Attack rate is a Cumulative Incidence; it shows the risk (probability) of disease to occur in a population

• In regard to risk, measles is the most important disease to public health while rubella being the least

Hypothetical Data

Measles Chickenpox Rubella

Children exposedChildren ill

Attack rate

251201

0.80

238172

0.72

21882

0.38

Attack rate = Number of Ill persons (new cases)Population at risk exposed

Which Disease if More Important to Public Health? Measure of Disease Occurence

Description of Disease Distribution in the Population

Disease affects mostly people under five years of age

Disease affects people living alongside the river

Disease reaches its peak in frequency in Week 6

Natural History of Disease

Cases Index – the first case identified Primary – the case that brings the infection into a population Secondary – infected by a primary case Tertiary – infected by a secondary case

P

S

S

T

Susceptible

Immune

Sub-clinical

Clinical

ST

Transmission

Infe

ctio

nSusceptible

Susceptible

Dynamics of infectiousness

Dynamics of disease

Incubation period

Symptomaticperiod

Non-diseased

Latentperiod

Infectious period

Non-infectious

Infe

ctio

n

Time

Time

Timeline of Infectiousness

Measure of Disease Frequency1. Cumulative Incidence (Incidence, Risk, I, R)=

Number of new case over a time periodPopulation at risk at the outset- Indicates the risk for the disease to occur in population at risk over a time period. Value from 0 to 1.

2. Incidence Density (Incidence Rate, ID, IR)=Number of new case over a time periodPerson time at riskIndicates the velocity (speed) of the disease to occur in population over a time period. Value from 0 to infinity

3. Prevalence (Point Prevalence):Number of new and old cases at a point of timePopulationIndicates burden of disease. Value from 0 to 1.

Endemic EpidemicNu

mb

er

of

Case

s of

a

Dis

ease

Time

Endemic vs. Epidemic

Sporadic level: occasional cases occurring at irregular intervals Endemic level: persistent occurrence with a low to moderate level Hyperendemic level: persistently high level of occurrenceEpidemic or outbreak: occurrence clearly in excess of the expected level for a given time periodPandemic: epidemic spread over several countries or continents, affecting a large number of people

Levels of Disease Occurence

Agent

Host

Environment

• Age

• Sex

• Genotype

• Behaviour

• Nutritional status

• Health status

• Infectivity• Pathogenicity• Virulence• Immunogenicity• Antigenic stability• Survival

• Weather

• Housing

• Geography

• Occupational setting

• Air quality

• Food

Factors Influencing Disease Transmission

•Infectivity (ability to infect)

(number infected / number susceptible) x 100

•Pathogenicity (ability to cause disease)

(number with clinical disease / number infected) x 100

•Virulence (ability to cause death)

(number of deaths / number with disease) x 100

All are dependent on host factors

Measures of Infectivity, Pathogenecity, Mortality

Preventable Causes of Disease“BEINGS”

• Biological factors and Behavioral Factors• Environmental factors• Immunologic factors• Nutritional factors• Genetic factors• Services, Social factors, and Spiritual factors[JF Jekel, Epidemiology, Biostatistics, and Preventive Medicine, 1996]

Types of Cause:• Necessary cause: Mycobacterium tuberculosis• Sufficient cause: HIV• Contributory cause: Sufficient-Component Cause

Causal Model of Risk Factors for CVD

Morbidity and Mortality(Stroke, MI)

Biological Risk Factors

(Hypertension, Blood Lipids, Homocysteine)

Genetic Risk Factors(Family History)

Behavioral Risk Factors(Cigarette, Diet, Exercise)

Environmental Factors(Socioeconomic Status, Work Environment)

Disease

Proximate cause

Intermediate cause

Distal cause

To Study Disease Etiology

Kuartil asupan buah dan sayurKuartil asupan buah dan sayur

To Study Prognosis (Survival)

Validity of Estimated Association and Causation

24

Smoking Lung CancerOR = 7.3

Bias?

Confounding?

Chance?

True associationcausalnon-causal

The Role of Bias, Confounding, and The Role of Bias, Confounding, and Chance in The Estimated AssociationChance in The Estimated Association

25

Association ?

Selection Bias and Information Bias?

Confounding ?

Chance ?

True association

present

absent

likely

likelyunlikely

present

absent

unlikely

False association

BIAS

• Systematic errors in selection of study subjects, collecting or interpreting data such that there is deviation of results or inferences from the truth.

• Selection bias: noncomparable procedure used to select study subjects leading to noncamparable study groups in their distribution of risk factors. Example: Healthy worker bias

• Information bias: bias resulting from measurement error/ error in data collection (e.g. faulty instrument, differential or non-differential misclassification of disease and/ or exposure status. Example: interviewer bias, recall bias)

Confounding

1. A mixing of effects • between the exposure, the disease, and a third

factor associated with both the exposure and the disease

• such that the effect of exposure on the disease is distorted by the association between the exposure and the third factor

2. This third factor is so called confounding factor

Cases of Down syndroms by birth order

0

20

40

60

80

100

120

140

160

180

1 2 3 4 5

Birth order

Cases per 100 000 live births

Confounding

Birth Order Down’s syndrome

Maternal age

Observed (but spurious) association, presumed causation

Unobserved association

True association

Apakah Ada Hubungan antara Urutan Kelahiran dan Risiko Sindroma Down?

Confounding [Biomedical Bestiary: Michael, Boyce & Wilcox, Little Brown. 1984]

Gambling Cancer

Smoking, Alcohol, other Factors

Observed (but spurious) association, presumed causation

Unobserved association

True association

Hill’s Criteria for Causation

1. Strength of association2. Specificity3. Temporal sequence4. Biologic gradient (dose-response relationship)5. Biologic plausibility6. Consistency7. Coherence8. Experimental study9. Analogy