Epidemiology: Principles and Methods

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EpidemiologyPrinciples and Methods

• Prof. dr. Bhisma Murti, MPH, MSc, PhD
• Department of Public Health,
• Faculty of Medicine, Universitas Sebelas Maret

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Definitions in Epidemiology

• Definition and aims of epidemiology
• Study designs used in epidemiology
• Measures of Disease Frequency
• Incidence (Cumulative Incidence and Incidence
  Density)
• Prevalence
• Measures of Association
• Bias
• Confounding
• Chance
• Causal Inference

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Epidemiology

• A study of the distribution of disease frequency
  in human population and the determinants of that
  distribution
• Epidemiologists are not concerned with an
  individuals 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

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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.

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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 disease
5. Predict the disease occurrence
6. To evaluate the prevention and control of disease
7. Control the disease distribution

• Descriptive epidemiology
• Analytic epidemiology
• Applied epidemiology

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Descriptive and Analytical Epidemiology

• Descriptive epidemiology
• Describes the occurrence of disease
  (cross-sectional)
• 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

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Epidemiologic Study Designs
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Epidemiologic Study Designs
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Study Design and Its Strength of Evidence

• Systematic review, meta-analysis secondary data
  analysis
• Randomized Controlled Trials (RCT)
• Cohort prospective or retrospective
• Quasi experiment
• Case control prospective or retrospective
• Cross sectional
• Case Reports / Case Series

Strongest evidence
Weakest evidence
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Which Disease if More Important to Public Health?
Measure of Disease Occurence
Hypothetical Data Hypothetical Data Hypothetical Data Hypothetical Data
Measles Chickenpox Rubella
Children exposed Children ill Attack rate 251 201 0.80 238 172 0.72 218 82 0.38

• 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

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Description of Disease Distribution in the
Population
Disease reaches its peak in frequency in Week 6
Disease affects mostly people under five years of
age
Disease affects people living alongside the river
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Natural History of Disease
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Transmission

• 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

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Timeline of Infectiousness
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Measure of Disease Frequency

• Cumulative Incidence (Incidence, Risk, I, R)
• Number of new case over a time period
• Population 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.
• Incidence Density (Incidence Rate, ID, IR)
• Number of new case over a time period
• Person time at risk
• Indicates the velocity (speed) of the disease to
  occur in population over a time period. Value
  from 0 to infinity
• Prevalence (Point Prevalence)
• Number of new and old cases at a point of time
• Population
• Indicates burden of disease. Value from 0 to 1.

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Endemic vs. Epidemic
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Levels of Disease Occurence
Sporadic level occasional cases occurring at
irregular intervals Endemic level persistent
occurrence with a low to moderate level
Hyperendemic level persistently high level of
occurrence Epidemic or outbreak occurrence
clearly in excess of the expected level for a
given time period Pandemic epidemic spread over
several countries or continents, affecting a
large number of people
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Factors Influencing Disease Transmission
Agent
Environment

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

• Weather
• Housing
• Geography
• Occupational setting
• Air quality
• Food

Host

• Age
• Sex
• Genotype
• Behaviour
• Nutritional status
• Health status

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Measures of Infectivity, Pathogenecity, Mortality

• 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

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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

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Causal Model of Risk Factors for CVD
Disease
Proximate cause
Intermediate cause
Distal cause
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To Study Disease Etiology
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To Study Prognosis (Survival)
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Validity of Estimated Association and Causation
Smoking Lung
Cancer
OR 7.3
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The Role of Bias, Confounding, and Chance in The
Estimated Association
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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)

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Confounding

• 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
• This third factor is so called confounding factor

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Confounding
Observed (but spurious) association, presumed
causation
Downs syndrome
Birth Order
Unobserved association
True association
Maternal age
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Apakah Ada Hubungan antara Urutan Kelahiran dan
Risiko Sindroma Down?
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Confounding Biomedical Bestiary Michael,
Boyce Wilcox, Little Brown. 1984
Observed (but spurious) association, presumed
causation
Gambling
Cancer
Smoking, Alcohol, other Factors
Unobserved association
True association
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Hills Criteria for Causation

• Strength of association
• Specificity
• Temporal sequence
• Biologic gradient (dose-response relationship)
• Biologic plausibility
• Consistency
• Coherence
• Experimental study
• Analogy