Epidemiology:Principles and MethodsProf. dr. Bhisma Murti, MPH, MSc, PhD

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

Definitions in EpidemiologyDefinition and aims of epidemiologyStudy designs used in epidemiologyMeasures of Disease FrequencyIncidence (Cumulative Incidence and Incidence Density) PrevalenceMeasures of AssociationBiasConfoundingChanceCausal Inference

EpidemiologyA study of the distribution of disease frequency in human population and the determinants of that distributionEpidemiologists are not concerned with an individuals disease as clinicians do, but with a population distribution of the diseaseDistribution of disease by person, place, timeAssumption:Disease does not occur randomly Disease has identifiable causes which can be altered and therefore prevent disease from developing

Definition of EpidemiologyThe 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 ResearchDescribe the health status of a populationTo assess the public health importance of diseases To describe the natural history of disease, Explain the etiology of diseasePredict the disease occurrenceTo evaluate the prevention and control of diseaseControl the disease distributionDescriptive epidemiology

Analytic epidemiology

Applied epidemiology

Descriptive and Analytical EpidemiologyDescriptive epidemiologyDescribes 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 itExperimental (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 EvidenceSystematic review, meta-analysis: secondary data analysisRandomized Controlled Trials (RCT)Cohort: prospective or retrospective Quasi experimentCase control: prospective or retrospectiveCross sectional Case Reports / Case SeriesStrongest evidenceWeakest evidence

Attack rate is a Cumulative Incidence; it shows the risk (probability) of disease to occur in a populationIn regard to risk, measles is the most important disease to public health while rubella being the leastWhich Disease if More Important to Public Health? Measure of Disease Occurence

Hypothetical DataMeaslesChickenpoxRubellaChildren exposedChildren ill

Attack rate251201

0.80238172

0.7221882

0.38

Description of Disease Distribution in the PopulationDisease affects mostly people under five years of ageDisease affects people living alongside the riverDisease 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

Transmission

Timeline of Infectiousness

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

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 peopleLevels of Disease Occurence

AgentHostEnvironment Age Sex Genotype Behaviour Nutritional status Health status Infectivity Pathogenicity Virulence Immunogenicity Antigenic stability Survival Weather Housing Geography Occupational setting Air quality FoodFactors Influencing Disease Transmission

Infectivity (ability to infect)(number infected / number susceptible) x 100Pathogenicity (ability to cause disease)(number with clinical disease / number infected) x 100Virulence (ability to cause death) (number of deaths / number with disease) x 100All are dependent on host factorsMeasures of Infectivity, Pathogenecity, Mortality

Preventable Causes of DiseaseBEINGS Biological factors and Behavioral FactorsEnvironmental factorsImmunologic factorsNutritional factorsGenetic factorsServices, Social factors, and Spiritual factors

[JF Jekel, Epidemiology, Biostatistics, and Preventive Medicine, 1996]Types of Cause:Necessary cause: Mycobacterium tuberculosisSufficient cause: HIVContributory cause: Sufficient-Component Cause

Causal Model of Risk Factors for CVDDiseaseProximate causeIntermediate causeDistal cause

To Study Disease Etiology

To Study Prognosis (Survival)

Validity of Estimated Association and Causation* Smoking Lung CancerOR = 7.3

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

BIASSystematic 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 biasInformation 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)

ConfoundingA mixing of effects between the exposure, the disease, and a third factor associated with both the exposure and the diseasesuch that the effect of exposure on the disease is distorted by the association between the exposure and the third factorThis third factor is so called confounding factor

Chart1

56.7

68.5

81.4

114.4

165.6

Birth order

Cases per 100 000 live births

Cases of Down syndroms by birth order

Feuil1

< 2046.93620.745.30< 2043.2

20-2442.647.140.239.323.720-2442.8

25-2953.351.351.748.651.325-2951.2

30-34102.6101.184.187.775.530-3486.6

35-39270.5299.2242.2299.8246.535-39263.8

40+850.9753.6863.6940.1851.740+858.9

Total56.768.581.4114.4165.6

Feuil1

000000

000000

000000

000000

000000

< 20

20-24

25-29

30-34

35-39

40+

Birth order

Cases per 100000

Age groups

Cases of Down syndrom by birth order and mother's age

Feuil2

0

0

0

0

0

Birth order

Cases per 100 000 live births

Cases of Down syndroms by birth order

Feuil3

0

0

0

0

0

0

Age groups

Cases per 100000 live births

Cases of Down Syndrom by age groups

Confounding

Birth OrderDowns syndromeMaternal ageObserved (but spurious) association, presumed causationUnobserved associationTrue association

Apakah Ada Hubungan antara Urutan Kelahiran dan Risiko Sindroma Down?

Confounding [Biomedical Bestiary: Michael, Boyce & Wilcox, Little Brown. 1984]GamblingCancerSmoking, Alcohol, other FactorsObserved (but spurious) association, presumed causationUnobserved associationTrue association

Hills Criteria for CausationStrength of associationSpecificityTemporal sequenceBiologic gradient (dose-response relationship)Biologic plausibilityConsistencyCoherenceExperimental studyAnalogy

*Epidemiology is the basic science of public health and preventive medicine.Biostatistics is the quantitative foundation of epidemiology.It is important to present a comprehensive view of the fields of epidemiology, biostatistics, preventive medicine, and public health by showing their interrelationships and by emphasizing their relevance to clinical practice, research, and public health policy.Our goal is to combine the theory and application of epidemiology, with a smattering of biostatistics, in a manner that allows students to critically appraise and interpret the scientific literature with increased understanding.**Epidemiology has been defined in many ways - the simplest is the distribution and determinants of disease in a population. Epidemiology is one of the ways in which disease is studied. Others you are very familiar with include:1. Sub-molecular or molecular level - cell biology, biochemistry, and immunology2. Tissue or organ level - anatomy and pathology3. Personal level -the individual patient (clinical medicine)4. Population level - health of populations (epidemiology)

***With attention on the application to control, The BEINGS acronym for remembering categories of preventable causes of disease: Biological factors: infectious agents, allergens, vaccinesBehavioral factors: smoking, drinking, exercise, diet, health-seeking behaviorEnvironmental factors: polutants and contamination, as well as ticks, air conditioning systemsImmunologic factors: natural immunity, acquired immunityNutritional factors: obesity, malnutrition, dis-equilibrium in dietGenetic factors: genetic susceptabilityServices: access to careSocial factors: family supportSpiritual factors: belief system**

*******