POPH90014 Epidemiology 1
The Complete Exam Bible · S2 2026POPH90014 Overview
- Melbourne School of Population and Global Health
- Semester 2, 2026
- graduate coursework
- 12.5 points
- a foundational epidemiology subject
POPH90014 Epidemiology 1 covers disease frequency, association, impact, descriptive epidemiology, screening validity, causal inference, trials, cohort and case-control studies, measurement error, systematic review and population inference. It is taught within Melbourne School of Population and Global Health. It is graduate coursework.
- Denominators define meaning Prevalence, incidence proportion and incidence rate answer different questions because their denominators encode different populations and time.
- Validity is contextual Predictive values move with prevalence even when sensitivity and specificity remain fixed.
- Design shapes inference Trials, cohorts and case-control studies expose different routes to confounding, selection and information bias.
- Evidence must travel Internal validity does not establish that an estimate applies to a different target population.
How POPH90014 is assessed
| Component | Weight | Format |
|---|---|---|
| Online quiz (60 mins) | 20% | Week 6 |
| Tutorial Oral Assessment and Participation | 20% | Weeks 4, 8, and 12; source row contains an inconsistent internal split |
| Written Assignment: Written short answer assignment - 1500 words | 20% | Week 10 |
| Written Exam: Written assignment - 2hours | 40% | During the examination period |
The current syllabus publishes an Online quiz (60 mins) 20%, Tutorial Oral Assessment and Participation 20%, Written Assignment: Written short answer assignment - 1500 words 20%, and Written Exam: Written assignment - 2hours 40%. The oral row also prints '3x15% + 5%, 20% total', an internally inconsistent string retained as a source conflict; the live LMS controls its operation.
Current POPH90014 dates
| Date | Item | Control |
|---|---|---|
| Week 6 | Online quiz (60 mins) | 20%; live LMS controls the exact date. |
| Week 10 | Written short answer assignment | 20%; 1500 words in the current syllabus. |
Dates are as published in the current course materials. Confirm exact deadlines and submission settings in the live LMS.
What POPH90014 covers
Start with Epidemiologic Evidence and Public-Health Burden; use Randomised Controlled Trials as the turning point; finish by bringing the course together in External Validity and Triangulation.
Epidemiologic Evidence and Public-Health Burden
epidemiology · population health burden · surveillance · define a population-health question and interpret routine evidenceDefine epidemiology
The course material gives this chapter a concrete anchor: Week 1 distinguishes epidemiologic evidence from common-sense inference and introduces burden measures.
- Epidemiology
- Population health burden
- Surveillance
- Applying epidemiology
- Limits of population health burden and surveillance
Disease Frequency and Transmission
prevalence · incidence proportion · incidence rate · calculate and distinguish prevalence, incidence proportion and incidence rateDefine prevalence
The course material gives this chapter a concrete anchor: Week 2 explicitly contrasts person denominators with person-time and introduces transmission measures.
- Prevalence
- Incidence proportion
- Incidence rate
- Applying prevalence
- Limits of incidence proportion and incidence rate
Exposure–Outcome Association and Impact
risk ratio · risk difference · attributable fraction · calculate relative and absolute association and impact measuresDefine risk ratio
The course material gives this chapter a concrete anchor: Week 3 contrasts relative and absolute scales and links them to public-health impact.
- Risk ratio
- Risk difference
- Attributable fraction
- Applying risk ratio
- Limits of risk difference and attributable fraction
Disease Distribution and Age Standardisation
descriptive epidemiology · confounding by age · direct standardisation · inspect person-place-time patterns and standardise ratesDefine descriptive epidemiology
The course material gives this chapter a concrete anchor: Week 4 uses visual pattern inspection and age standardisation to make populations comparable.
- Descriptive epidemiology
- Confounding by age
- Direct standardisation
- Applying descriptive epidemiology
- Limits of confounding by age and direct standardisation
Measurement Validity and Screening Performance
sensitivity · specificity · positive predictive value · calculate validity and predictive-value measures from a two-by-two tableDefine sensitivity
The course material gives this chapter a concrete anchor: Week 5 connects measurement accuracy to the public-health consequences of screening.
- Sensitivity
- Specificity
- Positive predictive value
- Applying sensitivity
- Limits of specificity and positive predictive value
Causal Questions, Counterfactuals and DAGs
causal contrast · exchangeability · directed acyclic graph · frame PICOT questions and use DAGs to identify confounding controlDefine causal contrast
The course material gives this chapter a concrete anchor: Week 6 links counterfactual reasoning, exchangeability and graphical assumptions.
- Causal contrast
- Exchangeability
- Directed acyclic graph
- Applying causal contrast
- Limits of exchangeability and directed acyclic graph
Randomised Controlled Trials
random allocation · intention-to-treat analysis · risk of bias · critique allocation, adherence, outcome assessment and reporting in an RCTDefine random allocation
The course material gives this chapter a concrete anchor: Week 7 evaluates trials through design, ethics, ITT and risk-of-bias domains.
- Random allocation
- Intention-to-treat analysis
- Risk of bias
- Applying random allocation
- Limits of intention-to-treat analysis and risk of bias
Cohort Studies and Longitudinal Bias
cohort study · temporality · loss to follow-up · construct and critique a cohort comparisonDefine cohort study
The course material gives this chapter a concrete anchor: Week 8 compares cohorts with trials and applies bias analysis to longitudinal evidence.
- Cohort study
- Temporality
- Loss to follow-up
- Applying cohort study
- Limits of temporality and loss to follow-up
Case–Control Studies and Odds Ratios
case-control study · odds ratio · selection bias · calculate an odds ratio and evaluate selection of cases and controlsDefine case-control study
The course material gives this chapter a concrete anchor: Week 9 centres the source population, control selection, exposure measurement and odds-ratio interpretation.
- Case-control study
- Odds ratio
- Selection bias
- Applying case-control study
- Limits of odds ratio and selection bias
Measurement Error and Misclassification
information bias · differential misclassification · non-differential misclassification · identify misclassification and assess its effect on association measuresDefine information bias
The course material gives this chapter a concrete anchor: Week 10 distinguishes random and systematic error and tests differential mechanisms across designs.
- Information bias
- Differential misclassification
- Non-differential misclassification
- Applying information bias
- Limits of differential misclassification and non-differential misclassification
Systematic Reviews and Evidence Synthesis
systematic review · meta-analysis · publication bias · build and appraise a systematic-review chainDefine systematic review
The course material gives this chapter a concrete anchor: Week 11 follows protocol registration through search, selection, appraisal, synthesis and certainty.
- Systematic review
- Meta-analysis
- Publication bias
- Applying systematic review
- Limits of meta-analysis and publication bias
External Validity and Triangulation
external validity · target population · triangulation · assess transportability and triangulate across designsDefine external validity
The course material gives this chapter a concrete anchor: Week 12 connects causal inference, sufficient-component causes, cross-sectional designs and population inference.
- External validity
- Target population
- Triangulation
- Applying external validity
- Limits of target population and triangulation
It carries 12.5 points. It is positioned as a foundational epidemiology subject.
Students repeatedly calculate measures and then judge whether design, bias and target-population assumptions support a public-health decision.
Use the published assessment components listed on this page.
The operational assessment conditions matter here.
Current subject materials and the official timetable control any examination operation.
What makes POPH90014 demanding is concrete: keeping population, time, denominator and causal target aligned while moving from a numerical result to a bias-aware public-health interpretation
Use the published component conditions and the ordinary overall subject pass requirement.
For enrolment planning, confirm current eligibility in the 2026 Handbook.
Start with Epidemiologic Evidence and Public-Health Burden; use Randomised Controlled Trials as the turning point; finish by bringing the course together in External Validity and Triangulation.
POPH90014 cheatsheet for the final exam
AskSia publishes a free POPH90014 cheatsheet for the final exam, a cheat sheet that follows the official permitted-materials rule for this assessment and condenses the topics in this guide.
Worked example · free
Choose and interpret a frequency measure
- 1Identify the at-risk population at the start.
- 1Divide 32 new cases by 800 people.
- 1Express the result as 0.04 or 4% over one year.
- 1State why this is not an incidence rate.
Key terms
- Epidemiology
- Study of the distribution and determinants of health-related states in populations and application to control. This chapter uses the concept when students define a population-health question and interpret routine evidence.
- Population health burden
- Frequency and consequence of disease, injury or risk across a defined population and period. It helps explain the reasoning required to define a population-health question and interpret routine evidence.
- Surveillance
- Ongoing systematic collection, analysis and interpretation of health data for action. Its limit matters because routine counts depend on case definitions, coverage and denominators.
- Prevalence
- Proportion of a population with a condition at a specified point or period. This chapter uses the concept when students calculate and distinguish prevalence, incidence proportion and incidence rate.
- Incidence proportion
- Proportion of an initially at-risk population developing the outcome over a stated period. It helps explain the reasoning required to calculate and distinguish prevalence, incidence proportion and incidence rate.
- Incidence rate
- New events divided by accumulated person-time at risk. Its limit matters because infectious-disease transmission measures add contact and susceptibility assumptions.
- Risk ratio
- Risk in the exposed group divided by risk in the unexposed group. This chapter uses the concept when students calculate relative and absolute association and impact measures.
- Risk difference
- Risk in the exposed group minus risk in the unexposed group. It helps explain the reasoning required to calculate relative and absolute association and impact measures.
- Attributable fraction
- Proportion of risk among exposed people attributed to exposure under a causal interpretation. Its limit matters because causal impact language requires exchangeability and valid measurement.
- Descriptive epidemiology
- Description of disease by person, place and time. This chapter uses the concept when students inspect person-place-time patterns and standardise rates.
- Confounding by age
- Mixing of age composition with the comparison of interest. It helps explain the reasoning required to inspect person-place-time patterns and standardise rates.
- Direct standardisation
- Weighted average of stratum-specific rates using a common standard population. Its limit matters because standardised rates are comparison constructs, not observed crude burdens.
- Sensitivity
- Probability a test is positive among people who have the condition. This chapter uses the concept when students calculate validity and predictive-value measures from a two-by-two table.
- Specificity
- Probability a test is negative among people who do not have the condition. It helps explain the reasoning required to calculate validity and predictive-value measures from a two-by-two table.
POPH90014 FAQ
Where is the hardest reasoning in Epidemiology 1?
Keeping population, time, denominator and causal target aligned while moving from a numerical result to a bias-aware public-health interpretation. Disease frequency, association, impact, descriptive epidemiology, screening validity, causal inference, trials, cohort and case-control studies, measurement error, systematic review and population inference.
How does assessment work in Epidemiology 1?
The published assessment components listed on this page. Current subject materials and the official timetable control any examination operation. Use the published component conditions and the ordinary overall subject pass requirement.
What form does the exam or final task take in Epidemiology 1?
Current subject materials and the official timetable control any examination operation. The published assessment components listed on this page. Use the published component conditions and the ordinary overall subject pass requirement.
Which pass conditions apply in Epidemiology 1?
Use the published component conditions and the ordinary overall subject pass requirement. The published assessment components listed on this page. Current subject materials and the official timetable control any examination operation.
Which teaching period does this Epidemiology 1 resource cover?
It is aligned to Semester 2, 2026; confirm your enrolled class and timetable in the current institutional system. Online quiz (60 mins): Week 6; Written short answer assignment: Week 10.
What should a student check before enrolling in Epidemiology 1?
Confirm current eligibility in the 2026 Handbook. This resource covers Semester 2, 2026. Disease frequency, association, impact, descriptive epidemiology, screening validity, causal inference, trials, cohort and case-control studies, measurement error, systematic review and population inference.
Where should current dates for Epidemiology 1 be confirmed?
Online quiz (60 mins): Week 6; Written short answer assignment: Week 10. Confirm any change and the exact submission setting in the live LMS. The published assessment components listed on this page.
Who controls the official rules for Epidemiology 1?
The university does. This is an independent POPH90014 study resource; current institutional instructions remain authoritative for assessment operation. Disease frequency, association, impact, descriptive epidemiology, screening validity, causal inference, trials, cohort and case-control studies, measurement error, systematic review and population inference.
Questions students ask in each POPH90014 chapter
- What must be fixed before students define a population-health question and interpret routine evidence?
- Define a population-health question and interpret routine evidence. Week 1 distinguishes epidemiologic evidence from common-sense inference and introduces burden measures. Study of the distribution and determinants of health-related states in populations and application to control. This chapter uses the concept when students define a population-health question and interpret routine evidence. Chapter 01 · Epidemiologic Evidence and Public-Health Burden
- Which inputs and assumptions control the attempt to calculate and distinguish prevalence, incidence proportion and incidence rate?
- Calculate and distinguish prevalence, incidence proportion and incidence rate. Week 2 explicitly contrasts person denominators with person-time and introduces transmission measures. Proportion of a population with a condition at a specified point or period. This chapter uses the concept when students calculate and distinguish prevalence, incidence proportion and incidence rate. Chapter 02 · Disease Frequency and Transmission
- Which inputs and assumptions control the attempt to calculate relative and absolute association and impact measures?
- Calculate relative and absolute association and impact measures. Week 3 contrasts relative and absolute scales and links them to public-health impact. Risk in the exposed group divided by risk in the unexposed group. This chapter uses the concept when students calculate relative and absolute association and impact measures. Chapter 03 · Exposure–Outcome Association and Impact
- How does descriptive epidemiology help a student inspect person-place-time patterns and standardise rates?
- Inspect person-place-time patterns and standardise rates. Week 4 uses visual pattern inspection and age standardisation to make populations comparable. Description of disease by person, place and time. This chapter uses the concept when students inspect person-place-time patterns and standardise rates. Chapter 04 · Disease Distribution and Age Standardisation
- Which inputs and assumptions control the attempt to calculate validity and predictive-value measures from a two-by-two table?
- Calculate validity and predictive-value measures from a two-by-two table. Week 5 connects measurement accuracy to the public-health consequences of screening. Probability a test is positive among people who have the condition. This chapter uses the concept when students calculate validity and predictive-value measures from a two-by-two table. Chapter 05 · Measurement Validity and Screening Performance
- How does causal contrast help a student frame PICOT questions and use DAGs to identify confounding control?
- Frame PICOT questions and use DAGs to identify confounding control. Week 6 links counterfactual reasoning, exchangeability and graphical assumptions. Comparison between potential outcomes under alternative exposure states. This chapter uses the concept when students frame PICOT questions and use DAGs to identify confounding control. Chapter 06 · Causal Questions, Counterfactuals and DAGs
- How does random allocation help a student critique allocation, adherence, outcome assessment and reporting in an RCT?
- Critique allocation, adherence, outcome assessment and reporting in an RCT. Week 7 evaluates trials through design, ethics, ITT and risk-of-bias domains. Chance mechanism assigning eligible participants to intervention groups. This chapter uses the concept when students critique allocation, adherence, outcome assessment and reporting in an RCT. Chapter 07 · Randomised Controlled Trials
- Which constraints shape the work needed to construct and critique a cohort comparison?
- Construct and critique a cohort comparison. Week 8 compares cohorts with trials and applies bias analysis to longitudinal evidence. Design following exposed and unexposed participants to observe subsequent outcomes. This chapter uses the concept when students construct and critique a cohort comparison. Chapter 08 · Cohort Studies and Longitudinal Bias
- Which inputs and assumptions control the attempt to calculate an odds ratio and evaluate selection of cases and controls?
- Calculate an odds ratio and evaluate selection of cases and controls. Week 9 centres the source population, control selection, exposure measurement and odds-ratio interpretation. Design sampling people by outcome status and comparing prior exposure. This chapter uses the concept when students calculate an odds ratio and evaluate selection of cases and controls. Chapter 09 · Case–Control Studies and Odds Ratios
- Which evidence helps students identify misclassification and assess its effect on association measures?
- Identify misclassification and assess its effect on association measures. Week 10 distinguishes random and systematic error and tests differential mechanisms across designs. Systematic error arising from measurement or classification of study variables. This chapter uses the concept when students identify misclassification and assess its effect on association measures. Chapter 10 · Measurement Error and Misclassification
- Which constraints shape the work needed to build and appraise a systematic-review chain?
- Build and appraise a systematic-review chain. Week 11 follows protocol registration through search, selection, appraisal, synthesis and certainty. Review using explicit methods to identify, select, appraise and synthesise studies for a question. This chapter uses the concept when students build and appraise a systematic-review chain. Chapter 11 · Systematic Reviews and Evidence Synthesis
- How does external validity help a student assess transportability and triangulate across designs?
- Assess transportability and triangulate across designs. Week 12 connects causal inference, sufficient-component causes, cross-sectional designs and population inference. Extent to which an inference applies to a specified target population or setting. This chapter uses the concept when students assess transportability and triangulate across designs. Chapter 12 · External Validity and Triangulation
How to study for the exam
Retrieve the course map, practise the recurring method—define the population, time and denominator; select and calculate the epidemiologic measure; interpret its scale; then audit design, bias, causation and transportability—on changed scenarios, and verify every operational assessment detail in the live institutional system.
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