Free 20-Lesson Course
Principles of EpidemiologyCount, describe, compare, explain, act
Principles of Epidemiology is a 20-lesson video course on how epidemiologists count disease, compare groups, and reason toward cause. It moves along one spine, count, describe, compare, explain, act: from prevalence, risk, person-time and standardized rates, through the two-by-two table and the ratio and difference measures, to ecological, cross-sectional, cohort, case-control and randomized designs, then random error, bias, confounding, effect modification, causal inference, screening and outbreak investigation. Every example is set in the fictional Oakhaven Health District, and every number is invented so the arithmetic stays clean and the method stays in focus. After the course, a learner can compute and interpret the core measures, choose and critique a study design, and judge whether an association is likely to be causal. It is education in epidemiologic reasoning, not clinical, screening or policy guidance.
Free Course
Principles of
Epidemiology
Produced by Subthesis
Course at a glance
20
Video lessons
About an hour each
1
Fictional district
Invented numbers keep the arithmetic clean
200
Quiz questions
Ten per lesson, every answer explained
Course outline
20 lessons from counting disease to investigating an outbreak · ~20 hours total · click any lesson to start
- Lesson 0
What Epidemiology Is: Counting Disease, Finding Its Causes
- State the standard definition of epidemiology and name its two halves, distribution and determinants
- Tell a descriptive question (how many, who, where, when) from an analytic one (why, compared with whom)
- Describe the course spine and explain why measures are taught before study designs
- Lesson 1
Prevalence vs Risk: How Epidemiologists Count Disease Right
- Classify any measure as a count, a ratio, a proportion or a rate
- Compute point and period prevalence and explain why they differ
- Build the population at risk by removing existing cases and people who cannot develop the condition
- Lesson 2
Person-Time and Incidence Rate: When Counting People Fails
- Explain why late entry, loss to follow-up and competing events break a closed-cohort risk
- Add up person-time by hand, stopping each clock at the case, the loss or the end of follow-up
- Compute an incidence rate with its units and read it as a speed rather than a percent
- Lesson 3
Natural History, Chain of Infection, and Levels of Prevention
- Place exposure, the detection threshold, symptom onset, diagnosis and outcome on the natural history timeline
- Distinguish the incubation period from the latent period and name the induction period
- Define infectivity, pathogenicity and virulence by their denominators
- Lesson 4
Epidemic Curves, Spot Maps, and Surveillance: Reading Data
- Describe a problem by person, place and time and pick the display that fits each question
- Build an epidemic curve by date of onset and classify its shape
- Estimate an exposure window from the earliest and latest onsets and the incubation range
- Lesson 5
Mortality Rates and Age Standardization: Why Crude Misleads
- Compute cause-specific mortality, proportionate mortality and the case fatality rate from one set of counts and name each denominator
- Define the infant mortality rate and the maternal mortality ratio and explain why each is a ratio
- Explain why crude death rates mislead when two populations have different age structures
- Lesson 6
The 2x2 Table: Risk Ratio and Risk Difference Explained Simply
- Build a two-by-two table in the course's fixed layout and fill in its margins
- Compute risk in each row by reading across, never down
- Compute and interpret the risk ratio at, above and below one, including the percent lower for a protective exposure
- Lesson 7
Odds Ratio vs Risk Ratio, Attributable Fraction, NNT Explained
- Convert a probability to odds and compute the odds ratio from a two-by-two table
- State when the odds ratio approximates the risk ratio and why a case-control study yields only an odds ratio
- Compute the attributable fraction among the exposed and the population attributable fraction, and name whose cases each describes
- Lesson 8
Epidemiology Study Designs: Ecological and Cross-Sectional
- Classify a study by what was done rather than by the name on the report
- Recognize an ecological study and explain the ecological fallacy
- Compute a prevalence ratio and a prevalence odds ratio from a survey table
- Lesson 9
Cohort Studies: Prospective, Retrospective, Open, and Closed
- Define a cohort study by its sampling and draw its schematic with time running forward
- Distinguish prospective from retrospective cohorts and tell a retrospective cohort from a case-control study
- Match closed cohorts to risks and open cohorts to rates
- Lesson 10
Case-Control Studies: Odds Ratios, Control Selection, Matching
- Define a case-control study by its sampling and draw its schematic with time running the right way
- Explain why the design yields only an odds ratio, and why doubling the controls leaves it unchanged
- Apply the control selection rule and spot a violation, such as clinic controls that turn 3.0 into 1.0
- Lesson 11
Randomized Controlled Trials: Randomization, Blinding, ITT
- Explain what randomization balances and distinguish random allocation from random sampling
- Draw a trial flow diagram that keeps exclusions, non-attenders and losses to follow-up separate
- Distinguish allocation concealment from blinding and name the bias each one prevents
- Lesson 12
Confidence Intervals and P-Values, Explained for Epidemiology
- Separate random error from systematic error, and precision from validity
- Read a confidence interval as a range of values compatible with the data and relate its width to study size
- Define the p-value correctly and name the three things it is not
- Lesson 13
Selection Bias in Epidemiology: Mechanism, Examples, Fixes
- Distinguish bias from chance and from confounding, and internal from external validity
- State the selection bias mechanism and show it as one leaking cell in a table
- Recompute an odds ratio under differential participation
- Lesson 14
Information Bias and Misclassification: Bias Toward the Null
- Define information bias and describe a measurement by its sensitivity and specificity
- Recompute a risk ratio under non-differential misclassification and explain why it moves toward the null
- Recompute the same truth under differential misclassification and explain why it can move either way
- Lesson 15
Confounding Explained: Criteria, Stratification, Adjustment
- State the three criteria for a confounder and restate confounding as a failure of comparability and as a backdoor path
- Distinguish a confounder from a mediator and decide which one to adjust for
- Detect confounding by comparing crude and stratum-specific risk ratios
- Lesson 16
Effect Modification vs Confounding: Reading Stratified Tables
- Define effect modification and contrast it with confounding
- Read a pair of stratified tables and decide whether the strata differ from each other, from the crude, or from neither
- Explain scale dependence and name the ratio or difference scale in every modification claim
- Lesson 17
Causal Inference in Epidemiology: Pies, Counterfactuals, DAGs
- Distinguish necessary, sufficient and component causes using the sufficient-component cause model
- Explain why fractions attributable to different component causes can sum past 100 percent
- State the counterfactual contrast and explain exchangeability as what randomization buys and confounding breaks
- Lesson 18
Sensitivity, Specificity, PPV, and the Biases of Screening
- Place screening on the natural history timeline and distinguish it from diagnosis
- Build the screening table and compute sensitivity, specificity and both predictive values with the right denominators
- Predict how prevalence changes the predictive values while sensitivity and specificity stay fixed
- Lesson 19
Outbreak Investigation Step by Step: Reports to Final Report
- List the steps of an outbreak investigation in order and explain why they overlap and loop
- Establish an outbreak against its baseline and write a tiered case definition
- Build a line list, read the epidemic curve, and estimate the exposure window
Questions, corrections, or a topic the course should cover?
Who it is for: Public health students, early-career practitioners and anyone who wants a concepts-first grounding in epidemiologic measures, designs and causal thinking.
Principles of Epidemiology is education in epidemiologic reasoning, not clinical, screening, or policy guidance. Every example is set in the fictional Oakhaven Health District, and every number is invented for teaching.