D625 is an in-depth look at the principles and methods used to understand patterns of health and disease in populations. WGU's guide names measures of disease frequency, study designs and principles of causation as core topics in the Master of Public Health.
The difficulty is precision. Terms such as incidence and prevalence, or association and causation, have exact meanings, and rubrics reward answers that use them correctly.
Course at a Glance
| Item | Details |
|---|---|
| University | Western Governors University |
| Course code | D625 |
| Level | Graduate, competency-based |
| Program | Master of Public Health (MPH) |
| Credit | 3 competency units |
| Prerequisite | None, per WGU's program guide |
| Related | D401 Introduction to Epidemiology (undergraduate) |
What D625 Covers
| Competency (summarized) | In practice |
|---|---|
| Analyze qualitative and quantitative epidemiological data | Interpret rates, tables and descriptive patterns |
| Apply epidemiologic methods, concepts and issues | Choose designs and measures for a question |
| Evaluate the effectiveness of disease prevention and control programs | Judge impact using appropriate evidence |
Key Concepts Explained
Incidence and Prevalence
Incidence counts new cases in a population at risk over a period. Prevalence counts existing cases at a point or over a period. Long-lasting diseases can have high prevalence even with low incidence.
Example: In a town of 10,000 people free of a disease at the start of the year, 50 develop it during the year. Incidence is 50 / 10,000 = 0.5 percent per year, or 5 per 1,000. If 200 residents live with the disease on 31 December, point prevalence is 2 percent.
Study Designs
Cross-sectional studies measure exposure and outcome at one time. Case-control studies compare people with and without the disease. Cohort studies follow exposed and unexposed groups. Randomized trials assign the intervention. Each has strengths and bias risks.
Measures of Association
The risk ratio compares risk in exposed and unexposed groups. The odds ratio is common in case-control studies. A value of 1 means no association.
Causation and Bias
Association does not equal causation. Weigh criteria such as temporality, strength, consistency, biological plausibility and dose-response, and check whether confounding explains the finding.
| Threat | Meaning | Typical remedy |
|---|---|---|
| Selection bias | Study groups differ systematically | Random selection or careful matching |
| Information bias | Exposure or outcome mismeasured | Standard, validated measurement |
| Confounding | A third factor distorts the association | Randomization, restriction or adjustment |
Example: Coffee drinkers appear to have higher lung cancer rates, but smoking is linked to both coffee drinking and lung cancer. Smoking is a confounder, and adjusting for it removes the false impression of an effect.
Evaluating Prevention and Control Programs
The third competency asks you to judge whether a program works. Define the outcome, choose a fair comparison, and consider reach as well as effect. A program with a strong effect in a few people may have less population impact than a modest one reaching many.
- Use surveillance trends to show before-and-after change.
- Compare with a similar population without the program.
- Consider unintended effects and equity of access.
Working a Two-by-Two Table
Many tasks involve a table of exposure and outcome. Setting it out carefully avoids most errors.
| Disease | No disease | Total | |
|---|---|---|---|
| Exposed | a | b | a + b |
| Unexposed | c | d | c + d |
Risk in the exposed is a / (a + b), risk in the unexposed is c / (c + d), and the risk ratio is their quotient. The odds ratio is (a x d) / (b x c).
Example: In a cohort, 30 of 200 exposed people and 10 of 200 unexposed people develop the disease. Risk is 15 percent versus 5 percent, so the risk ratio is 3.0. Exposed people had three times the risk, though confounding still has to be considered before claiming a cause.
Where Students Get Stuck
- Mixing up incidence and prevalence. Check the denominator and the time frame.
- Claiming causation from association. Discuss confounding and design.
- Picking a design by habit. Match design to question, time and ethics.
- Arithmetic errors. Show formulas and units.
Study Tips for D625
- Make a table of study designs with strengths and weaknesses.
- Do several two-by-two table calculations by hand.
- Always state the population at risk.
- Write a sentence of plain interpretation after each result.
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Frequently Asked Questions
WGU's program guide lists none.
Incidence measures new cases over time, prevalence measures existing cases.
Randomized trials are generally strongest, but they are not always possible or ethical.
It can create or hide associations, so conclusions must account for it.
It goes deeper into methods and expects more rigorous reasoning.
No. We provide tutoring and feedback only.