Vaccine and disease-model lab
Mon, Oct 19, 2026 · Week 9 · Genetics of Disease (Medical Interventions)
Today's goal: Model how a vaccine triggers adaptive immunity and use disease-spread data to test a simple outbreak prediction.
What a finished product looks like
This is a model of the work you should turn in today. Use it to check your own: match the structure and the level of detail, do not copy it. Your data and wording should be your own.
Adaptive immunity diagram (in words): A pathogen displays an antigen. A B cell that fits that antigen activates and makes antibodies that tag the pathogen for destruction. Some of those cells become long-lived memory cells, so the next exposure triggers a faster, stronger response. A vaccine delivers the antigen without the disease, so memory cells form safely.
Disease-model results: I ran the model at two vaccination rates and recorded new infections.
Comparison sentence: The antibody response stops the disease inside one person by clearing the pathogen, while the population data shows that vaccinating enough people stops the disease between people by leaving the virus too few hosts to spread to.
| Vaccination rate | New infections (model run) |
|---|---|
| 40% | 180 |
| 80% | 22 |
Also due today: Save the diagram, data table, and comparison sentence to the course shell.
WebXam problem for today's skill
One exam-style question that uses exactly what you practiced today. Try it before you reveal the answer, then read why each choice is right or wrong.
Tap an answer to see the full explanation. Nothing is recorded or graded.