7
Elaborate
Simulation: Stop the Spread
Duration
90 minutes
Type
Elaborate / Evaluate
Standards
MS-LS2-1, 7.SP.C.7
Learning Objectives
Students will be able to:
- Participate in a disease spread simulation using dice
- Collect and analyze outbreak data in real-time
- Test the effectiveness of different interventions
- Compare outcomes with and without interventions
The Dice Game Rules
Roles
S
Susceptible
Can get infected
Susceptible
Can get infected
I
Infected
Can infect others
Infected
Can infect others
R
Recovered
Immune
Recovered
Immune
Base Rules (No Interventions)
Each "Day" (Round):
- Everyone walks around the room randomly
- When an Infected person is near a Susceptible person:
- Infected rolls a die
- Roll 1-4: Transmission! Susceptible becomes Infected
- Roll 5-6: No transmission
- After 3 days infected: Become Recovered (immune)
Transmission probability: 4/6 = 67% per contact
Expected R0: ~2-3 depending on mixing
Intervention Rules
In later rounds, add interventions that change the dice rules:
| Intervention | New Rule | Effect |
|---|---|---|
| Better Ventilation | Roll 1-3 to transmit | ~25% reduction |
| Masks | Roll 1-2 to transmit | ~50% reduction |
| 50% Vaccinated | Half start as Recovered | Fewer susceptible |
| Distancing | Must be 2 arm lengths apart | Fewer contacts |
| Testing/Isolation | Infected removed after 1 day | Shorter infectious period |
Data Recording Sheet
Round 1: No Interventions
| Day | Susceptible (S) | Infected (I) | Recovered (R) |
|---|---|---|---|
| 0 | |||
| 1 | |||
| 2 | |||
| 3 | |||
| 4 | |||
| 5 | |||
| 6 | |||
| 7 | |||
| 8 |
Expected Results
No Interventions
- Fast spread
- Peak around day 4-6
- 60-80% eventually infected
- R0 estimate: 2-3
One Intervention
- Slower spread
- Later peak (day 6-8)
- 40-60% infected
- R0 estimate: 1.5-2
Multiple Interventions
- Much slower spread
- May not reach full peak
- 20-40% infected
- R0 estimate: 1-1.5
Note: Your results will vary due to randomness—that's part of the learning!
Analysis Questions
- Which intervention made the biggest difference?
- How did layering multiple interventions change outcomes?
- Was there variability between simulation runs? Why?
- When would have been the best time to implement interventions?
- How realistic was this simulation? What did it capture well? What was oversimplified?
- How does this connect to real-world decisions during an outbreak?
Compare Your Results
| Round | Interventions | Peak Day | Peak Infected | Total Infected |
|---|---|---|---|---|
| 1 | None | |||
| 2 | ||||
| 3 |
Key Takeaway
The simulation demonstrates how exponential spread works and how interventions can flatten the curve. Even simple changes to transmission probability (changing "roll 1-4" to "roll 1-2") have dramatic effects on outbreak size. Layering multiple imperfect interventions provides stronger protection than any single measure alone. And randomness matters—the same conditions can produce different outcomes, which is why early action is so important.