Parameters
Set up your outbreak, then explore how sensitive the results are to each parameter and how herd immunity works.
Simulation Parameters
Disease / Scenario Preset
Simulation Runs
Reproduction Numbers
Basic R₀
2.31
contacts × prob × time × density
Effective Rₑ
1.52
⚠ Outbreak can grow
R₀ = spread potential in a fully susceptible population.
Rₑ = actual spread after vaccination & immunity are applied.
Population
How crowded the community is. Crowded cities spread disease faster; low density works like social distancing.
🏘 Suburban / small city — density contact modifier: 0.96
Total number of people living in the simulated community.
How many people are already infectious on day 0 — the spark that starts the outbreak.
Disease Transmission
R₀ = contacts × density modifier × cluster factor × (prob/100) × days = 2.31
Higher → each sick person has more chances to spread the disease, so R₀ rises.
The chance that one meeting between a sick and a healthy person passes the disease. Realistic classroom values are often 1–5%.
How long a person stays sick and contagious. Longer → more chances to infect others, raising R₀.
The percentage of infected people who die. Higher → more deaths during the outbreak.
Vaccination
Higher → fewer people can catch the disease, so outbreaks stay smaller or may not start at all.
How well the vaccine protects each vaccinated person. Higher → fewer breakthrough infections.
Social Structure
"Random mixing" = everyone meets everyone equally. More clustering keeps contacts inside small groups, which usually slows the overall spread.
Reproducibility (Teacher Mode)
By default, each run uses a different random seed so students see genuine stochastic variation. Enable "Fixed Seed" so the whole class reproduces the same dataset.
Mode: random seed per run (recommended for students)
No simulation data yet
Configure parameters and run a simulation