The population is split into susceptible, infected and recovered groups, evolving under the classic epidemiological SIR model. Transmission rate sets how fast the disease jumps between people; preventative-care investment (hygiene, awareness, vaccination) scales it down before it ever reaches the population.
dS/dt = −β·S·I/N
dI/dt = β·S·I/N − γ·I
dR/dt = γ·I
β_eff = β·(1 − 0.7·prevention)
Healthcare capacity caps how many infected people can be actively treated at once. When the infected count exceeds it, the hospital (the central building) overloads: excess cases turn critical (red) instead of treated (orange), and the effective recovery rate drops.
γ_eff = γ·min(1, capacity / infected)
- Transmission rate — how contagious the outbreak is; higher values push more susceptible residents (green) into the infected pool each simulated week.
- Healthcare capacity — the share of the population the local clinic can treat simultaneously; too low and cases go untreated once the outbreak peaks.
- Preventative-care investment — masks, vaccination campaigns and public-health messaging that cut the effective transmission rate before people get sick.
- Reset outbreak — reseeds a handful of initial cases and restarts the run from a fully susceptible population.