CBRN Masks · Preparedness tools

Outbreak and Pandemic Simulator

See how an infectious disease would spread through your own town over 120 days, and how fewer contacts flatten the curve.

Explore. Understand. Prepare.Free tools for your own location.

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Educational model, not a forecast. In an emergency, follow official alerts.How it works ↓

How to use it

  1. 1
    Choose a townSearch a city or postcode, click the map or use your location. The model uses that town’s population.
  2. 2
    Set the diseaseChoose how contagious it is (R₀), how long people stay infectious and how strongly contacts are reduced.
  3. 3
    Watch the curvePress play or move through 120 days. The chart and the dots show the shares of susceptible, infectious and recovered people.

Every contact that does not happen slows the outbreak.

An outbreak grows as long as each infected person infects more than one other person on average. Fewer contacts, distance and protection push that number below one, and the outbreak fades.

This is a generic model for a closed community. It is not tied to a real disease, real case numbers or travel between towns.

SusceptibleInfectiousRecovered

How R₀ and contact reduction change an outbreak

Results of the simulator’s model for a town of 100,000 people with 10 initial infections and a 7-day infectious period.

R₀Peak without contact reductionInfected within 120 daysPeak with 40% fewer contactsInfected within 120 days (40% fewer contacts)
1.5day 11340%outbreak fades0%
2.0day 6480%after day 1202%
2.5day 4589%day 11340%
3.0day 3594%day 7772%

With 40% fewer contacts, R falls to 60% of R₀. Below 1 the outbreak fades; just above 1 it grows so slowly that the peak lies beyond 120 days.

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Questions and answers

What does the outbreak simulator show?

How an infectious disease could spread through the population of the town you choose over 120 days, using the classic SIR model (susceptible, infectious, recovered).

What does R₀ mean?

R₀ is the average number of people one infected person infects in a fully susceptible population. Above 1 the outbreak grows; below 1 it fades. Contact reduction lowers R by the same share.

Is this a forecast for a real disease?

No. The model is deliberately simple: no incubation period, deaths, vaccination, age groups or travel. It shows how the main factors interact, not what a real outbreak would do.

Which respiratory protection makes sense against infectious diseases?

For airborne pathogens, a filter that stops fine particles is what matters. A full-face mask also protects the eyes. For children and people who find breathing through a filter hard, hoods with a battery blower are an easier option.

How the model works · assumptions & sources

Deterministic SIR model for a closed population equal to the GeoNames population of the selected town (default: London or Berlin). β = R₀ × (1 − contact reduction) ÷ infectious period, γ = 1 ÷ infectious period; dS/dt = −βSI/N, dI/dt = βSI/N − γI, dR/dt = γI, integrated with 0.1-day Euler steps over 120 days. The 500 map dots are a random sample that shows the shares at the selected day; their positions are not real people. Not included: incubation, deaths, vaccination, age structure, travel, reinfection.

Maps: VersaTiles, © OpenStreetMap contributors. Places and postcodes: GeoNames (CC BY 4.0). Reactor data: GeoNuclearData (ODbL 1.0, from IAEA PRIS) and the IAEA research reactor database as compiled by Wikipedia (CC BY-SA 4.0), status updated to October 2026. Current weather on request: MET Norway (CC BY 4.0). Without location permission, the starting area is estimated from the country the store detects and your browser’s time zone. City search runs in your browser; your exact location is used only with your permission and stays in this browser tab. “Use current local weather” sends the coordinates of the scenario point to MET Norway. Map tile requests reveal the viewed map area to the map provider.