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OutbreakForge

How does one number, R₀, decide whether a disease fizzles out or sweeps a town? Predict, run the model, then weigh a hard decision.

How this works

Run a real epidemic model on a made-up population: predict what happens, watch the curve, then try vaccinating or reducing contact and weigh what you gained against what it cost. No real people, no real disease — just the mechanism, and a genuinely hard decision.

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A case · you decide

Amara's school-flu plan

Amara, 17 — on the student council, asked to recommend what the school does about a flu wave

The idea in play: an outbreak grows while each case infects more than one other person (R above 1); vaccination and fewer contacts both work by pushing R below 1.

Twelve students are off sick. The model the health class built puts R at about 1.8 for this flu at school. The council has two days and three options on the table.

At R = 1.8, each case leads to almost two more. Small numbers today become large numbers in a couple of weeks.

Herd immunity for R = 1.8 needs about 1 − 1/1.8 ≈ 44% of people protected.

Which question should Amara bring to the council first?

A free vaccine clinic could protect about 30% of students. Is that enough on its own?

Run an outbreak ↑

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