Reopening Calculator – Coronavirus

Estimate the chance that at least one infectious person is present at a gathering, from local COVID-19 case rates and group size, using P = 1 - (1 - p)^n.

Quick Facts

Method
Binomial event-risk model: P = 1 - (1 - p)^n
p is the estimated share of people currently infectious; n is the group size. Assumes infections are spread randomly across the local population.

Your Results

Calculated
Risk 1+ infectious person present
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P = 1 - (1 - p)^n
Estimated infectious prevalence
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Roughly 1 in this many people
Expected infectious in group
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Group size x prevalence (n x p)
Chance no one is infectious
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All-clear probability (1 - p)^n

Ready

Enter your group size and local case rate, then press Calculate.

About the Reopening Calculator

This calculator estimates the risk that at least one infectious person is present at a gathering, given how much COVID-19 is currently circulating in your area and how many people will attend. It uses the same binomial event-risk approach popularized by public COVID-19 event-risk planning tools: P = 1 - (1 - p)^n, where p is the probability a single random person is currently infectious and n is the group size.

How it works

The tool needs two things: how common active infections are locally, and how many people you are gathering. It converts reported case counts into an estimate of currently infectious people, then computes the chance that a group of that size includes at least one of them.

  • Prevalence (p): reported cases per 100,000 over the past 10 days are multiplied by an ascertainment factor (to account for undetected infections), then divided by 100,000. A roughly 10-day window approximates how long a person stays infectious.
  • Event risk: if each attendee is independently infectious with probability p, the chance that nobody is infectious is (1 - p)^n, so the chance that at least one person is infectious is 1 - (1 - p)^n.
  • Expected infectious attendees: on average, a group of n people contains n x p currently-infectious individuals.

How to interpret the result

The headline number is the probability that one or more infectious people attend — not the probability that anyone actually gets infected. Whether transmission happens also depends on ventilation, masking, vaccination, distance, and time spent together. A high presence risk paired with strong precautions can still be manageable, while a low presence risk with no precautions is not automatically safe.

Assumptions and limits

The model assumes infections are spread randomly and evenly across the local population and that recent reported cases approximate the currently infectious pool. It does not know your specific guests, so a group drawn from a higher- or lower-risk pool than the general population will differ from the estimate. Reported counts also undercount true infections, which is exactly why the ascertainment factor is applied.

When to rely on official guidance

Use this as a planning estimate, not a rule. For decisions about events, travel, or your own health, follow the current guidance of your local public-health authority or a qualified healthcare professional. This calculator provides a probability estimate only and does not account for individual circumstances or venue-specific factors.

Frequently Asked Questions

How does this reopening calculator estimate risk?
It uses the binomial event-risk formula P = 1 - (1 - p)^n. Here n is the group size and p is the probability that a single random person is currently infectious. It estimates p from reported cases per 100,000 over the past 10 days multiplied by an ascertainment factor, then divided by 100,000. P is the chance that at least one infectious person is present in the group.
What is the ascertainment factor and what value should I use?
Many infections are never reported, so official case counts undercount true circulating infections. The ascertainment factor scales reported cases up to approximate real active infections. Values between about 4 and 10 are commonly used depending on testing intensity; a higher factor reflects more undetected spread. If unsure, try a range of factors to see how sensitive the result is.
Does a low result mean the event is safe?
No. The result is the probability that at least one infectious person attends, not the probability that anyone is actually infected. Whether transmission occurs also depends on ventilation, masking, vaccination, distance, and time together. Treat it as a planning estimate and follow current guidance from your local public-health authority.

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