Estimate the chance that at least one attendee is infectious and compare broad mitigation scenarios with a simplified COVID event-risk worksheet.
This worksheet estimates the probability that at least one person at an event is infectious with SARS-CoV-2, then shows how that base probability changes across simple mitigation scenarios. It is built around the same event-size probability logic used in public event-risk tools and is meant for comparison and planning rather than for a yes-or-no safety decision.
The core calculation uses binomial probability: given a community prevalence rate and the number of attendees, the chance that at least one person is infectious rises quickly with group size. That makes the page useful for comparing event formats even when the exact prevalence estimate is uncertain.
The mitigation section is intentionally simplified. Vaccination, masking, ventilation, and duration are treated as broad modifiers so users can compare indoor versus outdoor, shorter versus longer, or better versus worse layered-prevention scenarios without pretending the output is an exact infection probability.
This worksheet is most useful when it turns event planning into a scenario comparison instead of a guess. It helps organizers see how attendance, prevalence, ventilation, masking, and duration move the risk picture without pretending to certify an event as safe.
P(≥1 infectious) = 1 − (1 − prevalence)^attendees Expected Infectious = attendees × prevalence Adjusted Risk = P(≥1 infectious) × ventilation_factor × duration_factor × (1 − vacc_rate × 0.6) × (1 − mask_rate × 0.5) Ventilation Factors: Outdoor = 0.05, Well-Ventilated = 0.4, Average = 0.7, Poor = 1.0
Result: Risk Level: High — 23.4% adjusted risk
With 200 attendees at 2% prevalence, the probability of at least one infectious person is 98.2%. Expected infectious: 4. With 80% vaccinated, 30% masked, average indoor ventilation, and 3-hour duration, adjusted risk is 23.4%. Moving outdoors would reduce risk to 1.7%.
The first step is the event-size calculation: if community prevalence is known or estimated, the page calculates the probability that at least one person in the group is currently infectious. That number can become surprisingly large even at modest prevalence when the event size grows.
Ventilation, masking, vaccination, and duration all matter, but none of them work as fixed percentages in every setting. The page therefore uses illustrative reduction factors so users can compare scenarios such as indoor versus outdoor or lightly versus heavily mitigated gatherings. It should be read as a relative planning tool rather than an exact exposure predictor.
Use the worksheet to compare formats, shorten events, improve air quality, and decide where layered prevention matters most. Local respiratory-virus activity, the vulnerability of attendees, and the actual venue setup still matter more than any single number on the page.
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This page uses the standard binomial event-risk approach to estimate the probability that at least one attendee is infectious at a gathering: 1 - (1 - prevalence)^n. It then applies simple mitigation multipliers for ventilation setting, masking, vaccination, and duration so different scenarios can be compared side by side.
Those mitigation multipliers are illustrative rather than definitive. The page is meant for relative scenario planning, not to certify that an event is safe, because actual risk depends on the quality of the prevalence estimate, variant circulation, behavior at the event, air-cleaning specifics, symptom screening, and the vulnerability of the people attending.
Check your local health department dashboard, the CDC's COVID Data Tracker, or wastewater surveillance data. Reported case rates typically underestimate actual prevalence by 3–10× due to home testing and asymptomatic infections. Wastewater data is generally more accurate.
The base model uses general transmission parameters. More transmissible variants (like Omicron sublineages) effectively increase the community prevalence estimate. The mitigation reduction factors remain roughly consistent across variants.
Current data suggests updated boosters reduce transmission by approximately 40–60% for several months after vaccination. The effectiveness wanes over time. This calculator uses a 60% reduction factor, which represents recently boosted individuals.
Well-ventilated spaces have 6+ air changes per hour (ACH) with outside air. Examples include venues with operable windows, dedicated HVAC systems meeting ASHRAE standards, or portable HEPA filters providing equivalent ACH. Most homes and offices achieve only 1–3 ACH.
Outdoor events are much safer (95% risk reduction) but not zero-risk. Close face-to-face contact, enclosed tents, or large dense crowds can still facilitate transmission even outdoors. Maintain reasonable spacing when possible.
Aerosol concentration increases over time in indoor spaces. Risk scales roughly linearly with duration: a 4-hour event has approximately double the risk of a 2-hour event in the same space. Short, well-ventilated events are significantly safer.