Most of what I see people use Microcovid.org for now is estimating risk for large gatherings, which it was not designed for and thus doesn’t handle very well. I spent a few hours going through every covid calculator I could find and this calculator from the Bazant lab at MIT, while less user-friendly than Microcovid and having some flaws of its own, is tailored made for calculating risks for groups indoors, and I think it is worth a shot.
[Note: I’ll be discussing the advanced version of the calculator here; I found the basic version too limited]
The Bazant calculator comes out of physics lab with a very detailed model of how covid particles hang and decay in the air, and how this is affected by ventilation and filtration. I haven’t checked their model, but I never checked Microcovid’s model either. The Bazant calculator lets you very finely adjust the parameters of a room: dimensions, mechanical ventilation, air filtration, etc. It combines those with more familiar parameters like vaccination and mask usage and feeds them into the model in this paper to produce an estimate of how long N people can be in a room before they accumulate a per-person level of risk between 0 and 1 (1 = person is definitely getting covid = 1,000,000 microcovids per person; .1 = 10% chance someone gets sick = 100,000 microcovids per person). It also produces an estimate of how much CO2 should accumulate over that time, letting you use a CO2 monitor to check its work and notice if risk is accumulating more rapidly than expected.
Reasons/scenarios to use the Bazant calculator over Microcovid:
You have a large group and want to set % immunized or effective mask usage for the group as a whole, instead of configuring everyone’s vaccinations and masks individually.
You want to incorporate the mechanics of the room and ventilation in really excruciating detail.
You want to set your own estimate for prevalence based on beliefs about your subpopulation.
You want a live check on your work, in the form of the CO2 estimates.
Reasons to use Microcovid instead:
Your scenario is outside – Bazant calculator doesn’t handle this at all.
You don’t want to have an opinion on infection prevalence, immunization, or mask usage.
Your masks are better than surgical masks (Bazant doesn’t handle N95 or similar. Also, it rates surgical masks as 90% effective, which seems very high to me).
Your per-person risk tolerance is < 10,000 microcovids (Bazant calculator can’t bet set at a lower risk tolerance, although you can do math on their results to approximate this).
You’re still using a bubble model, or tracking accumulated risk rather than planning for an event.
Scenarios neither handle well
Correlated risk. You might be fine with 10% of your attendees getting sick, but not a 10% chance of all of the attendees getting sick at once.
Differences in risk from low-dose vs. high-dose exposures.
I’m not currently planning any big events, but if someone else is, please give this a try and let us know if it is useful.
Bazant: An alternate covid calculator
Link post
Most of what I see people use Microcovid.org for now is estimating risk for large gatherings, which it was not designed for and thus doesn’t handle very well. I spent a few hours going through every covid calculator I could find and this calculator from the Bazant lab at MIT, while less user-friendly than Microcovid and having some flaws of its own, is tailored made for calculating risks for groups indoors, and I think it is worth a shot.
[Note: I’ll be discussing the advanced version of the calculator here; I found the basic version too limited]
The Bazant calculator comes out of physics lab with a very detailed model of how covid particles hang and decay in the air, and how this is affected by ventilation and filtration. I haven’t checked their model, but I never checked Microcovid’s model either. The Bazant calculator lets you very finely adjust the parameters of a room: dimensions, mechanical ventilation, air filtration, etc. It combines those with more familiar parameters like vaccination and mask usage and feeds them into the model in this paper to produce an estimate of how long N people can be in a room before they accumulate a per-person level of risk between 0 and 1 (1 = person is definitely getting covid = 1,000,000 microcovids per person; .1 = 10% chance someone gets sick = 100,000 microcovids per person). It also produces an estimate of how much CO2 should accumulate over that time, letting you use a CO2 monitor to check its work and notice if risk is accumulating more rapidly than expected.
Reasons/scenarios to use the Bazant calculator over Microcovid:
You have a large group and want to set % immunized or effective mask usage for the group as a whole, instead of configuring everyone’s vaccinations and masks individually.
You want to incorporate the mechanics of the room and ventilation in really excruciating detail.
You want to set your own estimate for prevalence based on beliefs about your subpopulation.
You want a live check on your work, in the form of the CO2 estimates.
Reasons to use Microcovid instead:
Your scenario is outside – Bazant calculator doesn’t handle this at all.
You don’t want to have an opinion on infection prevalence, immunization, or mask usage.
Your masks are better than surgical masks (Bazant doesn’t handle N95 or similar. Also, it rates surgical masks as 90% effective, which seems very high to me).
Your per-person risk tolerance is < 10,000 microcovids (Bazant calculator can’t bet set at a lower risk tolerance, although you can do math on their results to approximate this).
You’re still using a bubble model, or tracking accumulated risk rather than planning for an event.
Scenarios neither handle well
Correlated risk. You might be fine with 10% of your attendees getting sick, but not a 10% chance of all of the attendees getting sick at once.
Differences in risk from low-dose vs. high-dose exposures.
I’m not currently planning any big events, but if someone else is, please give this a try and let us know if it is useful.