You might have seen images categorizing COVID risk as “high,” “medium,” or “low” or rating activities on a riskiness scale from 1 through 9. This is helpful, but personally we found that we had to dig further—into actual numbers—so we could make confident decisions.
Calling an event “high risk” is like categorizing a furniture purchase as “expensive.” If I’m buying a rug, and I know it’s “expensive,” but it would really complete the look of my room, can I afford to splurge this time? Maybe, or maybe not! If the rug is $100, that might be a sensible purchase. But if the rug is $10,000 then I might have difficulty paying for rent and groceries if I buy it!
Similarly: if I’ve been told that going to gatherings is “high risk” but I really truly miss my friends and there’s a picnic coming up I want to attend, should I go? Is this high risk like skiing, or high risk like jumping off a cliff?
We would like to give you a research-based, quantitative framework to answer questions like these.
Some people might not realize that it’s even possible to measure and numerically quantify the risk of getting COVID. Most sources tend to give non-quantitative advice, such as “the CDC recommends that everyone wear a mask to reduce transmission.” This advice is good, but we would like to go even further.
Fortunately, there are now many research papers available about the numerical likelihood of getting COVID from different kinds of interactions. You can search for these studies on Google Scholar and read them yourself. Some of these studies are not peer-reviewed (which is the gold standard for scientific publication), so it’s extra important to analyze them carefully. While none of us are public health experts, we have enough academic background to feel comfortable wading into the literature to come up with numerical estimates. We explain more of our reasoning in footnotes and in the Research Sources section.
So let’s get started. To quantify the risk of an individual interaction—say, meeting a friend for coffee—we’re going to think in terms of microCOVIDs (abbreviated μCoV)[1]: a one-in-a-million chance of getting COVID[2].
1 microCOVID = a one-in-a-million chance of getting COVID
For example, if you live in a region where about 1 in 1,000 people currently has COVID, then you could calculate based on studies of other indoor interactions (as we will explain later in this writeup) that meeting a friend for coffee indoors has about a 1 in 17,000 chance of giving you COVID. Such small numbers are hard to think about, so we can use microCOVIDs instead. Your coffee date would be about 60 microCOVIDs. By the end of this white paper, you will understand how to do these calculations yourself.
One benefit of using microCOVIDs is that you can straightforwardly add up microCOVIDs to estimate your risk over longer periods of time.[3]
We use microCOVIDs rather than some other scale factor (milliCOVIDs? nanoCOVIDs?) because they tend to come out as conveniently-sized numbers.
This whitepaper was started by a group of 30-something-year-olds in San Francisco who live together in a communal 9-person house and mostly work from home. After much discussion (which we hope to explain later in a future post), the household agreed to aim to keep each housemate's individual risks of getting COVID below 1% per year[4] (i.e., about 10,000 microCOVIDs per year). Important factors in this decision were that nobody in the household regularly interacted with anyone who was at high risk of severe illness from COVID, and that the household collectively cared a lot about doing their part to reduce the spread of the pandemic.
Each person had 2,400 microCOVIDs to spend per year after taking into account how many microCOVIDs would be used up just by living with each other[5]. With this budget:
| An activity that measures this many microCOVIDs... | feels this risky… | … and we could do the activity this often, if we were not doing much else |
|---|---|---|
| 1 μCoV | almost negligible | dozens of times per week |
| 10 μCoV | moderate risk | a few times per week |
| 100 μCoV | quite substantial risk | once or twice a month |
| 1000 μCoV | borderline reckless | once a year, maybe |
In general, if you are young and healthy, don’t regularly visit anyone who is older or has COVID risk factors, and are lucky enough to be able to make voluntary choices about your risk exposure, then we think aiming for 10,000 microCOVIDs per year (corresponding to 1% risk of COVID per year) is a plausible choice.
You can read more details on choosing your risk budget here.
What we want you to take away from this section is that for people under 40, an activity that is 1 microCOVID is very low risk, whereas an activity that is 1,000 microCOVIDs is very high risk. Furthermore, any risk of infection that you incur is not just a risk to you, but also a risk to vulnerable people in your community.
Let’s now explore how to quantify the risk of various activities in terms of microCOVIDs.
μ is the standard abbreviation for “micro,” the unit prefix meaning “one millionth.” For example, one microgram (μg) is one millionth of a gram. ↩︎
Strictly speaking there is a difference between “getting SARS-CoV-2” (the virus itself) and “getting COVID-19” (the disease caused by the virus). In the rest of this article, no matter what language we use, we are talking about the total chance of getting infected, including if you show no symptoms and are an asymptomatic carrier of the virus. We chose to use “microCOVIDs” (referring to the disease) instead of “microCoV” (referring to the virus) for this article based on reader feedback that it was simpler and easier to understand. But we emphasize that we are not excluding asymptomatic infections from this measurement. ↩︎
Technical note—skip if you’re not interested in the underlying math! If you’ve worked with probabilities before, you might worry that adding them together like this is too straightforward to possibly be correct. There’s an underlying nonlinearity: while you could accumulate well over a million microCOVIDs if you do enough risky things, your chance of getting COVID can never be higher than 100%. To properly compute the probability that you remain uninfected despite independent activities A and B, you should calculate ”probability not infected via A” * “probability not infected via B”. If you’d prefer to add instead of multiplying, then you’ll need to take a logarithm somewhere. Thus, to be fully correct, the formula for converting a risk (like 0.01 or 1%) to microCOVIDs should be -1,000,000 * ln(1 - risk). You can use calculus to verify that when the risk is small, this is very well approximated by the simpler 1,000,000 * risk. For values as high as 100,000 microCOVIDs, the error introduced by ignoring the logarithm is still within about 5%. The uncertainty in our other estimates is at least that large, so we think the simplification is reasonable. For calculations involving a multiple interractions with substatial risk (any calculation tha would result in >10% chance of infection), the calculator switches to multiplying for accuracy. ↩︎
Technically, what we mean when we say “1% per year” is a 1% annualized risk. That is, if we go 6 months without getting sick, we aren’t going to double our chances and bump up to a 2% chance in the following 6 months to even it out. We’ll continue at the same 1% annualized risk level. ↩︎
We have a detailed write up on how to adjust your budget given the number of people in your household/pod. ↩︎