We have entered an odd pandemic moment. Some people are vaccinated, some are not. We are trapped between an ending and a fourth wave. Messaging is confusing. The CDC says it’s fine for vaccinated people to travel but also that they shouldn’t unless it’s absolutely necessary.
My email is full of questions again. They feel, in a way, not unlike the questions a year ago. Can I see my family? What about returning to child care? Can I get a haircut now? The difference is more optimism (yay!) but also more complexity, especially in the broader interactions. Last year, it was: “Can I see one set of grandparents outside for a hike?” Now, because of vaccination and other factors, there are many, many more people in these choices. I got one email outlining some possible future travel plans which involved two sets of grandparents, cousins with various levels of outside interaction and something about Uber.
People do not want to be unsafe. They do not want to be irresponsible. They want to think carefully about these choices and how to make them as safely as possible. But they are hard and confusing.
As I thought about answering this questions, regular readers will be unsurprised to learn that I decided we needed…a framework! But then I realized that wasn’t quite enough. The complexity of these questions needed something more precise; basically, they needed a calculator. With actual numbers.
So today I’m going to try to give you both: a framework (really, a simplification) which addresses some of your questions, and then a calculator for the rest. (You can use these together, or separately — that is, you can use the simplification and ignore the calculator, or you can modify the calculator to ignore the simplification. This is a bit of a choose your own adventure post).
Here’s the quick version.
Step 1: The Simplification This simplification will answer some of your questions directly, and make others easier. Like all simplifications, it’s imperfect and I’ll caveat below. Here it is: in your risk calculations, ignore the fully vaccinated people (fully vaccinated = 2 weeks from last dose). The quality of vaccines is such that, for most people in most situations, it is reasonable to assume that vaccinated people are safe. Or, put differently, that the risks they face and pose to others are well within the normal set of risks you are taking outside of COVID-19.
The ultimate goal is to give you a way to have a sense of the rough magnitude of risk (to your group, and to others) and to continue to push us to think about how to manage and lower those risk with the choices we make.
(Sidebar: I owe apologies to the several lovely people and groups who tried to help me build this weeks ago, when I didn’t have my head together to be helpful. I’m sorry!)
Step 1: The Simplification
The COVID-19 vaccines are really, really good. Our latest numbers suggest something close to 100% (it cannot really be 100%) protection against serious illness and death. This includes known variants. Protection against any illness also looks like it is running around 90% in the latest data. This latter fact — combined with the fact that any post-vaccine infections are likely to be asymptomatic — means vaccinated people are also extremely well protected against transmitting the virus.
The quality of these vaccines mean, as the CDC continues to suggest, vaccinated people can start to return to their normal lives. And for these reasons, I’m going to suggest you assume that vaccinated people are safe. Safe even if they are doing things like driving Ubers or going to indoor dining or seeing their friends for sleepovers. This is not a perfect assumption. Yes, vaccinated people can be infected and possibly infect others. But this is very unlikely.
It is helpful to see some numbers. Let’s say I’m vaccinated and I want to see a vaccinated friend in my house. We’ll assume a COVID prevalence in the area of 0.4%, and a within-household transmission risk of 12%.
The risk of her infecting me is:
0.4% (COVID prevalence) *
10% [90% reduction in her case risk] *
12% [Infection risk from in-house unmasked activity] *
10% [90% reduction in my case risk] = 0.00048%
This is about 1 in 208,000. This is the risk of any infection. My risk of serious illness or death is, basically, zero. My risk of transmitting to someone in the outside community is then this risk of infection, multiplied by that transmission risk. So, even smaller.
This risk is really, really small. It’s not zero. But it’s tiny.
What if she’s vaccinated and I’m not? Now, the risk of infection to me is about 1 in 20,000 (I lose the protection from my own vaccination). Serious illness and outside transmission risks are lower still.
It’s not that there is no risk here, but these risks are sufficiently small that they should likely be lumped in with all the other risks (accidents, other illnesses, etc) that you’re facing all the time and not thinking about. For example: the lifetime risk of being struck by lighting is 1 in 3,000 and the yearly rate of cancer diagnosis is 1 in about 250. Thinking about kids? The hospitalization rate for RSV for kids under a year is about 1 in 40. The death rate from drowning for children 1 to 4 is about 1 in 33,333 (from this post). Relative to these numbers, the vaccinated person COVID risks are simply very minimal.
A key reason to start with this simplification is that it actually answers a lot of questions people have. And it says some things are definitely okay. Examples from my inbox:
I’m fully vaccinated, can I go get a hair cut? Yes. You could have done this before, also.
My husband and I are fully vaccinated, can we go out on a dinner date just the two of us, even though our healthy 2 year old is unvaccinated? Yes. You are protected. The only relevant “interaction” here is between your kid and himself. Is he a risk to himself? Yes, but not from COVID.
My sister is fully vaccinated, and so are my husband and I. Can she come hold my healthy baby? Yes. Again, only risky interaction here is between baby and itself.
My mom is fully vaccinated. I’m not, and neither is my baby. Could she come hold the baby while I shower? Yes. Also while you nap. She’s protected. The relevant risky interactions are you and your baby; but your mom’s presence doesn’t affect that.
My dad is fully vaccinated but he likes to run marathons with other people. Should I avoid seeing him? No. He is protected. Good luck finding in-person marathons.
Caveats: Vaccinated people should keep masking in public, in no small part because it makes others more comfortable. For high risk unvaccinated people, more caution may be warranted. And if rates rise a huge amount or variants show vaccine escape, this could change. The pandemic has surprised us many times, but we need tools to make decisions now. For now: this simplification may help.
Of course, not everyone is vaccinated. Which is why we still need…a calculator.
Step 2: The Calculator
Imagine a scenario with multiple unvaccinated people (say, kids). What we need from a calculator is a way to think about these interactions.
A simple idea: list the (unvaccinated) people in the scenario, figure out the two-way risk from their interactions and aggregate the risks for each person. These risks include the risk of getting COVID, the risks of serious illness and (importantly) the risks of spreading to others.
This is going to require some work by you! You’ll need to think about who is coming, the COVID rates in their area, their serious illness risks. I’ve put in opportunities to modify each of these, and some sources. I’ve also included some baseline assumptions — which you can modify — about transmission, the efficacy of testing, the length of infectivity for COVID. (I also have a video — more on this below — with a particular example).
There is a way to modify the risk for each individual relative to the average in the population. Small children may have, on average, lower COVID risks; an unvaccinated family member who works in a customer-facing role may have higher risks. You could use this to modify for concerns about travel risk also. There is space for up to 10 people (you can add more) and a place to think about these people’s risk to the outside community. If you do not like the idea of ignoring vaccinated people, you could modify this to include them. You’d want to adjust their risks to reflect their vaccination
None of this is exact. The idea — like all models — is to help us think about the problem. Putting in numbers gives a sense of order of magnitude of risk — are we talking about 1 in 100, 1 in 1000, 1 in 10,000? Models help us think about what economists would call comparative statics. What can you move around in the assumptions to change the risk?
Examples & Results
Family Gathering Example
Let’s imagine I want to get together with my family. Here’s the setup: it’s me (vaccinated), my parents (both vaccinated), my brother (unvaccinated), my husband (unvaccinated), my brother’s kid (unvaccinated) and my two kids (both unvaccinated). We’re planning to drive to meet up at the parents house, and all stay together, unmasked, inside.
I worked through this example in this video. I encourage you to watch it, but not to @ me about my hair, which I swear I do sometimes brush.
There are a few things that become very clear. First, the rates where you are coming from matter. Higher rates are going to translate directly to a higher risk. Second, testing still matters. Remember testing? You can lower your risk a lot by having all the unvaccinated people test before they come.
The results in the example I work through suggest that this can be a low risk interaction, although not zero. It will be important to think about your interactions on the other end, too. For example, it is likely a good idea to test after the visit, as well as before.
Child Care or School
I designed this to think about family interactions, but you can easily modify to think about child care. Let’s say I’m thinking of sending my child to child care or school with a group of 9 other kids and two vaccinated caregivers or teachers. Ignore the vaccinated adults! But you can use this matrix to evaluate the kid risk to each other.
Here, I’d modify the baseline assumption of transmission. The baseline document assumes a household-based transmission rate. Child care and school settings are showing secondary infection rates more like 0.5%. But you can plug that in! Or higher rates if you are worried about more spread. And then you can think about how the risks vary with the rates in your area, with the testing protocols, and so on.
I do not know if this will be helpful! Almost a year ago, I wrote a decision framework which I think was helpful to a lot of people. This is a little more in the weeds. I mean, it needed a video. Still, this time is complicated, so maybe a spreadsheet is necessary. In my mind, a spreadsheet is always necessary.
This doesn’t answer everything. I know there are questions you all still have: What about airplanes and splash parks? What about long COVID in kids? What if transmission rates are higher due to variants? My goal with this was to provide a flexible tool, and my suggestion is that this is a way to start to organize your thoughts, and to see where you’d need to change up some numbers or plug different ones in.
Most importantly: even if this did capture every number, it wouldn’t give you an answer, because no two people will have the same reaction to a given number. The key, as always, is to look at the risks, look at them in context, and think about how they feel to you.