The Danish paper on negative effectiveness can be because Denmark required proof of vaccination to attend large events. If some of those events were superspreader events you would see an apparent negative effectiveness.
Same sort of result out of Canada, which also required vaccination for large events:
So the idea is the boosted/double-vaxxed risk-compensate with their behavior to an extent that they’re at more risk than, perhaps, a more isolated unvaccinated person?
That may contribute as well, but I think Peter was implying that if enough cases overall take place during superspreader events where ~all of the attendees were vaccinated, vaccinated people may be more likely to test positive just because they were substantially more likely to be attending those superspreader events than unvaccinated people.
I agree that attending large events is a type of risk compensation, and we may be referring to similar behavior patterns using different words here. But I’m trying to distinguish between these two types of infection:
Infections resulting from people going about their daily activities (e.g. getting exposed at work, in a store or restaurant, other small gatherings, etc.) Here, individuals might indeed change their behavior based on their own vaccination status and risk tolerance. But since Omicron is so widespread at this point, the probability that an infected person was vaccinated should be close to the base rate of vaccination among the overall population (although somewhat lower, since the vaccines still prevent some transmission of Omicron). In other words, P(vaccinated | type-1 infection) is a little less than P(vaccinated).
Infections resulting directly from attending large superspreader events where proof of vaccination was required. In this case, while P(vaccinated | type-2 infection) won’t be exactly 1 due to the possibility of fake vaccine ID cards or weak enforcement of the policy at the event, I think it would still be quite close to 1.
If type-2 infections are a high enough percentage of overall infections, this could make it look like vaccinated people are more likely to get infected (which would be true at the population level!) even though getting vaccinated makes it less likely for any individual to get infected (assuming their behavior after vaccination remains the same).
Apologies if much of this is obvious or redundant—I’m still trying to understand the gears behind this dynamic better myself. I agree there is likely a component coming from “vaccinated people take on more risk in general”, but I hadn’t considered that policies which only allow vaccinated people (to a first approximation) to attend large potentially-superspreading events could lead to increased transmission among the vaccinated relative to the unvaccinated, which could lead to negative perceived vaccine effectiveness, until seeing Peter’s post.
Suppose 50% of vaccinated people would attend this event, and so would 50% of unvaccinated people, after considering the risks (ergo, there is no risk compensation). However, only vaccinated people are allowed to go to the event. Then the vaccinated people could have increased rates of Covid compared to unvaccinated people because of being more likely to attend superspreader events, even though they did not increase their level of risk compared to the unvaccinated population.
Whether this is the actual reason for the apparent negative effectiveness would depend on the actual percentages, and how common/dangerous superspreader events really are.
A vaccination requirement could result in lower apparent effectiveness; so could risk compensation. In order to determine how much risk compensation occurred, we have to determine how much the vaccination requirement lowered the effectiveness. Without that analysis, concluding that risk compensation has a big enough effect to cause or contribute significantly to negative effectiveness is premature.
I am otherwise unsure of what you are trying to get at. The unvaccinated were prevented from doing a risky activity, and the vaccinated were allowed to do the activity (with a lower risk due to their status), yes.
Well, if this is consistently applied across many events, the unvaccinated will not be allowed risky activities and the vaccinated will be allowed risky activities. Which means in practice consistently higher number of risky activities available for the vaccinated. I agree that this effect might not be significantly big and more measurements would be needed.
This is true to an extent. Unvaccinated people are still able to attend. They just would need to forge their vaccination card. I think this is not particularly hard to do, though it’s not trivially easy and many unvaccinated people would not do it for ethical reasons.
The Danish paper on negative effectiveness can be because Denmark required proof of vaccination to attend large events. If some of those events were superspreader events you would see an apparent negative effectiveness.
Same sort of result out of Canada, which also required vaccination for large events:
https://www.medrxiv.org/content/10.1101/2021.12.30.21268565v1
So the idea is the boosted/double-vaxxed risk-compensate with their behavior to an extent that they’re at more risk than, perhaps, a more isolated unvaccinated person?
That may contribute as well, but I think Peter was implying that if enough cases overall take place during superspreader events where ~all of the attendees were vaccinated, vaccinated people may be more likely to test positive just because they were substantially more likely to be attending those superspreader events than unvaccinated people.
How is that different from what CraigMichael said? Attending that sort of event is a type of risk compensation.
I agree that attending large events is a type of risk compensation, and we may be referring to similar behavior patterns using different words here. But I’m trying to distinguish between these two types of infection:
Infections resulting from people going about their daily activities (e.g. getting exposed at work, in a store or restaurant, other small gatherings, etc.) Here, individuals might indeed change their behavior based on their own vaccination status and risk tolerance. But since Omicron is so widespread at this point, the probability that an infected person was vaccinated should be close to the base rate of vaccination among the overall population (although somewhat lower, since the vaccines still prevent some transmission of Omicron). In other words, P(vaccinated | type-1 infection) is a little less than P(vaccinated).
Infections resulting directly from attending large superspreader events where proof of vaccination was required. In this case, while P(vaccinated | type-2 infection) won’t be exactly 1 due to the possibility of fake vaccine ID cards or weak enforcement of the policy at the event, I think it would still be quite close to 1.
If type-2 infections are a high enough percentage of overall infections, this could make it look like vaccinated people are more likely to get infected (which would be true at the population level!) even though getting vaccinated makes it less likely for any individual to get infected (assuming their behavior after vaccination remains the same).
Apologies if much of this is obvious or redundant—I’m still trying to understand the gears behind this dynamic better myself. I agree there is likely a component coming from “vaccinated people take on more risk in general”, but I hadn’t considered that policies which only allow vaccinated people (to a first approximation) to attend large potentially-superspreading events could lead to increased transmission among the vaccinated relative to the unvaccinated, which could lead to negative perceived vaccine effectiveness, until seeing Peter’s post.
Thank you, good explanation. But see also my response to tivelen below.
Suppose 50% of vaccinated people would attend this event, and so would 50% of unvaccinated people, after considering the risks (ergo, there is no risk compensation). However, only vaccinated people are allowed to go to the event. Then the vaccinated people could have increased rates of Covid compared to unvaccinated people because of being more likely to attend superspreader events, even though they did not increase their level of risk compared to the unvaccinated population.
Whether this is the actual reason for the apparent negative effectiveness would depend on the actual percentages, and how common/dangerous superspreader events really are.
But effectively, the unvaccinated were not allowed to have the same level of risk as vaccinated if they couldn’t come to the event, right?
A vaccination requirement could result in lower apparent effectiveness; so could risk compensation. In order to determine how much risk compensation occurred, we have to determine how much the vaccination requirement lowered the effectiveness. Without that analysis, concluding that risk compensation has a big enough effect to cause or contribute significantly to negative effectiveness is premature.
I am otherwise unsure of what you are trying to get at. The unvaccinated were prevented from doing a risky activity, and the vaccinated were allowed to do the activity (with a lower risk due to their status), yes.
Well, if this is consistently applied across many events, the unvaccinated will not be allowed risky activities and the vaccinated will be allowed risky activities. Which means in practice consistently higher number of risky activities available for the vaccinated. I agree that this effect might not be significantly big and more measurements would be needed.
This is true to an extent. Unvaccinated people are still able to attend. They just would need to forge their vaccination card. I think this is not particularly hard to do, though it’s not trivially easy and many unvaccinated people would not do it for ethical reasons.