Hi. You might be interested in how a doctor (much older than you) did his risk calculation before attending a friend's birthday party. I think you might be on the same page, or at least adjacent pages.
I wish I had a better grasp on how to go from community prevalence and positivity to the chance that a random individual has COVID. You need something like reported cases per day, times cases per reported case, times average number of days infectious but pre-symptomatic. The first is easily obtainable, the third is around 2-3 (?), and I have no idea how to estimate the second.
Some time back, researchers at Georgia Tech developed a tool that allows you to select a given gathering size and determine the chance that at least one COVID-19 positive person is present at a gathering of that size, based on currently epidemiological data for all counties in the US. It has granularity that goes down to metropolitan or county level, depending on locale.
Right now, it estimates that a gathering of 100 people in New York City has a 40% chance of at least one positive attendee, which is one of the reasons I'm not entirely dropping masking and made an effort to mask as much as possible when I was at that wedding recently.
Keep in mind that this risk level is likely skewed by transmission and disease among unvaccinated people--and perhaps by missing data resulting from home tests. Settings where everyone is vaccinated are probably different (potentially lower risk; this was a requirement at the wedding I attended, and I probably wouldn't have gone otherwise) than what the model might predict. But, I find the tool to be useful for very rough estimates. You can find it here: https://covid19risk.biosci.gatech.edu/
I've been kind of working under the theory that less than 2 months after recovering it would take some incredibly bad dice rolls to manage to get infected again*, but what I'm reading above makes me wonder whether I'm missing something?
I missed this edition of the newsletter until now, and I am glad to see at least some comment about mucosal immunity because I've been trying to track that down. I'm going to a bat mitzvah this coming weekend and I'm trying to get a handle on what that means for interacting with other people in the next days, what with boosted, recently recovered, and carrying with me a ridiculous number of antigen tests.
* didn't the Danes find only 47 omicron to omicron under 60 day reinfections out of 1.8 million in the time period, and 42 were unvax?
Hi. You might be interested in how a doctor (much older than you) did his risk calculation before attending a friend's birthday party. I think you might be on the same page, or at least adjacent pages.
https://wapo.st/3M47AWz
Note: story above "gifted", so no Post paywall.
Nature reports data that fourth shots of mRNA vaccines, at least in the quite short term, don't boost immunity very much: https://www.nature.com/articles/d41586-022-00486-9
I wish I had a better grasp on how to go from community prevalence and positivity to the chance that a random individual has COVID. You need something like reported cases per day, times cases per reported case, times average number of days infectious but pre-symptomatic. The first is easily obtainable, the third is around 2-3 (?), and I have no idea how to estimate the second.
Some time back, researchers at Georgia Tech developed a tool that allows you to select a given gathering size and determine the chance that at least one COVID-19 positive person is present at a gathering of that size, based on currently epidemiological data for all counties in the US. It has granularity that goes down to metropolitan or county level, depending on locale.
Right now, it estimates that a gathering of 100 people in New York City has a 40% chance of at least one positive attendee, which is one of the reasons I'm not entirely dropping masking and made an effort to mask as much as possible when I was at that wedding recently.
Keep in mind that this risk level is likely skewed by transmission and disease among unvaccinated people--and perhaps by missing data resulting from home tests. Settings where everyone is vaccinated are probably different (potentially lower risk; this was a requirement at the wedding I attended, and I probably wouldn't have gone otherwise) than what the model might predict. But, I find the tool to be useful for very rough estimates. You can find it here: https://covid19risk.biosci.gatech.edu/
I've been kind of working under the theory that less than 2 months after recovering it would take some incredibly bad dice rolls to manage to get infected again*, but what I'm reading above makes me wonder whether I'm missing something?
I missed this edition of the newsletter until now, and I am glad to see at least some comment about mucosal immunity because I've been trying to track that down. I'm going to a bat mitzvah this coming weekend and I'm trying to get a handle on what that means for interacting with other people in the next days, what with boosted, recently recovered, and carrying with me a ridiculous number of antigen tests.
* didn't the Danes find only 47 omicron to omicron under 60 day reinfections out of 1.8 million in the time period, and 42 were unvax?