1/ Q: What’s my personal risk for a bad #Covid_19 outcome should I become infected?
A: A variety of new “risk calculators” can help you answer this very question (Links below).
BIG CAVEAT: There are huge margins of error on the results, often making risk scores LESS ACCURATE.
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Background: As several parts of the country #reopen, we need to make our own, individualized risk/benefit calculations. It’s a tough puzzle – we all have incredibly unique circumstances, constraints, and supports under which we’re operating.
3/ Both clinical medicine and health care policy rely on statistically sophisticated prediction models to estimate an individual’s risk for an outcome of interest (good or bad).
These models suggest answers to the Q: “What’s my personal risk for X outcome if I contract #COVID?”
4/ Much of the buzz around machine learning and AI in medicine relates to their improving the accuracy of person-specific “clinical risk scores.”
In fact, Nerdy Girl @lindsleininger spent a chapter of her career developing, testing, and translating such models for policy-makers.
5/ Many new #COVIDー19-specific risk calculators can meet individuals’ needs in making risk/benefit calculations during the pandemic (see table one): cebm.net/covid-19/what-…
6/ It’s so, so important note that these are built on new data that haven’t been widely validated. These tools perform best at the POPULATION level, as opposed to the INDIVIDUAL level.
7/ For example, we know that on average 100,000 people with preexisting heart conditions are more likely to have a poor #COVID__19 prognosis than 100,000 people with no conditions.
But for any one person within either of those groups there’s a large margin of error.
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If, on balance, you feel like having incomplete information is better than no information about your individual risk, then by all means check out the calculators. And note that it’s best to compare estimates from a variety of tools, versus having complete faith in one tool.
9/ Finally, look for calculators with LARGE underlying data sets that GENERALIZE WELL TO YOUR CONTEXT.
1/ Q: Has almost everyone been infected with COVID by now?
A: Recent estimates suggest around 58% of the population in the US and over 70% in England have been previously infected, with BIG increases during the Omicron wave.
3/ ➡️ During the Omicron wave from December 2021-February 2022, this estimate increased from 33% to 58%.
➡️ Rates vary a lot by age, ranging from 33.2% for those over age 65 to 75% for those under age 18.
2/ Not likely. If your kids are suddenly getting sick a lot, this is likely due to “catching up” on exposures rather than a weakened immune system.
3/ Many families w/ young kids have been hunkered down for the better part of 2 years– a good % of a young child’s entire life. While isolation had *many* downsides, we can agree that not having to suction snot out of infant noses or clean up norovirus puke was a happy upside.
1/ Q: Are cases peaking? That means it’s all downhill from here, right?
A: Sort of…. Remember that even if cases come down as quickly as they rise, there will be as many cases *after* the peak as before (think area under the curve).
2/ ➡️ And if the downward slope is *slower* than the rise, we will see *more* cases during the decline from a surge.
3/ Burning fast could be a silver lining of super transmissible #Omicron. Cases rose & fell quickly in S. Africa (w/ hospitalizations & deaths still lagging). The UK appears to have turned the Omicron corner. Many US states appear past their peak in cases, w/ regional variation:
Unfortunately, this includes New Year’s Eve plans. The perfect storm of a new variant & holiday get-togethers is hitting communities & health care w/ FORCE! Testing is in short supply.
3/ Health care is under extreme pressure with surging cases. If you can avoid even one additional contact, you are helping. This is a temporary and urgent request (from a health care provider).