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The “risk” is misleading because it’s the risk that you will catch it within a 90 day period based on the community spread in the UK at some point in the past (before Delta) times the risk that you will die if you catch it.

Since your wife is a nurse, she’s much more likely to be exposed than the average UK resident. I also think even in her case you likely added an extra zero or 2 based on what I’m seeing while playing around with it.

I think what most people want is what’s my risk of death assuming I get it, not that multiplied times the risk of being infected within only the next 90 days.



>an absolute failure to understand Bayes theorem.


>a totally asinine comment

Why not multiply by the probability that you don't die within the next 90 days from some other event, or the probability that the earth doesn't explode within 90 days.

The likelihood that you're infected is both too hard to calculate for a given individual to be useful and, based on current epidemiological models, close enough to 1 over the long term for unvaccinated people that it doesn't make much difference.

The probability used in the model presented is the probability that a random person in the UK will be infected given the same conditions seen in March of 2020 over a 90 day period. It's a useless number. Multiplying the IFR just destroys whatever useful information you could extract from the IFR in the first place.


Those are two different measurements.

You have: 1. Chance of getting a disease 2. Chance of dying from said disease once acquired

Both have numerous factors that affect the result.


For someone who works in health care, they're likely subjected to multiple variants at one time.

What's the metrics look like when someone is hit with 2+ variants at once?

HIV is similar, where someone can be positive for 1 or more different strains. And their viral loads are cumulative.


At this point the Delta variant has effectively out completed everything. The chance of exposure to any other variant is low.




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