There are many things to take into account - CFR always varies by location, method of counting, underlying practices - & perhaps most importantly, time. I won't be able to cover it all.
But lets focus on a top few.
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But lets focus on a top few.
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First, we see *no evidence* that this CFR difference is explained by 'different viruses'. The samples we have are actually remarkably similar - max of ~30 differences out of >29,000 bases between two samples!
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Also, these samples are *very well mixed* - almost every country has samples from every type of diversity circulating!
Samples from USA (red) & UK (yellw) intermix. Many countries are like this. Tight clusters are related only to intense sampling in some place (Washington)
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Samples from USA (red) & UK (yellw) intermix. Many countries are like this. Tight clusters are related only to intense sampling in some place (Washington)
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1. CFR depends on testing 🧪👩🏻⚕️
CFR is calculated as # dead ➗ # confirmed cases. If you test a lot, the bottom number gets bigger - so your % will get smaller! Germany & S Korea are doing *lots* of testing!
If only sick tested, bottom number gets smaller - % gets larger
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CFR is calculated as # dead ➗ # confirmed cases. If you test a lot, the bottom number gets bigger - so your % will get smaller! Germany & S Korea are doing *lots* of testing!
If only sick tested, bottom number gets smaller - % gets larger
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2. Death counts always lag ☠️⏱️
#COVID19 doesn't kill suddenly - it takes days/weeks to die. So the # dead will always be a few weeks behind # cases. At beginning of outbreak this effect can be particularly strong as not as many people have died as will eventually
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#COVID19 doesn't kill suddenly - it takes days/weeks to die. So the # dead will always be a few weeks behind # cases. At beginning of outbreak this effect can be particularly strong as not as many people have died as will eventually
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3. Population is important 👵🏻👴🏻
#COVID19 is most risky for elderly people. In countries were the population is older, or where its introduced more into elderly groups, the # deaths will be higher. This effect can be stronger at begin of epi, if elderly groups infected 1st
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#COVID19 is most risky for elderly people. In countries were the population is older, or where its introduced more into elderly groups, the # deaths will be higher. This effect can be stronger at begin of epi, if elderly groups infected 1st
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4. Hospital capacity matters 🏥🚑
In places where the outbreak is very bad (Spain, Italy, Iran), hospitals are struggling to cope. They don't have enough staff/beds/supplies. This means people who might have been saved otherwise, will die - increasing the CFR.
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In places where the outbreak is very bad (Spain, Italy, Iran), hospitals are struggling to cope. They don't have enough staff/beds/supplies. This means people who might have been saved otherwise, will die - increasing the CFR.
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So when you see CFRs being compared in the news, remember, these numbers are important, but there's lots to keep in mind & consider when making these comparisons! Often reasons are more complex than simple explanation.
Help do your part 2 reduce CFR: #StayHomeSaveLives!
10/10
Help do your part 2 reduce CFR: #StayHomeSaveLives!
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(This twitter thread was inspired by a question asked by @iwan1988 - thanks Iwan!)
