Here's a thread that contains my findings regarding the relationship between true infections, reported cases, test positivity rate, and infection fatality rate for COVID-19.
Full write-up: http://covid19-projections.com/estimating-true-infections/ …
I hope to get some review/feedback/discussion from #epitwitter.
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These are the main conclusions I drew: 1) The virus is more prevalent now than in March/April 2) Current infection fatality rate is lower (~0.25%) mostly due to lower median age of infection 3) Herd immunity threshold is lower (~10-35%) due to lower rate of transmission (Rt)
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1) Higher prevalence I computed the true daily new infections using 3 separate methods, and they all point towards a higher prevalence in July. The estimated peak is ~450k new infections per day in July compared to ~300k/day in March.pic.twitter.com/STyfAdfb8B
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One way I estimate prevalence is by looking at the test positivity rate. Higher positivity -> higher ratio of undetected cases. I use a square root function to map test positivity rate to true prevalence ratio: true-prevalence-ratio = 16 * (test-positivity-rate)^(0.5) + 2.5pic.twitter.com/J8WsZNelyj
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having a hard time seeing how you picked that function abive all others but i guess i can understand the overall shape, but then, what parameters?
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