Author: Tom Britton
Title: Basic prediction methodology for covid-19: estimation and sensitivity considerations Document date: 2020_3_30
ID: hsgzkpg4_39
Snippet: One of our main conclusions is that any prediction of the number of infected, using data from cumulative case fatalities, rely heavily on accurate knowledge of the infection fatality risk f . Without accurate knowledge of f , the prediction of the total case fatality once the epidemic outbreak is over, is equipped with a similar multiplicative uncertainty. It is hence of utmost importance to obtain more accurate estimates of f . The best way to o.....
Document: One of our main conclusions is that any prediction of the number of infected, using data from cumulative case fatalities, rely heavily on accurate knowledge of the infection fatality risk f . Without accurate knowledge of f , the prediction of the total case fatality once the epidemic outbreak is over, is equipped with a similar multiplicative uncertainty. It is hence of utmost importance to obtain more accurate estimates of f . The best way to obtain such estimates, now that seroprevalence tests are becoming available, is to conduct tests on a random sample of a community in which the outbreak is (close to) over. f is then simply estimated as the ratio of the total number of case fatalities and the estimated population number of people testing positive.
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