Journal article

Estimating the true (population) infection rate for COVID-19: A Backcasting Approach with Monte Carlo Methods

Steven Phipps, Quentin Grafton, Tom Kompas

Cold Spring Harbor Laboratory | Published : 2020

Abstract

ABSTRACT Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country overtime, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach, coupled with Monte Carlo methods, to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 countries where reliable data are available. We find a positive relationship between the testing rate per 1,000 people and the implied true detection rate of COVID-19, and a negative relationship between the proportion who test positive and ..

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University of Melbourne Researchers

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