A Method for Estimating the Number of Infections From the Reported Number of Deaths

Bibliographic Data

ID22077825
AuthorsÅke Brännström (0000-0001-9862-816X, International Institute for Applied Systems Analysis, corresponding author), Henrik Sjödin (0000-0003-1235-4781, Umeå University), Joacim Rocklöv (0000-0003-4030-0449, Umeå University)
Year2022
Volume9
Pages648545-648545
Publication date2022-01-20
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2021.648545
PMID35111706
OpenAlexW4200253792
LanguageEN
Citations received3
References cited13

At the outset of an epidemic, available case data typically underestimate the total number of infections due to insufficient testing, potentially hampering public responses. Here, we present a method for statistically estimating the true number of cases with confidence intervals from the reported number of deaths and estimates of the infection fatality ratio; assuming that the time from infection to death follows a known distribution. While the method is applicable to any epidemic with a significant mortality rate, we exemplify the method by applying it to COVID-19. Our findings indicate that the number of unreported COVID-19 infections in March 2020 was likely to be at least one order of magnitude higher than the reported cases, with the degree of underestimation among the countries considered being particularly high in the United Kingdom

2019-20 coronavirus outbreak · Case fatality rate · Confidence interval · Disease · Mortality rate · Outbreak · Statistics · COVID-19 Clinical Research Studies · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Demography · Mathematics · Medicine · Epidemiology · Internal Medicine · Virology