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An exact method for quantifying the reliability of end-of-epidemic declarations in real time.

Published version
Peer-reviewed

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Abstract

We derive and validate a novel and analytic method for estimating the probability that an epidemic has been eliminated (i.e. that no future local cases will emerge) in real time. When this probability crosses 0.95 an outbreak can be declared over with 95% confidence. Our method is easy to compute, only requires knowledge of the incidence curve and the serial interval distribution, and evaluates the statistical lifetime of the outbreak of interest. Using this approach, we show how the time-varying under-reporting of infected cases will artificially inflate the inferred probability of elimination, leading to premature (false-positive) end-of-epidemic declarations. Contrastingly, we prove that incorrectly identifying imported cases as local will deceptively decrease this probability, resulting in delayed (false-negative) declarations. Failing to sustain intensive surveillance during the later phases of an epidemic can therefore substantially mislead policymakers on when it is safe to remove travel bans or relax quarantine and social distancing advisories. World Health Organisation guidelines recommend fixed (though disease-specific) waiting times for end-of-epidemic declarations that cannot accommodate these variations. Consequently, there is an unequivocal need for more active and specialised metrics for reliably identifying the conclusion of an epidemic.

Description

Funder: Christ Church University of Oxford Junior Research Fellowship

Keywords

Communicable Diseases, Epidemics, Humans, Models, Theoretical, Probability, Reproducibility of Results, Social Isolation, Travel

Journal Title

PLoS Comput Biol

Conference Name

Journal ISSN

1553-734X
1553-7358

Volume Title

16

Publisher

Public Library of Science (PLoS)
Sponsorship
Medical Research Council (MR/R015600/1)
Medical Research Council (MR/R015600/1)
UK National Institute for Health Research (HPRU-2012–10080)