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An exact method for quantifying the reliability of end-of-epidemic declarations in real time
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, o...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717584/ https://www.ncbi.nlm.nih.gov/pubmed/33253158 http://dx.doi.org/10.1371/journal.pcbi.1008478 |
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author | Parag, Kris V. Donnelly, Christl A. Jha, Rahul Thompson, Robin N. |
author_facet | Parag, Kris V. Donnelly, Christl A. Jha, Rahul Thompson, Robin N. |
author_sort | Parag, Kris V. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7717584 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-77175842020-12-09 An exact method for quantifying the reliability of end-of-epidemic declarations in real time Parag, Kris V. Donnelly, Christl A. Jha, Rahul Thompson, Robin N. PLoS Comput Biol Research Article 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. Public Library of Science 2020-11-30 /pmc/articles/PMC7717584/ /pubmed/33253158 http://dx.doi.org/10.1371/journal.pcbi.1008478 Text en © 2020 Parag et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Parag, Kris V. Donnelly, Christl A. Jha, Rahul Thompson, Robin N. An exact method for quantifying the reliability of end-of-epidemic declarations in real time |
title | An exact method for quantifying the reliability of end-of-epidemic declarations in real time |
title_full | An exact method for quantifying the reliability of end-of-epidemic declarations in real time |
title_fullStr | An exact method for quantifying the reliability of end-of-epidemic declarations in real time |
title_full_unstemmed | An exact method for quantifying the reliability of end-of-epidemic declarations in real time |
title_short | An exact method for quantifying the reliability of end-of-epidemic declarations in real time |
title_sort | exact method for quantifying the reliability of end-of-epidemic declarations in real time |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717584/ https://www.ncbi.nlm.nih.gov/pubmed/33253158 http://dx.doi.org/10.1371/journal.pcbi.1008478 |
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