Estimating undetected Ebola spillovers
The preparedness of health systems to detect, treat, and prevent onward transmission of Ebola virus disease (EVD) is central to mitigating future outbreaks. Early detection of outbreaks is critical to timely response, but estimating detection rates is difficult because unreported spillover events an...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6563953/ https://www.ncbi.nlm.nih.gov/pubmed/31194734 http://dx.doi.org/10.1371/journal.pntd.0007428 |
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author | Glennon, Emma E. Jephcott, Freya L. Restif, Olivier Wood, James L. N. |
author_facet | Glennon, Emma E. Jephcott, Freya L. Restif, Olivier Wood, James L. N. |
author_sort | Glennon, Emma E. |
collection | PubMed |
description | The preparedness of health systems to detect, treat, and prevent onward transmission of Ebola virus disease (EVD) is central to mitigating future outbreaks. Early detection of outbreaks is critical to timely response, but estimating detection rates is difficult because unreported spillover events and outbreaks do not generate data. Using three independent datasets available on the distributions of secondary infections during EVD outbreaks across West Africa, in a single district (Western Area) of Sierra Leone, and in the city of Conakry, Guinea, we simulated realistic outbreak size distributions and compared them to reported outbreak sizes. These three empirical distributions lead to estimates for the proportion of detected spillover events and small outbreaks of 26% (range 8–40%, based on the full outbreak data), 48% (range 39–62%, based on the Sierra Leone data), and 17% (range 11–24%, based on the Guinea data). We conclude that at least half of all spillover events have failed to be reported since EVD was first recognized. We also estimate the probability of detecting outbreaks of different sizes, which is likely less than 10% for single-case spillover events. Comparing models of the observation process also suggests the probability of detecting an outbreak is not simply the cumulative probability of independently detecting any one individual. Rather, we find that any individual’s probability of detection is highly dependent upon the size of the cluster of cases. These findings highlight the importance of primary health care and local case management to detect and contain undetected early stage outbreaks at source. |
format | Online Article Text |
id | pubmed-6563953 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65639532019-06-20 Estimating undetected Ebola spillovers Glennon, Emma E. Jephcott, Freya L. Restif, Olivier Wood, James L. N. PLoS Negl Trop Dis Research Article The preparedness of health systems to detect, treat, and prevent onward transmission of Ebola virus disease (EVD) is central to mitigating future outbreaks. Early detection of outbreaks is critical to timely response, but estimating detection rates is difficult because unreported spillover events and outbreaks do not generate data. Using three independent datasets available on the distributions of secondary infections during EVD outbreaks across West Africa, in a single district (Western Area) of Sierra Leone, and in the city of Conakry, Guinea, we simulated realistic outbreak size distributions and compared them to reported outbreak sizes. These three empirical distributions lead to estimates for the proportion of detected spillover events and small outbreaks of 26% (range 8–40%, based on the full outbreak data), 48% (range 39–62%, based on the Sierra Leone data), and 17% (range 11–24%, based on the Guinea data). We conclude that at least half of all spillover events have failed to be reported since EVD was first recognized. We also estimate the probability of detecting outbreaks of different sizes, which is likely less than 10% for single-case spillover events. Comparing models of the observation process also suggests the probability of detecting an outbreak is not simply the cumulative probability of independently detecting any one individual. Rather, we find that any individual’s probability of detection is highly dependent upon the size of the cluster of cases. These findings highlight the importance of primary health care and local case management to detect and contain undetected early stage outbreaks at source. Public Library of Science 2019-06-13 /pmc/articles/PMC6563953/ /pubmed/31194734 http://dx.doi.org/10.1371/journal.pntd.0007428 Text en © 2019 Glennon 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 Glennon, Emma E. Jephcott, Freya L. Restif, Olivier Wood, James L. N. Estimating undetected Ebola spillovers |
title | Estimating undetected Ebola spillovers |
title_full | Estimating undetected Ebola spillovers |
title_fullStr | Estimating undetected Ebola spillovers |
title_full_unstemmed | Estimating undetected Ebola spillovers |
title_short | Estimating undetected Ebola spillovers |
title_sort | estimating undetected ebola spillovers |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6563953/ https://www.ncbi.nlm.nih.gov/pubmed/31194734 http://dx.doi.org/10.1371/journal.pntd.0007428 |
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