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Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission
In the recent 2014–2016 Ebola epidemic in West Africa, non-hospitalized cases were an important component of the chain of transmission. However, non-hospitalized cases are at increased risk of going unreported because of barriers to access to healthcare. Furthermore, underreporting rates may fluctua...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5806896/ https://www.ncbi.nlm.nih.gov/pubmed/29357363 http://dx.doi.org/10.1371/journal.pntd.0006161 |
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author | Dalziel, Benjamin D. Lau, Max S. Y. Tiffany, Amanda McClelland, Amanda Zelner, Jon Bliss, Jessica R. Grenfell, Bryan T. |
author_facet | Dalziel, Benjamin D. Lau, Max S. Y. Tiffany, Amanda McClelland, Amanda Zelner, Jon Bliss, Jessica R. Grenfell, Bryan T. |
author_sort | Dalziel, Benjamin D. |
collection | PubMed |
description | In the recent 2014–2016 Ebola epidemic in West Africa, non-hospitalized cases were an important component of the chain of transmission. However, non-hospitalized cases are at increased risk of going unreported because of barriers to access to healthcare. Furthermore, underreporting rates may fluctuate over space and time, biasing estimates of disease transmission rates, which are important for understanding spread and planning control measures. We performed a retrospective analysis on community deaths during the recent Ebola epidemic in Sierra Leone to estimate the number of unreported non-hospitalized cases, and to quantify how Ebola reporting rates varied across locations and over time. We then tested if variation in reporting rates affected the estimates of disease transmission rates that were used in surveillance and response. We found significant variation in reporting rates among districts, and district-specific rates of increase in reporting over time. Correcting time series of numbers of cases for variable reporting rates led, in some instances, to different estimates of the time-varying reproduction number of the epidemic, particularly outside the capital. Future analyses that compare Ebola transmission rates over time and across locations may be improved by considering the impacts of differential reporting rates. |
format | Online Article Text |
id | pubmed-5806896 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58068962018-02-23 Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission Dalziel, Benjamin D. Lau, Max S. Y. Tiffany, Amanda McClelland, Amanda Zelner, Jon Bliss, Jessica R. Grenfell, Bryan T. PLoS Negl Trop Dis Research Article In the recent 2014–2016 Ebola epidemic in West Africa, non-hospitalized cases were an important component of the chain of transmission. However, non-hospitalized cases are at increased risk of going unreported because of barriers to access to healthcare. Furthermore, underreporting rates may fluctuate over space and time, biasing estimates of disease transmission rates, which are important for understanding spread and planning control measures. We performed a retrospective analysis on community deaths during the recent Ebola epidemic in Sierra Leone to estimate the number of unreported non-hospitalized cases, and to quantify how Ebola reporting rates varied across locations and over time. We then tested if variation in reporting rates affected the estimates of disease transmission rates that were used in surveillance and response. We found significant variation in reporting rates among districts, and district-specific rates of increase in reporting over time. Correcting time series of numbers of cases for variable reporting rates led, in some instances, to different estimates of the time-varying reproduction number of the epidemic, particularly outside the capital. Future analyses that compare Ebola transmission rates over time and across locations may be improved by considering the impacts of differential reporting rates. Public Library of Science 2018-01-22 /pmc/articles/PMC5806896/ /pubmed/29357363 http://dx.doi.org/10.1371/journal.pntd.0006161 Text en © 2018 Dalziel 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 Dalziel, Benjamin D. Lau, Max S. Y. Tiffany, Amanda McClelland, Amanda Zelner, Jon Bliss, Jessica R. Grenfell, Bryan T. Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission |
title | Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission |
title_full | Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission |
title_fullStr | Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission |
title_full_unstemmed | Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission |
title_short | Unreported cases in the 2014-2016 Ebola epidemic: Spatiotemporal variation, and implications for estimating transmission |
title_sort | unreported cases in the 2014-2016 ebola epidemic: spatiotemporal variation, and implications for estimating transmission |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5806896/ https://www.ncbi.nlm.nih.gov/pubmed/29357363 http://dx.doi.org/10.1371/journal.pntd.0006161 |
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