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Key data for outbreak evaluation: building on the Ebola experience
Following the detection of an infectious disease outbreak, rapid epidemiological assessment is critical for guiding an effective public health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gaine...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5394647/ https://www.ncbi.nlm.nih.gov/pubmed/28396480 http://dx.doi.org/10.1098/rstb.2016.0371 |
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author | Cori, Anne Donnelly, Christl A. Dorigatti, Ilaria Ferguson, Neil M. Fraser, Christophe Garske, Tini Jombart, Thibaut Nedjati-Gilani, Gemma Nouvellet, Pierre Riley, Steven Van Kerkhove, Maria D. Mills, Harriet L. Blake, Isobel M. |
author_facet | Cori, Anne Donnelly, Christl A. Dorigatti, Ilaria Ferguson, Neil M. Fraser, Christophe Garske, Tini Jombart, Thibaut Nedjati-Gilani, Gemma Nouvellet, Pierre Riley, Steven Van Kerkhove, Maria D. Mills, Harriet L. Blake, Isobel M. |
author_sort | Cori, Anne |
collection | PubMed |
description | Following the detection of an infectious disease outbreak, rapid epidemiological assessment is critical for guiding an effective public health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gained in the West African Ebola epidemic and prior emerging infectious disease outbreaks to set out a checklist of data needed to: (1) quantify severity and transmissibility; (2) characterize heterogeneities in transmission and their determinants; and (3) assess the effectiveness of different interventions. We differentiate data needs into individual-level data (e.g. a detailed list of reported cases), exposure data (e.g. identifying where/how cases may have been infected) and population-level data (e.g. size/demographics of the population(s) affected and when/where interventions were implemented). A remarkable amount of individual-level and exposure data was collected during the West African Ebola epidemic, which allowed the assessment of (1) and (2). However, gaps in population-level data (particularly around which interventions were applied when and where) posed challenges to the assessment of (3). Here we highlight recurrent data issues, give practical suggestions for addressing these issues and discuss priorities for improvements in data collection in future outbreaks. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’. |
format | Online Article Text |
id | pubmed-5394647 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-53946472017-04-24 Key data for outbreak evaluation: building on the Ebola experience Cori, Anne Donnelly, Christl A. Dorigatti, Ilaria Ferguson, Neil M. Fraser, Christophe Garske, Tini Jombart, Thibaut Nedjati-Gilani, Gemma Nouvellet, Pierre Riley, Steven Van Kerkhove, Maria D. Mills, Harriet L. Blake, Isobel M. Philos Trans R Soc Lond B Biol Sci Articles Following the detection of an infectious disease outbreak, rapid epidemiological assessment is critical for guiding an effective public health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gained in the West African Ebola epidemic and prior emerging infectious disease outbreaks to set out a checklist of data needed to: (1) quantify severity and transmissibility; (2) characterize heterogeneities in transmission and their determinants; and (3) assess the effectiveness of different interventions. We differentiate data needs into individual-level data (e.g. a detailed list of reported cases), exposure data (e.g. identifying where/how cases may have been infected) and population-level data (e.g. size/demographics of the population(s) affected and when/where interventions were implemented). A remarkable amount of individual-level and exposure data was collected during the West African Ebola epidemic, which allowed the assessment of (1) and (2). However, gaps in population-level data (particularly around which interventions were applied when and where) posed challenges to the assessment of (3). Here we highlight recurrent data issues, give practical suggestions for addressing these issues and discuss priorities for improvements in data collection in future outbreaks. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’. The Royal Society 2017-05-26 2017-04-10 /pmc/articles/PMC5394647/ /pubmed/28396480 http://dx.doi.org/10.1098/rstb.2016.0371 Text en © 2017 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Articles Cori, Anne Donnelly, Christl A. Dorigatti, Ilaria Ferguson, Neil M. Fraser, Christophe Garske, Tini Jombart, Thibaut Nedjati-Gilani, Gemma Nouvellet, Pierre Riley, Steven Van Kerkhove, Maria D. Mills, Harriet L. Blake, Isobel M. Key data for outbreak evaluation: building on the Ebola experience |
title | Key data for outbreak evaluation: building on the Ebola experience |
title_full | Key data for outbreak evaluation: building on the Ebola experience |
title_fullStr | Key data for outbreak evaluation: building on the Ebola experience |
title_full_unstemmed | Key data for outbreak evaluation: building on the Ebola experience |
title_short | Key data for outbreak evaluation: building on the Ebola experience |
title_sort | key data for outbreak evaluation: building on the ebola experience |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5394647/ https://www.ncbi.nlm.nih.gov/pubmed/28396480 http://dx.doi.org/10.1098/rstb.2016.0371 |
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