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Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji
Dengue is a major health burden, but it can be challenging to examine transmission and evaluate control measures because outbreaks depend on multiple factors, including human population structure, prior immunity and climate. We combined population-representative paired sera collected before and afte...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6092126/ https://www.ncbi.nlm.nih.gov/pubmed/30103854 http://dx.doi.org/10.7554/eLife.34848 |
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author | Kucharski, Adam J Kama, Mike Watson, Conall H Aubry, Maite Funk, Sebastian Henderson, Alasdair D Brady, Oliver J Vanhomwegen, Jessica Manuguerra, Jean-Claude Lau, Colleen L Edmunds, W John Aaskov, John Nilles, Eric James Cao-Lormeau, Van-Mai Hué, Stéphane Hibberd, Martin L |
author_facet | Kucharski, Adam J Kama, Mike Watson, Conall H Aubry, Maite Funk, Sebastian Henderson, Alasdair D Brady, Oliver J Vanhomwegen, Jessica Manuguerra, Jean-Claude Lau, Colleen L Edmunds, W John Aaskov, John Nilles, Eric James Cao-Lormeau, Van-Mai Hué, Stéphane Hibberd, Martin L |
author_sort | Kucharski, Adam J |
collection | PubMed |
description | Dengue is a major health burden, but it can be challenging to examine transmission and evaluate control measures because outbreaks depend on multiple factors, including human population structure, prior immunity and climate. We combined population-representative paired sera collected before and after the 2013/14 dengue-3 outbreak in Fiji with surveillance data to determine how such factors influence transmission and control in island settings. Our results suggested the 10–19 year-old age group had the highest risk of infection, but we did not find strong evidence that other demographic or environmental risk factors were linked to seroconversion. A mathematical model jointly fitted to surveillance and serological data suggested that herd immunity and seasonally varying transmission could not explain observed dynamics. However, the model showed evidence of an additional reduction in transmission coinciding with a vector clean-up campaign, which may have contributed to the decline in cases in the later stages of the outbreak. |
format | Online Article Text |
id | pubmed-6092126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-60921262018-08-16 Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji Kucharski, Adam J Kama, Mike Watson, Conall H Aubry, Maite Funk, Sebastian Henderson, Alasdair D Brady, Oliver J Vanhomwegen, Jessica Manuguerra, Jean-Claude Lau, Colleen L Edmunds, W John Aaskov, John Nilles, Eric James Cao-Lormeau, Van-Mai Hué, Stéphane Hibberd, Martin L eLife Epidemiology and Global Health Dengue is a major health burden, but it can be challenging to examine transmission and evaluate control measures because outbreaks depend on multiple factors, including human population structure, prior immunity and climate. We combined population-representative paired sera collected before and after the 2013/14 dengue-3 outbreak in Fiji with surveillance data to determine how such factors influence transmission and control in island settings. Our results suggested the 10–19 year-old age group had the highest risk of infection, but we did not find strong evidence that other demographic or environmental risk factors were linked to seroconversion. A mathematical model jointly fitted to surveillance and serological data suggested that herd immunity and seasonally varying transmission could not explain observed dynamics. However, the model showed evidence of an additional reduction in transmission coinciding with a vector clean-up campaign, which may have contributed to the decline in cases in the later stages of the outbreak. eLife Sciences Publications, Ltd 2018-08-14 /pmc/articles/PMC6092126/ /pubmed/30103854 http://dx.doi.org/10.7554/eLife.34848 Text en © 2018, Kucharski et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Epidemiology and Global Health Kucharski, Adam J Kama, Mike Watson, Conall H Aubry, Maite Funk, Sebastian Henderson, Alasdair D Brady, Oliver J Vanhomwegen, Jessica Manuguerra, Jean-Claude Lau, Colleen L Edmunds, W John Aaskov, John Nilles, Eric James Cao-Lormeau, Van-Mai Hué, Stéphane Hibberd, Martin L Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji |
title | Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji |
title_full | Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji |
title_fullStr | Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji |
title_full_unstemmed | Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji |
title_short | Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji |
title_sort | using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in fiji |
topic | Epidemiology and Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6092126/ https://www.ncbi.nlm.nih.gov/pubmed/30103854 http://dx.doi.org/10.7554/eLife.34848 |
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