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Reconstructing unseen transmission events to infer dengue dynamics from viral sequences
For most pathogens, transmission is driven by interactions between the behaviours of infectious individuals, the behaviours of the wider population, the local environment, and immunity. Phylogeographic approaches are currently unable to disentangle the relative effects of these competing factors. We...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985522/ https://www.ncbi.nlm.nih.gov/pubmed/33753725 http://dx.doi.org/10.1038/s41467-021-21888-9 |
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author | Salje, Henrik Wesolowski, Amy Brown, Tyler S. Kiang, Mathew V. Berry, Irina Maljkovic Lefrancq, Noemie Fernandez, Stefan Jarman, Richard G. Ruchusatsawat, Kriangsak Iamsirithaworn, Sopon Vandepitte, Warunee P. Suntarattiwong, Piyarat Read, Jonathan M. Klungthong, Chonticha Thaisomboonsuk, Butsaya Engø-Monsen, Kenth Buckee, Caroline Cauchemez, Simon Cummings, Derek A. T. |
author_facet | Salje, Henrik Wesolowski, Amy Brown, Tyler S. Kiang, Mathew V. Berry, Irina Maljkovic Lefrancq, Noemie Fernandez, Stefan Jarman, Richard G. Ruchusatsawat, Kriangsak Iamsirithaworn, Sopon Vandepitte, Warunee P. Suntarattiwong, Piyarat Read, Jonathan M. Klungthong, Chonticha Thaisomboonsuk, Butsaya Engø-Monsen, Kenth Buckee, Caroline Cauchemez, Simon Cummings, Derek A. T. |
author_sort | Salje, Henrik |
collection | PubMed |
description | For most pathogens, transmission is driven by interactions between the behaviours of infectious individuals, the behaviours of the wider population, the local environment, and immunity. Phylogeographic approaches are currently unable to disentangle the relative effects of these competing factors. We develop a spatiotemporally structured phylogenetic framework that addresses these limitations by considering individual transmission events, reconstructed across spatial scales. We apply it to geocoded dengue virus sequences from Thailand (N = 726 over 18 years). We find infected individuals spend 96% of their time in their home community compared to 76% for the susceptible population (mainly children) and 42% for adults. Dynamic pockets of local immunity make transmission more likely in places with high heterotypic immunity and less likely where high homotypic immunity exists. Age-dependent mixing of individuals and vector distributions are not important in determining spread. This approach provides previously unknown insights into one of the most complex disease systems known and will be applicable to other pathogens. |
format | Online Article Text |
id | pubmed-7985522 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79855222021-04-16 Reconstructing unseen transmission events to infer dengue dynamics from viral sequences Salje, Henrik Wesolowski, Amy Brown, Tyler S. Kiang, Mathew V. Berry, Irina Maljkovic Lefrancq, Noemie Fernandez, Stefan Jarman, Richard G. Ruchusatsawat, Kriangsak Iamsirithaworn, Sopon Vandepitte, Warunee P. Suntarattiwong, Piyarat Read, Jonathan M. Klungthong, Chonticha Thaisomboonsuk, Butsaya Engø-Monsen, Kenth Buckee, Caroline Cauchemez, Simon Cummings, Derek A. T. Nat Commun Article For most pathogens, transmission is driven by interactions between the behaviours of infectious individuals, the behaviours of the wider population, the local environment, and immunity. Phylogeographic approaches are currently unable to disentangle the relative effects of these competing factors. We develop a spatiotemporally structured phylogenetic framework that addresses these limitations by considering individual transmission events, reconstructed across spatial scales. We apply it to geocoded dengue virus sequences from Thailand (N = 726 over 18 years). We find infected individuals spend 96% of their time in their home community compared to 76% for the susceptible population (mainly children) and 42% for adults. Dynamic pockets of local immunity make transmission more likely in places with high heterotypic immunity and less likely where high homotypic immunity exists. Age-dependent mixing of individuals and vector distributions are not important in determining spread. This approach provides previously unknown insights into one of the most complex disease systems known and will be applicable to other pathogens. Nature Publishing Group UK 2021-03-22 /pmc/articles/PMC7985522/ /pubmed/33753725 http://dx.doi.org/10.1038/s41467-021-21888-9 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Salje, Henrik Wesolowski, Amy Brown, Tyler S. Kiang, Mathew V. Berry, Irina Maljkovic Lefrancq, Noemie Fernandez, Stefan Jarman, Richard G. Ruchusatsawat, Kriangsak Iamsirithaworn, Sopon Vandepitte, Warunee P. Suntarattiwong, Piyarat Read, Jonathan M. Klungthong, Chonticha Thaisomboonsuk, Butsaya Engø-Monsen, Kenth Buckee, Caroline Cauchemez, Simon Cummings, Derek A. T. Reconstructing unseen transmission events to infer dengue dynamics from viral sequences |
title | Reconstructing unseen transmission events to infer dengue dynamics from viral sequences |
title_full | Reconstructing unseen transmission events to infer dengue dynamics from viral sequences |
title_fullStr | Reconstructing unseen transmission events to infer dengue dynamics from viral sequences |
title_full_unstemmed | Reconstructing unseen transmission events to infer dengue dynamics from viral sequences |
title_short | Reconstructing unseen transmission events to infer dengue dynamics from viral sequences |
title_sort | reconstructing unseen transmission events to infer dengue dynamics from viral sequences |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985522/ https://www.ncbi.nlm.nih.gov/pubmed/33753725 http://dx.doi.org/10.1038/s41467-021-21888-9 |
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