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Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling
Hantaviruses are zoonotic hemorrhagic fever viruses for which prevention of human spillover remains the first priority in disease management. Tailored intervention measures require an understanding of the drivers of enzootic dynamics, commonly inferred from distorted human incidence data. Here, we u...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6476162/ https://www.ncbi.nlm.nih.gov/pubmed/31024739 http://dx.doi.org/10.1093/ve/vez009 |
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author | Laenen, Lies Vergote, Valentijn Vanmechelen, Bert Tersago, Katrien Baele, Guy Lemey, Philippe Leirs, Herwig Dellicour, Simon Vrancken, Bram Maes, Piet |
author_facet | Laenen, Lies Vergote, Valentijn Vanmechelen, Bert Tersago, Katrien Baele, Guy Lemey, Philippe Leirs, Herwig Dellicour, Simon Vrancken, Bram Maes, Piet |
author_sort | Laenen, Lies |
collection | PubMed |
description | Hantaviruses are zoonotic hemorrhagic fever viruses for which prevention of human spillover remains the first priority in disease management. Tailored intervention measures require an understanding of the drivers of enzootic dynamics, commonly inferred from distorted human incidence data. Here, we use longitudinal sampling of approximately three decades of Puumala orthohantavirus (PUUV) evolution in isolated reservoir populations to estimate PUUV evolutionary rates, and apply these to study the impact of environmental factors on viral spread. We find that PUUV accumulates genetic changes at a rate of ∼10(−4) substitutions per site per year and that land cover type defines the dispersal dynamics of PUUV, with forests facilitating and croplands impeding virus spread. By providing reliable short-term PUUV evolutionary rate estimates, this work facilitates the evaluation of spatial risk heterogeneity starting from timed phylogeographic reconstructions based on virus sampling in its animal reservoir, thereby side-stepping the need for difficult-to-collect human disease incidence data. |
format | Online Article Text |
id | pubmed-6476162 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-64761622019-04-25 Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling Laenen, Lies Vergote, Valentijn Vanmechelen, Bert Tersago, Katrien Baele, Guy Lemey, Philippe Leirs, Herwig Dellicour, Simon Vrancken, Bram Maes, Piet Virus Evol Research Article Hantaviruses are zoonotic hemorrhagic fever viruses for which prevention of human spillover remains the first priority in disease management. Tailored intervention measures require an understanding of the drivers of enzootic dynamics, commonly inferred from distorted human incidence data. Here, we use longitudinal sampling of approximately three decades of Puumala orthohantavirus (PUUV) evolution in isolated reservoir populations to estimate PUUV evolutionary rates, and apply these to study the impact of environmental factors on viral spread. We find that PUUV accumulates genetic changes at a rate of ∼10(−4) substitutions per site per year and that land cover type defines the dispersal dynamics of PUUV, with forests facilitating and croplands impeding virus spread. By providing reliable short-term PUUV evolutionary rate estimates, this work facilitates the evaluation of spatial risk heterogeneity starting from timed phylogeographic reconstructions based on virus sampling in its animal reservoir, thereby side-stepping the need for difficult-to-collect human disease incidence data. Oxford University Press 2019-04-22 /pmc/articles/PMC6476162/ /pubmed/31024739 http://dx.doi.org/10.1093/ve/vez009 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Research Article Laenen, Lies Vergote, Valentijn Vanmechelen, Bert Tersago, Katrien Baele, Guy Lemey, Philippe Leirs, Herwig Dellicour, Simon Vrancken, Bram Maes, Piet Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling |
title | Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling |
title_full | Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling |
title_fullStr | Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling |
title_full_unstemmed | Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling |
title_short | Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling |
title_sort | identifying the patterns and drivers of puumala hantavirus enzootic dynamics using reservoir sampling |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6476162/ https://www.ncbi.nlm.nih.gov/pubmed/31024739 http://dx.doi.org/10.1093/ve/vez009 |
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