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Partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern Atlantic, June 2013–2014

Morbilliviruses cause major mortality in marine mammals, but the dynamics of transmission and persistence are ill understood compared to terrestrial counterparts such as measles; this is especially true for epidemics in cetaceans. However, the recent outbreak of dolphin morbillivirus in the northwes...

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Autores principales: Morris, Sinead E., Zelner, Jonathan L., Fauquier, Deborah A., Rowles, Teresa K., Rosel, Patricia E., Gulland, Frances, Grenfell, Bryan T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4685842/
https://www.ncbi.nlm.nih.gov/pubmed/26577594
http://dx.doi.org/10.1098/rsif.2015.0676
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author Morris, Sinead E.
Zelner, Jonathan L.
Fauquier, Deborah A.
Rowles, Teresa K.
Rosel, Patricia E.
Gulland, Frances
Grenfell, Bryan T.
author_facet Morris, Sinead E.
Zelner, Jonathan L.
Fauquier, Deborah A.
Rowles, Teresa K.
Rosel, Patricia E.
Gulland, Frances
Grenfell, Bryan T.
author_sort Morris, Sinead E.
collection PubMed
description Morbilliviruses cause major mortality in marine mammals, but the dynamics of transmission and persistence are ill understood compared to terrestrial counterparts such as measles; this is especially true for epidemics in cetaceans. However, the recent outbreak of dolphin morbillivirus in the northwestern Atlantic Ocean can provide new insights into the epidemiology and spatio-temporal spread of this pathogen. To deal with uncertainties surrounding the ecology of this system (only stranded animals were observed), we develop a statistical framework that can extract key information about the underlying transmission process given only sparse data. Our self-exciting Poisson process model suggests that individuals are infectious for at most 24 days and can transfer infection up to two latitude degrees (220 km) within this time. In addition, the effective reproduction number is generally below one, but reaches 2.6 during a period of heightened stranding numbers near Virginia Beach, Virginia, in summer 2013. Network analysis suggests local movements dominate spatial spread, with seasonal migration facilitating wider dissemination along the coast. Finally, a low virus transmission rate or high levels of pre-existing immunity can explain the lack of viral spread into the Gulf of Mexico. More generally, our approach illustrates novel methodologies for analysing very indirectly observed epidemics.
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spelling pubmed-46858422016-01-04 Partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern Atlantic, June 2013–2014 Morris, Sinead E. Zelner, Jonathan L. Fauquier, Deborah A. Rowles, Teresa K. Rosel, Patricia E. Gulland, Frances Grenfell, Bryan T. J R Soc Interface Research Articles Morbilliviruses cause major mortality in marine mammals, but the dynamics of transmission and persistence are ill understood compared to terrestrial counterparts such as measles; this is especially true for epidemics in cetaceans. However, the recent outbreak of dolphin morbillivirus in the northwestern Atlantic Ocean can provide new insights into the epidemiology and spatio-temporal spread of this pathogen. To deal with uncertainties surrounding the ecology of this system (only stranded animals were observed), we develop a statistical framework that can extract key information about the underlying transmission process given only sparse data. Our self-exciting Poisson process model suggests that individuals are infectious for at most 24 days and can transfer infection up to two latitude degrees (220 km) within this time. In addition, the effective reproduction number is generally below one, but reaches 2.6 during a period of heightened stranding numbers near Virginia Beach, Virginia, in summer 2013. Network analysis suggests local movements dominate spatial spread, with seasonal migration facilitating wider dissemination along the coast. Finally, a low virus transmission rate or high levels of pre-existing immunity can explain the lack of viral spread into the Gulf of Mexico. More generally, our approach illustrates novel methodologies for analysing very indirectly observed epidemics. The Royal Society 2015-11-06 /pmc/articles/PMC4685842/ /pubmed/26577594 http://dx.doi.org/10.1098/rsif.2015.0676 Text en © 2015 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 Research Articles
Morris, Sinead E.
Zelner, Jonathan L.
Fauquier, Deborah A.
Rowles, Teresa K.
Rosel, Patricia E.
Gulland, Frances
Grenfell, Bryan T.
Partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern Atlantic, June 2013–2014
title Partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern Atlantic, June 2013–2014
title_full Partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern Atlantic, June 2013–2014
title_fullStr Partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern Atlantic, June 2013–2014
title_full_unstemmed Partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern Atlantic, June 2013–2014
title_short Partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern Atlantic, June 2013–2014
title_sort partially observed epidemics in wildlife hosts: modelling an outbreak of dolphin morbillivirus in the northwestern atlantic, june 2013–2014
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4685842/
https://www.ncbi.nlm.nih.gov/pubmed/26577594
http://dx.doi.org/10.1098/rsif.2015.0676
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