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Forecasting Outbreaks of Hantaviral Disease: Future Directions in Geospatial Modeling

Hantaviral diseases have been recognized as ‘place diseases’ from their earliest identification and, epidemiologically, are tied to single host species with transmission occurring from infectious hosts to humans. As such, human populations are most at risk when they are in physical proximity to suit...

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Detalles Bibliográficos
Autor principal: Glass, Gregory E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383283/
https://www.ncbi.nlm.nih.gov/pubmed/37515149
http://dx.doi.org/10.3390/v15071461
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author Glass, Gregory E.
author_facet Glass, Gregory E.
author_sort Glass, Gregory E.
collection PubMed
description Hantaviral diseases have been recognized as ‘place diseases’ from their earliest identification and, epidemiologically, are tied to single host species with transmission occurring from infectious hosts to humans. As such, human populations are most at risk when they are in physical proximity to suitable habitats for reservoir populations, when numbers of infectious hosts are greatest. Because of the lags between improving habitat conditions and increasing infectious host abundance and spillover to humans, it should be possible to anticipate (forecast) where and when outbreaks will most likely occur. Most mammalian hosts are associated with specific habitat requirements, so identifying these habitats and the ecological drivers that impact population growth and the dispersal of viral hosts should be markers of the increased risk for disease outbreaks. These regions could be targeted for public health and medical education. This paper outlines the rationale for forecasting zoonotic outbreaks, and the information that needs to be clarified at various levels of biological organization to make the forecasting of orthohantaviruses successful. Major challenges reflect the transdisciplinary nature of forecasting zoonoses, with needs to better understand the implications of the data collected, how collections are designed, and how chosen methods impact the interpretation of results.
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spelling pubmed-103832832023-07-30 Forecasting Outbreaks of Hantaviral Disease: Future Directions in Geospatial Modeling Glass, Gregory E. Viruses Perspective Hantaviral diseases have been recognized as ‘place diseases’ from their earliest identification and, epidemiologically, are tied to single host species with transmission occurring from infectious hosts to humans. As such, human populations are most at risk when they are in physical proximity to suitable habitats for reservoir populations, when numbers of infectious hosts are greatest. Because of the lags between improving habitat conditions and increasing infectious host abundance and spillover to humans, it should be possible to anticipate (forecast) where and when outbreaks will most likely occur. Most mammalian hosts are associated with specific habitat requirements, so identifying these habitats and the ecological drivers that impact population growth and the dispersal of viral hosts should be markers of the increased risk for disease outbreaks. These regions could be targeted for public health and medical education. This paper outlines the rationale for forecasting zoonotic outbreaks, and the information that needs to be clarified at various levels of biological organization to make the forecasting of orthohantaviruses successful. Major challenges reflect the transdisciplinary nature of forecasting zoonoses, with needs to better understand the implications of the data collected, how collections are designed, and how chosen methods impact the interpretation of results. MDPI 2023-06-28 /pmc/articles/PMC10383283/ /pubmed/37515149 http://dx.doi.org/10.3390/v15071461 Text en © 2023 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Perspective
Glass, Gregory E.
Forecasting Outbreaks of Hantaviral Disease: Future Directions in Geospatial Modeling
title Forecasting Outbreaks of Hantaviral Disease: Future Directions in Geospatial Modeling
title_full Forecasting Outbreaks of Hantaviral Disease: Future Directions in Geospatial Modeling
title_fullStr Forecasting Outbreaks of Hantaviral Disease: Future Directions in Geospatial Modeling
title_full_unstemmed Forecasting Outbreaks of Hantaviral Disease: Future Directions in Geospatial Modeling
title_short Forecasting Outbreaks of Hantaviral Disease: Future Directions in Geospatial Modeling
title_sort forecasting outbreaks of hantaviral disease: future directions in geospatial modeling
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383283/
https://www.ncbi.nlm.nih.gov/pubmed/37515149
http://dx.doi.org/10.3390/v15071461
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