The influence of bat ecology on viral diversity and reservoir status.
Chiroptera
infectious disease forecasting
machine learning
pathogen diversity
viruses
zoonotic disease
Journal
Ecology and evolution
ISSN: 2045-7758
Titre abrégé: Ecol Evol
Pays: England
ID NLM: 101566408
Informations de publication
Date de publication:
Jun 2020
Jun 2020
Historique:
received:
15
02
2020
accepted:
21
03
2020
entrez:
2
7
2020
pubmed:
2
7
2020
medline:
2
7
2020
Statut:
epublish
Résumé
Repeated emergence of zoonotic viruses from bat reservoirs into human populations demands predictive approaches to preemptively identify virus-carrying bat species. Here, we use machine learning to examine drivers of viral diversity in bats, determine whether those drivers depend on viral genome type, and predict undetected viral carriers. Our results indicate that bat species with longer life spans, broad geographic distributions in the eastern hemisphere, and large group sizes carry more viruses overall. Life span was a stronger predictor of deoxyribonucleic acid viral diversity, while group size and family were more important for predicting ribonucleic acid viruses, potentially reflecting broad differences in infection duration. Importantly, our models predict 54 bat species as likely carriers of zoonotic viruses, despite not currently being considered reservoirs. Mapping these predictions as a proportion of local bat diversity, we identify global regions where efforts to reduce disease spillover into humans by identifying viral carriers may be most productive.
Identifiants
pubmed: 32607188
doi: 10.1002/ece3.6315
pii: ECE36315
pmc: PMC7319232
doi:
Types de publication
Journal Article
Langues
eng
Pagination
5748-5758Informations de copyright
© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
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