1. Ecology and geography of Cache Valley virus assessed using ecological niche modeling
- Author
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John A. Muller, Krisangel López, Luis E. Escobar, and Albert J. Auguste
- Subjects
Cache Valley virus ,Ecological niche modeling ,White-tailed deer ,Mosquito ,Vector ,Infectious and parasitic diseases ,RC109-216 - Abstract
Abstract Background Cache Valley virus (CVV) is an understudied Orthobunyavirus with a high spillover transmission potential due to its wide geographical distribution and large number of associated hosts and vectors. Although CVV is known to be widely distributed throughout North America, no studies have explored its geography or employed computational methods to explore the mammal and mosquito species likely participating in the CVV sylvatic cycle. Methods We used a literature review and online databases to compile locality data for CVV and its potential vectors and hosts. We linked location data points with climatic data via ecological niche modeling to estimate the geographical range of CVV and hotspots of transmission risk. We used background similarity tests to identify likely CVV mosquito vectors and mammal hosts to detect ecological signals from CVV sylvatic transmission. Results CVV distribution maps revealed a widespread potential viral occurrence throughout North America. Ecological niche models identified areas with climate, vectors, and hosts suitable to maintain CVV transmission. Our background similarity tests identified Aedes vexans, Culiseta inornata, and Culex tarsalis as the most likely vectors and Odocoileus virginianus (white-tailed deer) as the most likely host sustaining sylvatic transmission. Conclusions CVV has a continental-level, widespread transmission potential. Large areas of North America have suitable climate, vectors, and hosts for CVV emergence, establishment, and spread. We identified geographical hotspots that have no confirmed CVV reports to date and, in view of CVV misdiagnosis or underreporting, can guide future surveillance to specific localities and species. Graphical Abstract
- Published
- 2024
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