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Abstract BackgroundCache Valley virus (CVV) is an understudiedOrthobunyaviruswith 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. MethodsWe 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. ResultsCVV 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 identifiedAedes vexans,Culiseta inornata, andCulex tarsalisas the most likely vectors andOdocoileus virginianus(white-tailed deer) as the most likely host sustaining sylvatic transmission. ConclusionsCVV 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
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Trends in mosquito species distribution modeling: insights for vector surveillance and disease control
Abstract Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they relate to infectious disease vectors. Here, we conducted a systematic review of the scientific literature, screening 563 abstracts and identifying 204 studies that used SDMs to produce distribution estimates for mosquito species. While the number of studies employing SDM methods has increased markedly over the past decade, the overwhelming majority used a single method (maximum entropy modeling; MaxEnt) and focused on human infectious disease vectors or their close relatives. The majority of regional models were developed for areas in Africa and Asia, while more localized modeling efforts were most common for North America and Europe. Findings from this study highlight gaps in taxonomic, geographic, and methodological foci of current SDM literature for mosquitoes that can guide future efforts to study the geography of mosquito-borne disease risk. Graphical Abstract
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- PAR ID:
- 10448090
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Parasites & Vectors
- Volume:
- 16
- Issue:
- 1
- ISSN:
- 1756-3305
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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