Dynamic distribution modeling of arboviral vesicular stomatitis and its vector, the biting midge (Culicoides spp.): two case studies

Vesicular stomatitis (VS) is a multi-vector arboviral disease that affects livestock and has a significant impact on agriculture in both the US and Mexico. Biting midges (Culicoides species) are known vectors of VS. Presence-only species distribution models (SDMs) provide a powerful and versatile tool for estimating both the habitat suitability of biting midges and the distribution of VS, the disease they spread. Such models can improve our understanding of Culicoides ecology, provide opportunities for more efficient VS surveillance and mitigation, and help determine geographical areas where VS is endemic or vulnerable to potential future transmission.

Here, we discuss two case studies related to modeling the distribution of VS and its insect vector. The first focused on predicting the habitat suitability of biting midges, including C. sonorensis and its close relatives (C. variipennis, C. albertensis, and C. occidentalis), based on species presence records collected in the past hundred years from various sources. The second study involved directly estimating the distribution of VS in Mexico, where we used occurrence data in the form of confirmed VS cases in livestock from 2005-2020 in historically endemic regions of Mexico.

SDMs are typically generated using temporally static input data. However, we improved the accuracy of our predictions by applying the Maxent algorithm to time-specific input data, creating dynamic species distribution models and habitat suitability maps. For both case studies, a robust dynamic Maxent distribution modeling workflow was implemented using temporally matched occurrence and environmental data that were carefully selected in collaboration with domain experts.