Data-Driven Modeling to Assess Receptivity for Rift Valley Fever Virus

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Abstract

Rift Valley Fever virus (RVFV) is an enzootic virus that causes extensive morbidity and mortality in domestic ruminants in Africa, and it has shown the potential to invade other areas such as the Arabian Peninsula. Here, we develop methods for linking mathematical models to real-world data that could be used for continent-scale risk assessment given adequate data on local host and vector populations. We have applied the methods to a well-studied agricultural region of California with w1 million dairy cattle, abundant and competent mosquito vectors, and a permissive climate that has enabled consistent transmission of West Nile virus and historically other arboviruses. Our results suggest that RVFV outbreaks could

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Barker, C. M., Niu, T., Reisen, W. K., & Hartley, D. M. (2013). Data-Driven Modeling to Assess Receptivity for Rift Valley Fever Virus. PLoS Neglected Tropical Diseases, 7(11). https://doi.org/10.1371/journal.pntd.0002515

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