2020 ESA Annual Meeting (August 3 - 6)

PS 9 Abstract - Risks and rewards of vaccination during Rift Valley Fever epizootics

Ola Weinbaum1, Helen J. Wearing2, Quincy D. Harris1 and Rebecca C. Christofferson3, (1)Biology, University of New Mexico, Albuquerque, NM, (2)Department of Biology and Department of Mathematics & Statistics, University of New Mexico, Albuquerque, NM, (3)Pathobiological Sciences, Louisiana State University, Baton Rouge, LA
Background/Question/Methods

Rift Valley Fever Virus is an emerging mosquito-borne zoonosis that can cause severe disease in livestock and humans. The virus persists in wild ruminants and Aedes sp., but epizootics are precipitated by surges in Culex sp. vectors with cattle acting as the amplifying hosts. Culex sp. populations only surge after extended periods of heavy rain that do not regularly occur. Live-attenuated vaccines only require a single application, are not transmitted by vectors, and have been the preferred agricultural choice for decades, but they bear some increased risk of reassortment compared to inactivated vaccines. Reassortment of this virus between wildtype and live-attenuated vaccine strains has been documented, which caused the World Health Organization to recommend against live-attenuated vaccine use during epizootics. Here, we focus on the Culex sp.-cattle interaction and develop a mathematical model (in a differential equations framework) to quantify the relative incidence of coinfection when a live-attenuated vaccine is introduced at different timepoints during an epizootic.

Results/Conclusions

Although the specific incidence of coinfection is contingent on which live-attenuated vaccine is used, incidence of coinfection is always small relative to incidence of single infection. Low incidence of coinfection provides little opportunity for reassortment. Cumulative infections are greatly reduced by live-attenuated vaccine introduction during the course of an epizootic. We identify temporal windows of opportunity (specifically, before the epizootic peak) that maximize infection prevention and minimize opportunity for reassortment. These results imply that attempting to entirely prevent virus strain interaction may be short-sighted. We show that it is both possible and informative to quantify the risks of such interaction before making policy decisions.