Predicting Abundances of Aedes mcintoshi, a primary Rift Valley fever virus mosquito vector.

ABSTRACT: Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic arbovirus with important livestock and human health, and economic consequences across Africa and the Arabian Peninsula. Climate and vegetation monitoring guide RVFV forecasting models and early warning systems; however, these approaches make monthly predictions and a need exists to predict primary vector abundances at finer temporal scales. In Kenya, an important primary RVFV vector is the mosquito Aedes mcintoshi. We used a zero-inflated negative binomial regression and multimodel averaging approach with georeferenced Ae. mcintoshi mosquito counts and remotely sensed climate and topographic variables to predict where and when abundances would be high in Kenya and western Somalia. The data supported a positive effect on abundance

SUBMITTER: Campbell LP 

PROVIDER: S-EPMC6917266 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature