West Nile virus is the most significant arbovirus in the United States
in terms of both morbidity and mortality. West Nile exists in a complex
transmission cycle between avian hosts and the arthropod vector, Culex
spp. mosquitoes. Human spillover events occur when humans are in close
proximity to vector populations with high rates of infection. Predicting
these rates of infection and therefore the risk to humans is not
straightforward. In this study, we evaluate the hydrological and
meteorological drivers associated with mosquito biology and viral
development to determine if these associations can be used to forecast
seasonal West Nile risk in the Coachella Valley of California. To test
this, we developed and tested a spatially-resolved ensemble forecast
model of West Nile virus transmission in the Coachella Valley using 17
years of mosquito surveillance data and NLDAS-2 environmental data. Our
multi-model inference system indicated that the combination of a cooler
and dryer winter followed by a wetter and warmer spring and a cooler
than normal summer was most predictive of West Nile positive mosquitoes
in the Coachella Valley. The ability to make accurate early season
predictions of West Nile risk could allow local abatement districts and
public health entities to implement early season interventions such as
targeted adulticiding and public messaging before human transmission
occurs. Such early and targeted interventions could better mitigate the
risk of West Nile virus to humans in the Coachella Valley.