Predicting seasonal abundance of mosquitoes based on off-season meteorological conditions

Modeling mosquito population dynamics has become an important part of understanding the transmission of mosquito-borne arboviruses. Of these models, those including meteorological variables have mainly focused on conditions during or immediately preceding the mosquito breeding season. While these conditions are clearly critical biologically and statistically, it is also biologically plausible that conditions during the off-season may contribute to interannual variation in mosquito population size. To examine the effect of off-season factors, we develop a pair of Poisson regression models for July captures of Aedes sollicitans and Culex salinarius, two East Coast vector species of arboviruses including Eastern equine encephalitis virus and West Nile virus. Model results indicate that average maximum temperature, total heating degree-days, and the total number of days with a minimum temperature below freezing during the winter months was predictive of mosquito populations. In addition, the average maximum relative humidity from the preceding fall and total rainfall and total heating degree-days during the preceding spring were also associated with vector population dynamics. The descriptive and predictive power of these models is discussed.