Application of a degree-day model of West Nile virus transmission risk to the East Coast of the United States of America.

A geographical information systems model that identifies regions of the United States of America (USA) susceptible to West Nile virus (WNV) transmission risk is presented. This system has previously been calibrated and tested in the western USA; in this paper we use datasets of WNV-killed birds from South Carolina and Connecticut to test the model in the eastern USA. Because their response to WNV infection is highly predictable, American crows were chosen as the primary source for model calibration and testing. Where crow data are absent, other birds are shown to be an effective substitute. Model results show that the same calibrated model demonstrated to work in the western USA has the same predictive ability in the eastern USA, allowing for a continental-scale evaluation of the transmission risk of WNV at a daily time step. The calibrated model is independent of mosquito species and requires inputs of only local maximum and minimum temperatures. Of benefit to the general public and vector control districts, the model predicts the onset of seasonal transmission risk, although it is less effective at identifying the end of the transmission risk season.