Integrating Wind Speed into Climate-Based West Nile Virus Models: A Comparative Analysis in Two Distinct Regions

Since its introduction to North America in 1999, West Nile virus (WNV) has become the most significant mosquito-borne disease in the United States. Climatic conditions significantly influence transmission dynamics. While temperature, precipitation, and humidity are known to affect mosquito populations and virus replication, wind speed is often neglected in transmission models despite its potential to alter mosquito behavior and facilitate virus dispersal. This study incorporates wind speed into climate-based WNV models to compare its effects in Louisiana and South Dakota regions with contrasting climates, land cover, and vector and host species. From 2004 to 2022, we analyzed weekly WNV human case data alongside daily meteorological data. The climate variables were modeled using logistic regression with distributed lag effects. Incorporating wind speed consistently enhanced the performance of climate-based models across both states, as evidenced by improved Akaike Information Criterion values. Higher-than-normal wind speeds were associated with decreased WNV cases over specific lag periods, suggesting that increased wind speed may inhibit mosquito activity and reduce virus transmission. Differences in how temperature and moisture-related variables influenced the two regions highlight the importance of considering regional climatic contexts. These findings show that incorporating wind speed into WNV transmission models can be highly beneficial and reinforce the need to consider a broader range of climatic factors beyond temperature, precipitation, and humidity. Understanding these regional variations is essential for capturing local climatic influences on disease transmission, which is crucial for developing more targeted and effective public health strategies.