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Models that forecast the timing and location of human arboviral disease have the potential to make mosquito control and disease prevention more effective. A common approach is to use statistical time-series models that predict disease cases as lagged functions of environmental variables. However, the simplifying assumptions required for standard modeling approaches may not capture important aspects of complex, non-linear transmission cycles. Here, we compared a set of alternative models of human West Nile virus (WNV) in 2004-2017 in South Dakota, USA. We used county-level logistic regressions to model historical human case data as functions of distributed lag summaries of air temperature and several moisture indices. We tested two variations of the standard model in which 1) the distributed lag functions were allowed to change over the transmission season, so that dependence on past meteorological conditions was time varying rather than static, and 2) an additional predictor was included that quantified the mosquito infection growth rate estimated from mosquito surveillance data. The best-fitting model included temperature and vapor pressure deficit as meteorological predictors, and also incorporated time-varying lags and the mosquito infection growth rate. The time-varying lags helped to predict the seasonal pattern of WNV cases, whereas the mosquito infection growth rate improved the prediction of year-to-year variability in WNV risk. These relatively simple and practical enhancements may be particularly helpful for developing data-driven time series models for use in arbovirus forecasting applications., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Despite a cold temperate climate and low human population density, the Northern Great Plains has become a persistent hot spot for human West Nile virus (WNV) disease in North America. Understanding the spatial and temporal patterns of WNV can provide insights into the epidemiological and ecological factors that influence disease emergence and persistence. We analyzed the 1,962 cases of human WNV disease that occurred in South Dakota from 2002-2012 to identify the geographic distribution, seasonal cycles, and interannual variability of disease risk. The geographic and seasonal patterns of WNV have changed since the invasion and initial epidemic in 2002-2003, with cases shifting toward the eastern portion of South Dakota and occurring earlier in the transmission season in more recent years. WNV cases were temporally autocorrelated at lags of up to six weeks and early season cumulative case numbers were correlated with seasonal totals, indicating the possibility of using these data for short-term early detection of outbreaks. Epidemiological data are likely to be most effective for early warning of WNV virus outbreaks if they are integrated with entomological surveillance and environmental monitoring to leverage the strengths and minimize the weaknesses of each information source.

Background: The incidence of West Nile virus (WNv) has remained high in the northern Great Plains compared to the rest of the United States. However, the reasons for the sustained high risk of WNv transmission in this region have not been determined. To assess the environmental drivers of WNv in the northern Great Plains, we analyzed the county-level spatial pattern of human cases during the 2003 epidemic across a seven-state region., Methodology/principal Findings: County-level data on WNv cases were examined using spatial cluster analysis, and were used to fit statistical models with weather, climate, and land use variables as predictors. In 2003 there was a single large cluster of elevated WNv risk encompassing North Dakota, South Dakota, and Nebraska along with portions of eastern Montana and Wyoming. The relative risk of WNv remained high within the boundaries of this cluster from 2004-2007. WNv incidence during the 2003 epidemic was found to have a stronger relationship with long-term climate patterns than with annual weather in either 2002 or 2003. WNv incidence increased with mean May-July temperature and had a unimodal relationship with total May-July precipitation. WNv incidence also increased with the percentage of irrigated cropland and with the percentage of the human population living in rural areas., Conclusions/significance: The spatial pattern of WNv cases during the 2003 epidemic in the northern Great Plains was associated with both climatic gradients and land use patterns. These results were interpreted as evidence that environmental conditions across much of the northern Great Plains create a favorable ecological niche for Culex tarsalis, a particularly efficient vector of WNv. Further research is needed to determine the proximal causes of sustained WNv transmission and to enhance strategies for disease prevention.