West Nile Virus Risk Research Articles

Short-term Forecasting of Daily Abundance of West Nile Virus Vectors Culex pipiens-restuans (Diptera: Culicidae) and Aedes vexans Based on Weather Conditions in Southern Québec (Canada).

Since 2002, human cases of West Nile virus (WNV) have occurred every year in southern Canada, but WNV risk remains challenging to predict. Here, we explored the ability of weather-based forecasting models to predict the seasonal abundance of two WNV vector species (Culex pipiens-restuans and Aedes vexans) in Québec, Canada, and explored the importance of accounting for larvicide use and local habitat (forest park vs residential garden). A gamma-generalized linear model predicting mosquito abundance was developed based on an approach previously used in Ontario combining temperature and precipitation during the days preceding mosquito captures. This model was calibrated and validated for each species with independent entomological datasets from the Montréal region collected in 2013 and 2014. Culex pipiens-restuans abundance was associated with mean degree days (dd; >9°C) over the 22 d before mosquito capture and with mean precipitation over the 71 d before capture; Ae. vexans abundance with the mean dd (>12°C) over the 24 d before capture and mean precipitation over the 30 d before capture. These results are consistent with temperature effects on immature development rates and adult activity, and effects of precipitation on the abundance and suitability of breeding sites. Taking into account larvicide use and habitat significantly improved the predictions. This study provides evidence that weather conditions can yield robust short-term predictions of the regional daily mosquito abundance, particularly when accounting for local variation in habitat or mosquito control efforts, and may provide real-time indicators of WNV or other mosquito-borne disease risks during the summer.

Influence of Demography, Land Use, and Urban Form on West Nile Virus Risk and Human West Nile Virus Incidence in Ottawa, Canada.

Human infection by West Nile virus (WNV; family Flaviviridae), in some cases, develops into a deadly neuroinvasive disease. WNV risk is thought to be influenced by factors affecting the density of species that promote replication and transmission of the virus, namely peridomestic bird and mosquito species. Factors influencing contact between peridomestic bird and mosquito species and contact between infected mosquitoes and vulnerable human populations may also be important in determining WNV risk in an area. Several urban form and demographic factors, such as population density and the proportion of aged housing units, have been linked with increased WNV risk. Other factors, such as proportion of old-growth forest and wetlands, have been linked to decreased WNV risk. In this study, we aimed to test the effect of several demographic, land use, and urban form variables on WNV risk within neighborhoods of the city of Ottawa, Canada, based on the spatiotemporal clustering of infected mosquitoes and human WNV cases. We found a large positive effect of population density and proportion of aged housing units on WNV risk, using both entomological and epidemiological data. Interestingly, we found a large negative effect of proportion of natural areas in our epidemiological analysis, but not in our entomological analysis. Although our epidemiological data set was relatively small, these results suggest entomological surveillance results should be interpreted alongside other factors when investigating risk to humans. Our study is also one of the few to suggest an effect of demography, land use, and urban form on WNV risk in a Canadian urban center, using both entomological and epidemiological data.

Identifying Environmental Risk Factors and Mapping the Distribution of West Nile Virus in an Endemic Region of North America.

Understanding the geographic distribution of mosquito‐borne disease and mapping disease risk are important for prevention and control efforts. Mosquito‐borne viruses (arboviruses), such as West Nile virus (WNV), are highly dependent on environmental conditions. Therefore, the use of environmental data can help in making spatial predictions of disease distribution. We used geocoded human case data for 2004–2017 and population‐weighted control points in combination with multiple geospatial environmental data sets to assess the environmental drivers of WNV cases and to map relative infection risk in South Dakota, USA. We compared the effectiveness of (1) land cover and physiography data, (2) climate data, and (3) spectral data for mapping the risk of WNV in South Dakota. A final model combining all data sets was used to predict spatial patterns of disease transmission and characterize the associations between environmental factors and WNV risk. We used a boosted regression tree model to identify the most important variables driving WNV risk and generated risk maps by applying this model across the entire state. We found that combining multiple sources of environmental data resulted in the most accurate predictions. Elevation, late‐season humidity, and early‐season surface moisture were the most important predictors of disease distribution. Indices that quantified interannual variability of climatic conditions and land surface moisture were better predictors than interannual means. We suggest that combining measures of interannual environmental variability with static land cover and physiography variables can help to improve spatial predictions of arbovirus transmission risk.

An Operational System for Surveillance and Ecological Forecasting of West Nile Virus Outbreaks

Mosquito-borne disease surveillance has traditionally focused on tracking human cases along with the abundance and infection status of mosquito vectors. Vector and host population dynamics are also sensitive to climatic factors, including temperature fluctuations and the availability of surface water for mosquito breeding. There is a potential to strengthen surveillance and predict future outbreaks by monitoring environmental risk factors using broad-scale sensor networks that include earth-observing satellites. The South Dakota Mosquito Information System (SDMIS) project combines entomological surveillance with gridded meteorological data from NASA’s North American Land Data Assimilation System (NLDAS) to generate weekly risk maps for West Nile virus (WNV) in the north-central United States. Critical components include a mosquito infection model that smooths the noisy infection rate and compensates for unbalanced sampling, and a human infection model that combines entomological risk estimates with lagged effects of meteorological variables from the North American Land Data Assimilation System (NLDAS). Two types of forecasts are generated: long-term forecasts of statewide risk extending through the entire WNV season, and short-term forecasts of the geographic pattern of WNV risk in the upcoming week. Model forecasts are connected to public health actions through decision support matrices that link predicted risk levels to a set of phased responses. SDMIS accurately predicted higher-than-normal WNV transmission in 2016 and lower-than-normal transmission in 2017. Our experiences highlight several important lessons that can inform future efforts at disease early warning. These include the value of integrating climatic models with recent observations of infection, the importance of automated workflows to facilitate timely integration of multiple data streams, and the need to link forecasts with specific public health responses.

Improving the prediction of arbovirus outbreaks: A comparison of climate-driven models for West Nile virus in an endemic region of the United States

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.

Association of spring-summer hydrology and meteorology with human West Nile virus infection in West Texas, USA, 2002\u20132016

BackgroundThe emergence of West Nile virus (WNV) in the Western Hemisphere has motivated research into the processes contributing to the incidence and persistence of the disease in the region. Meteorology and hydrology are fundamental determinants of vector-borne disease transmission dynamics of a region. The availability of water influences the population dynamics of vector and host, while temperature impacts vector growth rates, feeding habits, and disease transmission potential. Characterization of the temporal pattern of environmental factors influencing WNV risk is crucial to broaden our understanding of local transmission dynamics and to inform efforts of control and surveillance.MethodsWe used hydrologic, meteorological and WNV data from west Texas (2002–2016) to analyze the relationship between environmental conditions and annual human WNV infection. A Bayesian model averaging framework was used to evaluate the association of monthly environmental conditions with WNV infection.ResultsFindings indicate that wet conditions in the spring combined with dry and cool conditions in the summer are associated with increased annual WNV cases. Bayesian multi-model inference reveals monthly means of soil moisture, specific humidity and temperature to be the most important variables among predictors tested. Environmental conditions in March, June, July and August were the leading predictors in the best-fitting models.ConclusionsThe results significantly link soil moisture and temperature in the spring and summer to WNV transmission risk. Wet spring in association with dry and cool summer was the temporal pattern best-describing WNV, regardless of year. Our findings also highlight that soil moisture may be a stronger predictor of annual WNV transmission than rainfall.

Economics of One Health: Costs and benefits of integrated West Nile virus surveillance in Emilia-Romagna.

Since 2013 in Emilia-Romagna, Italy, surveillance information generated in the public health and in the animal health sectors has been shared and used to guide public health interventions to mitigate the risk of West Nile virus (WNV) transmission via blood transfusion. The objective of the current study was to identify and estimate the costs and benefits associated with this One Health surveillance approach, and to compare it to an approach that does not integrate animal health information in blood donations safety policy (uni-sectoral scenario). Costs of human, animal, and entomological surveillance, sharing of information, and triggered interventions were estimated. Benefits were quantified as the averted costs of potential human cases of WNV neuroinvasive disease associated to infected blood transfusion. In the 2009–2015 period, the One Health approach was estimated to represent a cost saving of €160,921 compared to the uni-sectoral scenario. Blood donation screening was the main cost for both scenarios. The One Health approach further allowed savings of €1.21 million in terms of avoided tests on blood units. Benefits of the One Health approach due to short-term costs of hospitalization and compensation for transfusion-associated disease potentially avoided, were estimated to range from €0 to €2.98 million according to the probability of developing WNV neuroinvasive disease after receiving an infected blood transfusion.

Geographic variations of the bird-borne structural risk of West Nile virus circulation in Europe.

The structural risk of West Nile Disease results from the usual functioning of the socio-ecological system, which may favour the introduction of the pathogen, its circulation and the occurrence of disease cases. Its geographic variations result from the local interactions between three components: (i) reservoir hosts, (ii) vectors, both characterized by their diversity, abundance and competence, (iii) and the socio-economic context that impacts the exposure of human to infectious bites. We developed a model of bird-borne structural risk of West Nile Virus (WNV) circulation in Europe, and analysed the association between the geographic variations of this risk and the occurrence of WND human cases between 2002 and 2014. A meta-analysis of WNV serosurveys conducted in wild bird populations was performed to elaborate a model of WNV seropositivity in European bird species, considered a proxy for bird exposure to WNV. Several eco-ethological traits of bird species were linked to seropositivity and the statistical model adequately fitted species-specific seropositivity data (area under the ROC curve: 0.85). Combined with species distribution maps, this model allowed deriving geographic variations of the bird-borne structural risk of WNV circulation. The association between this risk, and the occurrence of WND human cases across the European Union was assessed. Geographic risk variations of bird-borne structural risk allowed predicting WND case occurrence in administrative districts of the EU with a sensitivity of 86% (95% CI: 0.79–0.92), and a specificity of 68% (95% CI: 0.66–0.71). Disentangling structural and conjectural health risks is important for public health managers as risk mitigation procedures differ according to risk type. The results obtained show promise for the prevention of WND in Europe. Combined with analyses of vector-borne structural risk, they should allow designing efficient and targeted prevention measures.

Characterizing environmental risk factors for West Nile virus in Quebec, Canada, using clinical data in humans and serology in pet dogs.

The identification of specific environments sustaining emerging arbovirus amplification and transmission to humans is a key component of public health intervention planning. This study aimed at identifying environmental factors associated with West Nile virus (WNV) infections in southern Quebec, Canada, by modelling and jointly interpreting aggregated clinical data in humans and serological data in pet dogs. Environmental risk factors were estimated in humans by negative binomial regression based on a dataset of 191 human WNV clinical cases reported in the study area between 2011 and 2014. Risk factors for infection in dogs were evaluated by logistic and negative binomial models based on a dataset including WNV serological results from 1442 dogs sampled from the same geographical area in 2013. Forested lands were identified as low-risk environments in humans. Agricultural lands represented higher risk environments for dogs. Environments identified as impacting risk in the current study were somewhat different from those identified in other studies conducted in north-eastern USA, which reported higher risk in suburban environments. In the context of the current study, combining human and animal data allowed a more comprehensive and possibly a more accurate view of environmental WNV risk factors to be obtained than by studying aggregated human data alone.

Modelling West Nile virus transmission risk in Europe: effect of temperature and mosquito biotypes on the basic reproduction number

West Nile virus (WNV) is a mosquito-borne flavivirus which has caused repeated outbreaks in humans in southern and central Europe, but thus far not in northern Europe. The main mosquito vector for WNV, Culex pipiens, consists of two behaviourally distinct biotypes, pipiens and molestus, which can form hybrids. Differences between biotypes, such as vector competence and host preference, could be important in determining the risk of WNV outbreaks. Risks for WNV establishment can be modelled with basic reproduction number (R0) models. However, existing R0 models have not differentiated between biotypes. The aim of this study was, therefore, to explore the role of temperature-dependent and biotype-specific effects on the risk of WNV establishment in Europe. We developed an R0 model with temperature-dependent and biotype-specific parameters, and calculated R0 values using the next-generation matrix for several scenarios relevant for Europe. In addition, elasticity analysis was done to investigate the contribution of each biotype to R0. Global warming and increased mosquito-to-host ratios can possibly result in more intense WNV circulation in birds and spill-over to humans in northern Europe. Different contributions of the Cx. pipiens biotypes to R0 shows the importance of including biotype-specific parameters in models for reliable WNV risk assessments.

Remote-sensing based risk mapping for mosquito-borne diseases: a spatial modelling study

BackgroundWithin the USA, South Dakota is the state with the highest incidence rates of human West Nile virus disease. For effective disease prevention and mosquito control, it is crucial to identify potential transmission hot spots. Because disease occurrence is driven by the presence of avian hosts and mosquito vectors, understanding their habitats is important to predict the risk of cases of human West Nile virus. Geospatial environmental information about vegetation cover and water availability can help us to understand what drives the spatial distribution of disease outbreaks and to map the spatial pattern of the risk of West Nile virus. MethodsIn our study, we use Landsat imagery from 2003 to 2012 to predict the risk of West Nile virus transmission to human beings in South Dakota. We computed environmental indices such as the normalised differenced vegetation index (NDVI) and the normalised differenced water index (NDWI) as proxies for vegetation cover and water availability. For predictive mapping, we used boosted regression tree models to fit a model of disease risk based on geocoded human case data. FindingsIndices that measured interannual variability in vegetation and surface water were important predictors of West Nile virus risk, and identified locations with temporary water bodies that provided habitat for vectors and hosts. The resulting risk map accurately highlighted the major areas of high West Nile virus risk across South Dakota. InterpretationWe suggest that use of the temporal depth of the Landsat archive will help to develop more effective environmental metrics for mapping vector-borne diseases. FundingNational Institute of Allergy and Infectious Diseases NIH/NIAID (R01AI079411) and NASA Applied Science Public Health and Air Quality Programme.

A comparison of least squares regression and geographically weighted regression modeling of West Nile virus risk based on environmental parameters.

BackgroundThe primary aim of the study reported here was to determine the effectiveness of utilizing local spatial variations in environmental data to uncover the statistical relationships between West Nile Virus (WNV) risk and environmental factors. Because least squares regression methods do not account for spatial autocorrelation and non-stationarity of the type of spatial data analyzed for studies that explore the relationship between WNV and environmental determinants, we hypothesized that a geographically weighted regression model would help us better understand how environmental factors are related to WNV risk patterns without the confounding effects of spatial non-stationarity.MethodsWe examined commonly mapped environmental factors using both ordinary least squares regression (LSR) and geographically weighted regression (GWR). Both types of models were applied to examine the relationship between WNV-infected dead bird counts and various environmental factors for those locations. The goal was to determine which approach yielded a better predictive model.ResultsLSR efforts lead to identifying three environmental variables that were statistically significantly related to WNV infected dead birds (adjusted R2 = 0.61): stream density, road density, and land surface temperature. GWR efforts increased the explanatory value of these three environmental variables with better spatial precision (adjusted R2 = 0.71).ConclusionsThe spatial granularity resulting from the geographically weighted approach provides a better understanding of how environmental spatial heterogeneity is related to WNV risk as implied by WNV infected dead birds, which should allow improved planning of public health management strategies.

Risk mapping of West Nile virus circulation in Spain, 2015

West Nile fever is an emergent disease in Europe. The objective of this study was to conduct a predictive risk mapping of West Nile Virus (WNV) circulation in Spain based on historical data of WNV circulation. Areas of Spain with evidence of WNV circulation were mapped based on data from notifications to the surveillance systems and a literature review. A logistic regression-based spatial model was used to assess the probability of WNV circulation. Data were analyzed at municipality level. Mean temperatures of the period from June to October, presence of wetlands and presence of Special Protection Areas for birds were considered as potential predictors. Two predictors of WNV circulation were identified: higher temperature [adjusted odds ratio (AOR) 2.07, 95% CI 1.82–2.35, p<0.01] and presence of wetlands (3.37, 95% CI 1.89–5.99, p<0.01). Model validations indicated good predictions: area under the ROC curve was 0.895 (95% CI 0.870–0.919) for internal validation and 0.895 (95% CI 0.840–0.951) for external validation. This model could support improvements of WNV risk- based surveillance in Spain. The importance of a comprehensive surveillance for WNF, including human, animal and potential vectors is highlighted, which could additionally result in model refinements.

Latitudinal Diversity of Culex pipiens Biotypes and Hybrids in Farm, Peri-Urban, and Wetland Habitats in Europe.

Despite the presence of Culex (Cx.) pipiens mosquitoes and circulation of West Nile virus (WNV), WNV outbreaks have so far not occurred in northern Europe. The species Cx. pipiens consists of two morphologically identical biotypes, pipiens and molestus, which can form hybrids. Until now, population dynamic studies of Cx. pipiens have not differentiated between biotypes and hybrids at the European scale, nor have they used comparative surveillance approaches. We therefore aimed to elucidate the relative abundance of Cx. pipiens biotypes and hybrids in three habitat types at different latitudes across Europe, using two different surveillance traps. BG-Sentinel and Mosquito-Magnet Liberty Plus traps were placed in three habitat types (farms, peri-urban, wetlands), in three European countries (Sweden, The Netherlands, Italy). Collected Cx. pipiens mosquitoes were identified to biotype with real-time PCR. Both trap types collected equal ratios of the biotypes and their hybrids. From northern to southern latitudes there was a significant decrease of pipiens and an increase of molestus. Habitat types influenced the relative ratios of biotypes and hybrids, but results were not consistent across latitudes. Our results emphasize the need to differentiate Cx. pipiens to the biotype level, especially for proper future WNV risk assessments for Europe.

A simulation model to estimate the risk of transfusion-transmitted arboviral infection

BackgroundThe arboviruses West Nile virus (WNV), dengue virus (DENV) and Ross River virus (RRV) have been demonstrated to be blood transfusion-transmissible. A model to estimate the risk of WNV to the blood supply using a Monte Carlo approach has been developed and also applied to Chikungunya virus. Also, a probabilistic model was developed to assess the risk of DENV to blood safety, which was later adapted to RRV. To address efficacy and limitations within each model we present a hybrid model that promises improved accuracy, and is broadly applicable to assess the risk of arboviral transmission by blood transfusion. Material and methodsData were drawn from the Cairns Public Health Unit (Australia) and published literature. Based on the published models and using R code, a novel ‘combined’ model was developed and validated against the BP model using sensitivity testing. ResultsThe mean risk per 10,000 of the combined model is 0.98 with a range from 0.79 to 1.25, while the maximum risk was 4.45 ranging from 2.62 to 7.67 respectively. These parameters for the BP model were 1.20 ranging from 0.84 to 1.55, and 2.86 ranging from 1.33 to 5.23 respectively. ConclusionThe combined simulation model is simple and robust. We propose it can be applied as a ‘generic’ arbovirus model to assess the risk from known or novel arboviral threats to the blood supply.

Vector competence of northern European Culex pipiens biotypes and hybrids for West Nile virus is differentially affected by temperature.

BackgroundOutbreaks of West Nile virus (WNV) have not occurred in northern Europe despite nearby circulation of WNV in the southern part of the continent. The main vector for WNV, the mosquito Culex (Cx.) pipiens, consists of two behaviorally distinct biotypes, pipiens and molestus, which can form hybrids. Although temperature has been shown to influence vector competence of Cx. pipiens for WNV and biotypes are differentially susceptible towards infection, the interaction between the two has not been elucidated.MethodsWe determined vector competence of the Cx. pipiens biotypes and hybrids, after 14 days of incubation at 18, 23 and 28 °C. Mosquitoes were orally infected by providing an infectious blood meal or by injecting WNV directly in the thorax. Infection and transmission rates were determined by testing the bodies and saliva for WNV presence. In addition, titers of mosquitoes with WNV-positive bodies and saliva samples were determined.ResultsOrally infected biotype pipiens and hybrids showed significantly increased transmission rates with higher temperatures, up to 32 and 14 %, respectively. In contrast, the molestus biotype had an overall transmission rate of 10 %, which did not increase with temperature. All mosquitoes that were infected via WNV injections had (close to) 100 % infection and transmission rates, suggesting an important role of the mosquito midgut barrier. We found no effect of increasing temperature on viral titers.ConclusionsTemperature differentially affected vector competence of the Cx. pipiens biotypes. This shows the importance of accounting for biotype-by-temperature interactions, which influence the outcomes of vector competence studies. Vector competence studies with Cx. pipiens mosquitoes differentiated to the biotype level are essential for proper WNV risk assessments.Electronic supplementary materialThe online version of this article (doi:10.1186/s13071-016-1677-0) contains supplementary material, which is available to authorized users.

Evaluation of the Control of West Nile Virus in Ontario: Did Risk Patterns Change from 2005 to 2012?

The goal of this study was to evaluate and compare the risk distribution of human cases of West Nile virus (WNV) disease in Ontario in 2005 to 2012. The objectives were to: map the risk distribution of WNV in 2005 and 2012, identify clusters of human WNV disease and determine whether the clusters are significantly different between the years 2005 and 2012. West Nile virus surveillance data were used to calculate empirical Bayesian smoothed estimates of disease incidence in southern Ontario for 2005 and 2012. Choropleth maps were generated to visualize the spatial risk distribution, and the spatial scan test was performed to identify clusters of disease. Following identification of clusters for 2005 and 2012, a Poisson model was applied to the 2012 human WNV incidence adjusted for the smoothed human WNV incidence rate from 2005 and the scan test was repeated. Two significant clusters were identified in both the year 2005 and 2012. In 2005, the primary cluster was located in the Windsor-Essex and Chatham-Kent public health units (PHUs). For 2012, the primary cluster was identified in the Golden Horseshoe area. A cluster analysis for 2012 adjusted for those identified in 2005 resulted in one significant cluster in the Windsor-Essex PHU. In 2012, the Windsor-Essex PHU remained as a high-risk area for human WNV disease when compared with the rest of southern Ontario. Although overall risk may change from year to year, public health programming should be employed to decrease the relative risk of WNV in this area.

Effects of weather and landscape on the equine West Nile virus infection risk in Mississippi, USA.

The West Nile virus (WNv) continues to be a public health concern in North America. Dry weather appears to increase human WNv infection risks, but it is uncertain whether dry weather conditions exert similar effects on the corresponding equine WNv infection. This study assessed the effects of precipitation of the previous year and land cover diversity on the equine WNv risk of Mississippi, USA, at the county level in the year 2002 using Bayesian hierarchical models. The risk estimated for 2002 was found to be inversely related to annual precipitation of the preceding year. Equine WNv risks were lower with greater land cover diversity probably due to the diluting effects of biodiversity. Correlation between the equine and human WNv risks was positive but relatively low. Dry weather conditions of the previous year might reduce mosquito competitors and predators and subsequently increase mosquito abundances and equine WNv risks in agricultural areas with low biodiversity.

Persistent impacts of West Nile virus on North American bird populations

Since its introduction to North America in 1999, West Nile virus (WNV) has had devastating impacts on native host populations, but to date these impacts have been difficult to measure. Using a continental-scale dataset comprised of a quarter-million birds captured over nearly two decades and a recently developed model of WNV risk, we estimated the impact of this emergent disease on the survival of avian populations. We find that populations were negatively affected by WNV in 23 of the 49 species studied (47%). We distinguished two groups of species: those for which WNV negatively impacted survival only during initial spread of the disease (n = 11), and those that show no signs of recovery since disease introduction (n = 12). Results provide a novel example of the taxonomic breadth and persistent impacts of this wildlife disease on a continental scale. Phylogenetic analyses further identify groups (New World sparrows, finches, and vireos) disproportionally affected by temporary or persistent WNV effects, suggesting an evolutionary dimension of disease risk. Identifying the factors affecting the persistence of a disease across host species is critical to mitigating its effects, particularly in a world marked by rapid anthropogenic change.

Regional variation of climatic influences on West Nile virus outbreaks in the United States.

The national resurgence of human West Nile virus (WNV) disease in 2012 raised questions about the factors responsible for WNV outbreaks. Interannual climatic variations may influence WNV amplification and transmission to humans through multiple pathways, including mosquito breeding habitats, gonotrophic cycles, extrinsic incubation, avian communities, and human behavior. We examined the influences of temperature and precipitation anomalies on interannual variation in human WNV cases in three regions of the United States. There were consistent positive influences of winter temperatures, weaker and more variable positive effects of spring and summer temperatures, and highly variable precipitation effects that ranged from positive to negative. The overwintering period may be a particularly important climatic constraint on the dynamics of WNV in cold-temperate regions of North America. Geographic differences in the seasonal timing and relative importance of climatic drivers of WNV risk likely reflect underlying variability in key ecological and social characteristics.