Landscape-level spatial patterns of West Nile virus risk in the northern Great Plains

Scoping review of Culex mosquito life history trait heterogeneity in response to temperature

BACKGROUND

Mosquitoes in the genus Culex are primary vectors in the US for West Nile virus (WNV) and other arboviruses. Climatic drivers such as temperature have differential effects on species-specific changes in mosquito range, distribution, and abundance, posing challenges for population modeling, disease forecasting, and subsequent public health decisions. Understanding these differences in underlying biological dynamics is crucial in the face of climate change.

METHODS

We collected empirical data on thermal response for immature development rate, egg viability, oviposition, survival to adulthood, and adult lifespan for Culex pipiens, Cx. quinquefasciatus, Cx. tarsalis, and Cx. restuans from existing literature according to the PRISMA scoping review guidelines.

RESULTS

We observed linear relationships with temperature for development rate and lifespan, and nonlinear relationships for survival and egg viability, with underlying variation between species. Optimal ranges and critical minima and maxima also appeared varied. To illustrate how model output can change with experimental input data from individual Culex species, we applied a modified equation for temperature-dependent mosquito type reproduction number for endemic spread of WNV among mosquitoes and observed different effects.

CONCLUSIONS

Current models often input theoretical parameters estimated from a single vector species; we show the need to implement the real-world heterogeneity in thermal response between species and present a useful data resource for researchers working toward that goal.

Integrated Forecasts Based on Public Health Surveillance and Meteorological Data Predict West Nile Virus in a High-Risk Region of North America

BACKGROUND

West Nile virus (WNV), a global arbovirus, is the most prevalent mosquito-transmitted infection in the United States. Forecasts of WNV risk during the upcoming transmission season could provide the basis for targeted mosquito control and disease prevention efforts. We developed the Arbovirus Mapping and Prediction (ArboMAP) WNV forecasting system and used it in South Dakota from 2016 to 2019. This study reports a post hoc forecast validation and model comparison.

OBJECTIVES

Our objective was to validate historical predictions of WNV cases with independent data that were not used for model calibration. We tested the hypothesis that predictive models based on mosquito surveillance data combined with meteorological variables were more accurate than models based on mosquito or meteorological data alone.

METHODS

The ArboMAP system incorporated models that predicted the weekly probability of observing one or more human WNV cases in each county. We compared alternative models with different predictors including a) a baseline model based only on historical WNV cases, b) mosquito models based on seasonal patterns of infection rates, c) environmental models based on lagged meteorological variables, including temperature and vapor pressure deficit, d) combined models with mosquito infection rates and lagged meteorological variables, and e) ensembles of two or more combined models. During the WNV season, models were calibrated using data from previous years and weekly predictions were made using data from the current year. Forecasts were compared with observed cases to calculate the area under the receiver operating characteristic curve (AUC) and other metrics of spatial and temporal prediction error.

RESULTS

Mosquito and environmental models outperformed the baseline model that included county-level averages and seasonal trends of WNV cases. Combined models were more accurate than models based only on meteorological or mosquito infection variables. The most accurate model was a simple ensemble mean of the two best combined models. Forecast accuracy increased rapidly from early June through early July and was stable thereafter, with a maximum AUC of 0.85. The model predictions captured the seasonal pattern of WNV as well as year-to-year variation in case numbers and the geographic pattern of cases.

DISCUSSION

The predictions reached maximum accuracy early enough in the WNV season to allow public health responses before the peak of human cases in August. This early warning is necessary because other indicators of WNV risk, including early reports of human cases and mosquito abundance, are poor predictors of case numbers later in the season. https://doi.org/10.1289/EHP10287.

Effect of Agroecosystems on Seroprevalence of St. Louis Encephalitis and West Nile Viruses in Birds, La Pampa, Argentina, 2017-2019

In Argentina, the Pampa ecoregion has been almost completely transformed into agroecosystems. To evaluate the environmental (agricultural area, tree coverage, distance to the nearest water body and urban site) and biological (dove, cowbird, and sparrow abundance) effects on free-ranging bird exposure to St. Louis encephalitis virus (SLEV) and West Nile virus (WNV), we used generalized linear mixed models. For 1,019 birds sampled during 2017–2019, neutralizing antibodies were found against SLEV in samples from 60 (5.8%) birds and against WNV for 21 (2.1%). The best variable for explaining SLEV seroprevalence was agricultural area, which had a positive effect; however, for WNV, no model was conclusive. Our results suggest that agroecosystems in the La Pampa ecoregion increase the exposure of avian hosts to SLEV, thus potentially increasing virus activity.

West Nile virus transmission potential in Portugal

It is unclear whether West Nile virus (WNV) circulates endemically in Portugal. Despite the country’s adequate climate for transmission, Portugal has only reported four human WNV infections so far. We performed a review of WNV-related data (1966–2020), explored mosquito (2016–2019) and land type distributions (1992–2019), and used climate data (1981–2019) to estimate WNV transmission suitability in Portugal. Serological and molecular evidence of WNV circulation from animals and vectors was largely restricted to the south. Land type and climate-driven transmission suitability distributions, but not the distribution of WNV-capable vectors, were compatible with the North-South divide present in serological and molecular evidence of WNV circulation. Our study offers a comprehensive, data-informed perspective and review on the past epidemiology, surveillance and climate-driven transmission suitability of WNV in Portugal, highlighting the south as a subregion of importance. Given the recent WNV outbreaks across Europe, our results support a timely change towards local, active surveillance.

Lourenço et al. review historical data and quantify the transmission potential of West Nile virus in Portugal. They report a North-South divide in infection patterns, a higher ecological capacity in the south, and an increasing positive effect of climate change over the last 40 years.

Spatial patterns of West Nile virus distribution in the Volgograd region of Russia, a territory with long-existing foci

Southern Russia remains affected by West Nile virus (WNV). In the current study, we identified the spatial determinants of WNV distribution in an area with endemic virus transmission, with special reference to the urban settings, by mapping probable points of human infection acquisition and points of virus detection in mosquitoes, ticks, birds, and mammals during 1999-2016. The suitability of thermal conditions for extrinsic virus replication was assessed based on the approach of degree-day summation and their changes were estimated by linear trend analysis. A generalized linear model was used to analyze the year-to-year variation of human cases versus thermal conditions. Environmental suitability was determined by ecological niche modelling using MaxEnt software. Human population density was used as an offset to correct for possible bias. Spatial analysis of virus detection in the environment showed significant contributions from surface temperature, altitude, and distance from water bodies. When indicators of location and mobility of the human population were included, the relative impact of factors changed, with roads becoming most important. When the points of probable human case infection were added, the percentage of leading factors changed only slightly. The urban environment significantly increased the epidemic potential of the territory and created quite favorable conditions for virus circulation. The private building sector with low-storey houses and garden plots located in the suburbs provided a connection between urban and rural transmission cycles.

Spatiotemporal Analysis of West Nile Virus Epidemic in South Banat District, Serbia, 2017-2019

West Nile virus (WNV) is an arthropod-born pathogen, which is transmitted from wild birds through mosquitoes to humans and animals. At the end of the 20th century, the first West Nile fever (WNF) outbreaks among humans in urban environments in Eastern Europe and the United States were reported. The disease continued to spread to other parts of the continents. In Serbia, the largest number of WNV-infected people was recorded in 2018. This research used spatial statistics to identify clusters of WNV infection in humans and animals in South Banat County, Serbia. The occurrence of WNV infection and risk factors were analyzed using a negative binomial regression model. Our research indicated that climatic factors were the main determinant of WNV distribution and were predictors of endemicity. Precipitation and water levels of rivers had an important influence on mosquito abundance and affected the habitats of wild birds, which are important for maintaining the virus in nature. We found that the maximum temperature of the warmest part of the year and the annual temperature range; and hydrographic variables, e.g., the presence of rivers and water streams were the best environmental predictors of WNF outbreaks in South Banat County.

Spring temperature shapes West Nile virus transmission in Europe

West Nile Virus (WNV) is now endemic in many European countries, causing hundreds of human cases every year, with a high spatial and temporal heterogeneity. Previous studies have suggested that spring temperature might play a key role at shaping WNV transmission. Specifically, warmer temperatures in April-May might amplify WNV circulation, thus increasing the risk for human transmission later in the year. To test this hypothesis, we collated publicly available data on the number of human infections recorded in Europe between 2011 and 2019. We then applied generalized linear models to quantify the relationship between human cases and spring temperature, considering both average conditions (over years 2003-2010) and deviations from the average for subsequent years (2011-2019). We found a significant positive association both spatial (average conditions) and temporal (deviations). The former indicates that WNV circulation is higher in usually warmer regions while the latter implies a predictive value of spring conditions over the coming season. We also found a positive association with WNV detection during the previous year, which can be interpreted as an indication of the reliability of the surveillance system but also of WNV overwintering capacity. Weather anomalies at the beginning of the mosquito breeding season might act as an early warning signal for public health authorities, enabling them to strengthen in advance ongoing surveillance and prevention strategies.

The drivers of West Nile virus human illness in the Chicago, Illinois, USA area: Fine scale dynamic effects of weather, mosquito infection, social, and biological conditions

West Nile virus (WNV) has consistently been reported to be associated with human cases of illness in the region near Chicago, Illinois. However, the number of reported cases of human illness varies across years, with intermittent outbreaks. Several dynamic factors, including temperature, rainfall, and infection status of vector mosquito populations, are responsible for much of these observed variations. However, local landscape structure and human demographic characteristics also play a key role. The geographic and temporal scales used to analyze such complex data affect the observed associations. Here, we used spatial and statistical modeling approaches to investigate the factors that drive the outcome of WNV human illness on fine temporal and spatial scales. Our approach included multi-level modeling of long-term weekly data from 2005 to 2016, with weekly measures of mosquito infection, human illness and weather combined with more stable landscape and demographic factors on the geographical scale of 1000m hexagons. We found that hot weather conditions, warm winters, and higher MIR in earlier weeks increased the probability of an area of having a WNV human case. Higher population and the proportion of urban light intensity in an area also increased the probability of observing a WNV human case. A higher proportion of open water sources, percentage of grass land, deciduous forests, and housing built post 1990 decreased the probability of having a WNV case. Additionally, we found that cumulative positive mosquito pools up to 31 weeks can strongly predict the total annual human WNV cases in the Chicago region. This study helped us to improve our understanding of the fine-scale drivers of spatiotemporal variability of human WNV cases.

Landscape and demographic determinants of Culex infection with West Nile virus during the 2012 epidemic in Dallas County, TX

In 2012, the United States experienced one of the largest outbreaks of West Nile virus (WNV)-associated deaths, with the majority occurring in Dallas County (Co.), Texas (TX) and surrounding areas. In this study, logistic mixed models were used to identify associations between the landscape, human population, and WNV-infected Culex quinquefasciatus mosquitoes during the 2012 WNV epidemic in Dallas Co. We found increased probabilities for WNV-positive mosquitoes in north and central Dallas Co. The most significant predictors of the presence of WNV in Cx. quinquefasciatus pools were increased urbanization (based on an index composed of greater population density, lower normalized difference vegetation index, higher coverage of urban land types, and more impervious surfaces), older human populations, and lower elevation. These relationships between the landscape, sociodemographics, and risk of enzootic transmission identified regions of Dallas Co., TX with highest risk of spillover to human disease during the 2012 WNV epidemic.

Models and Surveillance Systems to Detect and Predict West Nile Virus Outbreaks

Over the past 20 yr, many models have been developed to predict risk for West Nile virus (WNV; Flaviviridae: Flavivirus) disease in the human population. These models have aided our understanding of the meteorological and land-use variables that drive spatial and temporal patterns of human disease risk. During the same period, electronic data systems have been adopted by surveillance programs across much of the United States, including a growing interest in integrated data services that preserve the autonomy and attribution of credit to originating agencies but facilitate data sharing, analysis, and visualization at local, state, and national scales. At present, nearly all predictive models have been limited to the scientific literature, with few having been implemented for use by public-health and vector-control decision makers. The current article considers the development of models for spatial patterns, early warning, and early detection of WNV over the last 20 yr and considers some possible paths toward increasing the utility of these models for guiding interventions.

The influence of weather and weather variability on mosquito abundance and infection with West Nile virus in Harris County, Texas, USA

Early warning systems for vector-borne diseases (VBDs) prediction are an ecological application where data from the interface of several environmental components can be used to predict future VBD transmission. In general, models for early warning systems only consider average environmental conditions ignoring variation in weather variables, despite the prediction from Schmalhausen's law about the importance of environmental variability for biological systems. We present results from a long-term mosquito surveillance program from Harris County, Texas, USA, where we use time series analysis techniques to study the abundance and West Nile virus (WNV) infection patterns in the local primary vector, Culex quinquefasciatus Say. We found that, as predicted by Schmalhausen's law, mosquito abundance was associated with the standard deviation and kurtosis of environmental variables. By contrast, WNV infection rates were associated with 8-month lagged temperature, suggesting environmental conditions during overwintering might be key for WNV amplification during summer outbreaks. Finally, model validation showed that seasonal autoregressive models successfully predicted mosquito WNV infection rates up to 2 months ahead, but did rather poorly at predicting mosquito abundance, a result that might reflect impacts of vector control for mosquito population reduction, geographic scale, and other artifacts generated by operational constraints of mosquito surveillance systems.

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.

Increased Human Incidence of West Nile Virus Disease near Rice Fields in California but Not in Southern United States

Anthropogenic land use change, including agriculture, can alter mosquito larval habitat quality, increase mosquito abundance, and increase incidence of vector-borne disease. Rice is a staple food crop for more than half of the world's population, with ∼1% of global production occurring within the United States (US). Flooded rice fields provide enormous areas of larval habitat for mosquito species and may be hotspots for mosquito-borne pathogens, including West Nile virus (WNV). West Nile virus was introduced into the Americas in 1999 and causes yearly epidemics in the US with an average of approximately 1,400 neuroinvasive cases and 130 deaths per year. We examined correlations between rice cultivation and WNV disease incidence in rice-growing regions within the US. Incidence of WNV disease increased with the fraction of each county under rice cultivation in California but not in the southern US. We show that this is likely due to regional variation in the mosquitoes transmitting WNV. Culex tarsalis was an important vector of WNV in California, and its abundance increased with rice cultivation, whereas in rice-growing areas of the southern US, the dominant WNV vector was Culex quinquefasciatus, which rarely breeds in rice fields. These results illustrate how cultivation of particular crops can increase disease risk and how spatial variation in vector ecology can alter the relationship between land cover and disease.

Factors associated with human West Nile virus infection in Ontario: a generalized linear mixed modelling approach

BACKGROUND

West Nile Virus (WNV) is a mosquito-borne pathogen that has become established in North America. Risk for human infection varies geographically in accordance with climate and population factors. Though often asymptomatic, human WNV infection can cause febrile illness or, rarely, neurologic disease. WNV has become a public health concern in Canada since its introduction in 2001.

METHODS

To identify predictors of human WNV incidence at the public health unit (PHU) level in Ontario, Canada, we combined data on environmental and population characteristics of PHUs with historical mosquito and human surveillance records from 2002 to 2013. We examined the associations between annual WNV incidence and monthly climate indices (e.g. minimum and maximum temperature, average precipitation), land cover (e.g. deciduous forest, water), population structure (e.g. age and sex composition) and the annual percentage of WNV-positive mosquito pools from 2002 to 2013. We then developed a generalized linear mixed model with a Poisson distribution adjusting for spatial autocorrelation and repeat measures. Further to this, to examine potential 'early season' predictors of WNV incidence in a given year, we developed a model based on winter and spring monthly climate indices.

RESULTS

Several climate indices, including mean minimum temperature (o C) in February (RR = 1.58, CI: [1.42, 1.75]), and the annual percentage of WNV-positive mosquito pools (RR = 1.07, CI: [1.04, 1.11]) were significantly associated with human WNV incidence at the PHU level. Higher winter minimum temperatures were also strongly associated with annual WNV incidence in the 'early season' model (e.g. February minimum temperature (RR = 1.91, CI: [1.73, 2.12]).

CONCLUSIONS

Our study demonstrates that early season temperature and precipitation indices, in addition to the percentage of WNV-positive mosquito pools in a given area, may assist in predicting the likelihood of a more severe human WNV season in southern regions of Ontario, where WNV epidemics occur sporadically.

Integrating Environmental Monitoring and Mosquito Surveillance to Predict Vector-borne Disease: Prospective Forecasts of a West Nile Virus Outbreak

INTRODUCTION

Predicting the timing and locations of future mosquito-borne disease outbreaks has the potential to improve the targeting of mosquito control and disease prevention efforts. Here, we present and evaluate prospective forecasts made prior to and during the 2016 West Nile virus (WNV) season in South Dakota, a hotspot for human WNV transmission in the United States.

METHODS

We used a county-level logistic regression model to predict the weekly probability of human WNV case occurrence as a function of temperature, precipitation, and an index of mosquito infection status. The model was specified and fitted using historical data from 2004-2015 and was applied in 2016 to make short-term forecasts of human WNV cases in the upcoming week as well as whole-year forecasts of WNV cases throughout the entire transmission season. These predictions were evaluated at the end of the 2016 WNV season by comparing them with spatial and temporal patterns of the human cases that occurred.

RESULTS

There was an outbreak of WNV in 2016, with a total of 167 human cases compared to only 40 in 2015. Model results were generally accurate, with an AUC of 0.856 for short-term predictions. Early-season temperature data were sufficient to predict an earlier-than-normal start to the WNV season and an above-average number of cases, but underestimated the overall case burden. Model predictions improved throughout the season as more mosquito infection data were obtained, and by the end of July the model provided a close estimate of the overall magnitude of the outbreak.

CONCLUSIONS

An integrated model that included meteorological variables as well as a mosquito infection index as predictor variables accurately predicted the resurgence of WNV in South Dakota in 2016. Key areas for future research include refining the model to improve predictive skill and developing strategies to link forecasts with specific mosquito control and disease prevention activities.

Effects of landscape anthropization on mosquito community composition and abundance

Anthropogenic landscape transformation has an important effect on vector-borne pathogen transmission. However, the effects of urbanization on mosquito communities are still only poorly known. Here, we evaluate how land-use characteristics are related to the abundance and community composition of mosquitoes in an area with endemic circulation of numerous mosquito-borne pathogens. We collected 340 829 female mosquitoes belonging to 13 species at 45 localities spatially grouped in 15 trios formed by 1 urban, 1 rural and 1 natural area. Mosquito abundance and species richness were greater in natural and rural areas than in urban areas. Environmental factors including land use, vegetation and hydrological characteristics were related to mosquito abundance and community composition. Given the differing competences of each species in pathogen transmission, these results provide valuable information on the transmission potential of mosquito-borne pathogens that will be of great use in public and animal health management by allowing, for instance, the identification of the priority areas for pathogen surveillance and vector control.

Effect of Trapping Methods, Weather, and Landscape on Estimates of the Culex Vector Mosquito Abundance

The local abundance of Culex mosquitoes is a central factor adding to the risk of West Nile virus transmission, and vector abundance data influence public health decisions. This study evaluated differences in abundance estimates from mosquitoes trapped using two common methods: CO2-baited CDC light traps and infusion-baited gravid traps in suburban, Chicago, Illinois. On a weekly basis, the two methods were modestly correlated (r = 0.219) across 71 weeks over 4 years. Lagged weather conditions of up to four weeks were associated with the number of mosquitoes collected in light and gravid traps. Collections in light traps were higher with higher temperature in the same week, higher precipitation one, two, and four weeks before the week of trapping, and lower maximum average wind speed. Collections in gravid traps were higher with higher temperature in the same week and one week earlier, lower temperature four weeks earlier, and with higher precipitation two and four weeks earlier. Culex abundance estimates from light traps were significantly higher in semi-natural areas compared to residential areas, but abundance estimates from gravid traps did not vary by the landscape type. These results highlight the importance of the surveillance methods used in the assessment of local Culex abundance estimates. Measures of risk of exposure to West Nile virus should assess carefully how mosquito abundance has been estimated and integrated into assessments of transmission risk.

Software to Facilitate Remote Sensing Data Access for Disease Early Warning Systems

Satellite remote sensing produces an abundance of environmental data that can be used in the study of human health. To support the development of early warning systems for mosquito-borne diseases, we developed an open-source, client based software application to enable the Epidemiological Applications of Spatial Technologies (EASTWeb). Two major design decisions were full automation of the discovery, retrieval and processing of remote sensing data from multiple sources, and making the system easily modifiable in response to changes in data availability and user needs. Key innovations that helped to achieve these goals were the implementation of a software framework for data downloading and the design of a scheduler that tracks the complex dependencies among multiple data processing tasks and makes the system resilient to external errors. EASTWeb has been successfully applied to support forecasting of West Nile virus outbreaks in the United States and malaria epidemics in the Ethiopian highlands.

Identifying the environmental conditions favouring West Nile Virus outbreaks in Europe

West Nile Virus (WNV) is a globally important mosquito borne virus, with significant implications for human and animal health. The emergence and spread of new lineages, and increased pathogenicity, is the cause of escalating public health concern. Pinpointing the environmental conditions that favour WNV circulation and transmission to humans is challenging, due both to the complexity of its biological cycle, and the under-diagnosis and reporting of epidemiological data. Here, we used remote sensing and GIS to enable collation of multiple types of environmental data over a continental spatial scale, in order to model annual West Nile Fever (WNF) incidence across Europe and neighbouring countries. Multi-model selection and inference were used to gain a consensus from multiple linear mixed models. Climate and landscape were key predictors of WNF outbreaks (specifically, high precipitation in late winter/early spring, high summer temperatures, summer drought, occurrence of irrigated croplands and highly fragmented forests). Identification of the environmental conditions associated with WNF outbreaks is key to enabling public health bodies to properly focus surveillance and mitigation of West Nile virus impact, but more work needs to be done to enable accurate predictions of WNF risk.

Association between agricultural land use and West Nile virus antibody prevalence in Iowa birds

In the Plains states of the central United States, research suggests that the prevalence of West Nile virus (WNV) disease in humans is higher in agricultural areas than in nonagricultural areas. In contrast, there is limited information about WNV exposure in birds, the primary amplifying host of WNV, in agriculturally dominated landscapes. We evaluated whether exposure to WNV in peridomestic birds sampled in central Iowa varied with the proportion of land use devoted to agriculture. Over the summers of 2009 and 2010, we captured birds in sites comprising gradients of agricultural, urban, and natural land uses, and tested their sera for antibodies to WNV. Overall, WNV antibody prevalence was low (2.3%). Our results suggest that agricultural land use had minimal influence on WNV exposure in birds. We conclude that birds are not likely to be useful indicators of WNV activity in agricultural areas in the Plains states despite human risk being highest in those areas. Antibody prevalence for WNV, however, was higher in American Robins, Mourning Doves, and Northern Cardinals than in other species, making these species potentially useful for monitoring WNV activity in the US Plains states.

Towards an early warning system for forecasting human west nile virus incidence

We have identified environmental and demographic variables, available in January, that predict the relative magnitude and spatial distribution of West Nile virus (WNV) for the following summer. The yearly magnitude and spatial distribution for WNV incidence in humans in the United States (US) have varied wildly in the past decade. Mosquito control measures are expensive and having better estimates of the expected relative size of a future WNV outbreak can help in planning for the mitigation efforts and costs. West Nile virus is spread primarily between mosquitoes and birds; humans are an incidental host. Previous efforts have demonstrated a strong correlation between environmental factors and the incidence of WNV. A predictive model for human cases must include both the environmental factors for the mosquito-bird epidemic and an anthropological model for the risk of humans being bitten by a mosquito. Using weather data and demographic data available in January for every county in the US, we use logistic regression analysis to predict the probability that the county will have at least one WNV case the following summer. We validate our approach and the spatial and temporal WNV incidence in the US from 2005 to 2013. The methodology was applied to forecast the 2014 WNV incidence in late January 2014. We find the most significant predictors for a county to have a case of WNV to be the mean minimum temperature in January, the deviation of this minimum temperature from the expected minimum temperature, the total population of the county, publicly available samples of local bird populations, and if the county had a case of WNV the previous year.

Towards an early warning system for forecasting human west nile virus incidence

We have identified environmental and demographic variables, available in January, that predict the relative magnitude and spatial distribution of West Nile virus (WNV) for the following summer. The yearly magnitude and spatial distribution for WNV incidence in humans in the United States (US) have varied wildly in the past decade. Mosquito control measures are expensive and having better estimates of the expected relative size of a future WNV outbreak can help in planning for the mitigation efforts and costs. West Nile virus is spread primarily between mosquitoes and birds; humans are an incidental host. Previous efforts have demonstrated a strong correlation between environmental factors and the incidence of WNV. A predictive model for human cases must include both the environmental factors for the mosquito-bird epidemic and an anthropological model for the risk of humans being bitten by a mosquito. Using weather data and demographic data available in January for every county in the US, we use logistic regression analysis to predict the probability that the county will have at least one WNV case the following summer. We validate our approach and the spatial and temporal WNV incidence in the US from 2005 to 2013. The methodology was applied to forecast the 2014 WNV incidence in late January 2014. We find the most significant predictors for a county to have a case of WNV to be the mean minimum temperature in January, the deviation of this minimum temperature from the expected minimum temperature, the total population of the county, publicly available samples of local bird populations, and if the county had a case of WNV the previous year.

Modeling Culex tarsalis abundance on the northern Colorado front range using a landscape-level approach

Remote sensing and Geographic Information System (GIS) data can be used to identify larval mosquito habitats and predict species distribution and abundance across a landscape. An understanding of the landscape features that impact abundance and dispersal can then be applied operationally in mosquito control efforts to reduce the transmission of mosquito-borne pathogens. In an effort to better understand the effects of landscape heterogeneity on the abundance of the West Nile virus (WNV) vector Culex tarsalis, we determined associations between GIS-based environmental data at multiple spatial extents and monthly abundance of adult Cx. tarsalis in Larimer County and Weld County, CO. Mosquito data were collected from Centers for Disease Control and Prevention miniature light traps operated as part of local WNV surveillance efforts. Multiple regression models were developed for prediction of monthly Cx. tarsalis abundance for June, July, and August using 4 years of data collected over 2007-10. The models explained monthly adult mosquito abundance with accuracies ranging from 51-61% in Fort Collins and 57-88% in Loveland-Johnstown. Models derived using landscape-level predictors indicated that adult Cx. tarsalis abundance is negatively correlated with elevation. In this case, low-elevation areas likely more abundantly include habitats for Cx. tarsalis. Model output indicated that the perimeter of larval sites is a significant predictor of Cx. tarsalis abundance at a spatial extent of 500 m in Loveland-Johnstown in all months examined. The contribution of irrigated crops at a spatial extent of 500 m improved model fit in August in both Fort Collins and Loveland-Johnstown. These results emphasize the significance of irrigation and the manual control of water across the landscape to provide viable larval habitats for Cx. tarsalis in the study area. Results from multiple regression models can be applied operationally to identify areas of larval Cx. tarsalis production (irrigated crops lands and standing water) and assign priority in larval treatments to areas with a high density of larval sites at relevant spatial extents around urban locations.

Limited spillover to humans from West Nile Virus viremic birds in Atlanta, Georgia

West Nile Virus (WNV) is a mosquito-borne pathogen that impacts the health of its passerine bird hosts as well as incidentally infected humans in the United States. Intensive enzootic activity among the hosts and vectors does not always lead to human outbreaks, as is the situation throughout much of the southeastern United States. In Georgia, substantial yearly evidence of WNV in the mosquito vectors and avian hosts since 2001 has only led to 324 human cases. Although virus has been consistently isolated from mosquitoes trapped in Atlanta, GA, little is known about viral activity among the passerine hosts. A possible reason for the suppression of WNV spillover to humans is that viremic birds are absent from high human-use areas of the city. To test this hypothesis, multiseason, multihabitat, longitudinal WNV surveillance for active WNV viremia was conducted within the avian host community of urban Atlanta by collection of blood samples from wild passerine birds in five urban microhabitats. WNV was isolated from the serum of six blood samples collected from 630 (0.95%) wild passerine birds in Atlanta during 2010-2012, a proportion similar to that found in the Chicago, IL, area in 2005, when over 200 human cases were reported. Most of the viremic birds were Northern Cardinals, suggesting they may be of particular importance to the WNV transmission cycle in Georgia. Results indicated active WNV transmission in all microhabitats of urban Atlanta, except in the old-growth forest patches. The number of viremic birds was highest in Zoo Atlanta, where 3.5% of samples were viremic. Although not significant, these observations may suggest a possible transmission reduction effect of urban old-growth forests and a potential role in WNV amplification for Zoo Atlanta. Overall, spillover to humans remains a rare occurrence in urban Atlanta settings despite active WNV transmission in the avian population.

Spatio-temporal epidemiology of human West Nile virus disease in South Dakota

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.

Environmental forcing shapes regional house mosquito synchrony in a warming temperate island

Seasonal changes in the abundance of exothermic organisms can be expected with climate change if warmer temperatures can induce changes in their phenology. Given the increased time for ectothermic organism development at lower temperatures, we asked whether population dynamics of the house mosquito, Culex pipiens s.l. (L.) (Diptera: Culicidae), in Jeju-do (South Korea), an island with a gradient of warming temperatures from north to south, showed differences in sensitivity to changes in temperature along the warming gradient. In addition, we asked whether synchrony, that is, the degree of concerted fluctuations in mosquito abundance across locations, was affected by the temperature gradient. We found the association of mosquito abundance with temperature to be delayed by 2 wk in the north when compared with the south. The abundance across all our sampling locations had a flat synchrony profile that could reflect impacts of rainfall and average temperature on the average of all our samples. Finally, our results showed that population synchrony across space can emerge even when abundance is differentially impacted by an exogenous factor across an environmental gradient.

Climate change and West Nile virus in a highly endemic region of North America

The Canadian prairie provinces of Manitoba, Saskatchewan, and Alberta have reported the highest human incidence of clinical cases of West Nile virus (WNV) infection in Canada. The primary vector for WVN in this region is the mosquito Culex tarsalis. This study used constructed models and biological thresholds to predict the spatial and temporal distribution of Cx. tarsalis and WNV infection rate in the prairie provinces under a range of potential future climate and habitat conditions. We selected one median and two extreme outcome scenarios to represent future climate conditions in the 2020 (2010–2039), 2050 (2040–2069) and 2080 (2070–2099) time slices. In currently endemic regions, the projected WNV infection rate under the median outcome scenario in 2050 raised 17.91 times (ranged from 1.29-27.45 times for all scenarios and time slices) comparing to current climate conditions. Seasonal availability of Cx. tarsalis infected with WNV extended from June to August to include May and September. Moreover, our models predicted northward range expansion for Cx. tarsalis (1.06–2.56 times the current geographic area) and WNV (1.08–2.34 times the current geographic area). These findings predict future public and animal health risk of WNV in the Canadian prairie provinces.

Remote sensing of climatic anomalies and West Nile virus incidence in the northern Great Plains of the United States

The northern Great Plains (NGP) of the United States has been a hotspot of West Nile virus (WNV) incidence since 2002. Mosquito ecology and the transmission of vector-borne disease are influenced by multiple environmental factors, and climatic variability is an important driver of inter-annual variation in WNV transmission risk. This study applied multiple environmental predictors including land surface temperature (LST), the normalized difference vegetation index (NDVI) and actual evapotranspiration (ETa) derived from Moderate-Resolution Imaging Spectroradiometer (MODIS) products to establish prediction models for WNV risk in the NGP. These environmental metrics are sensitive to seasonal and inter-annual fluctuations in temperature and precipitation, and are hypothesized to influence mosquito population dynamics and WNV transmission. Non-linear generalized additive models (GAMs) were used to evaluate the influences of deviations of cumulative LST, NDVI, and ETa on inter-annual variations of WNV incidence from 2004–2010. The models were sensitive to the timing of spring green up (measured with NDVI), temperature variability in early spring and summer (measured with LST), and moisture availability from late spring through early summer (measured with ETa), highlighting seasonal changes in the influences of climatic fluctuations on WNV transmission. Predictions based on these variables indicated a low WNV risk across the NGP in 2011, which is concordant with the low case reports in this year. Environmental monitoring using remote-sensed data can contribute to surveillance of WNV risk and prediction of future WNV outbreaks in space and time.

Satellite Microwave Remote Sensing for Environmental Modeling of Mosquito Population Dynamics

Environmental variability has important influences on mosquito life cycles and understanding the spatial and temporal patterns of mosquito populations is critical for mosquito control and vector-borne disease prevention. Meteorological data used for model-based predictions of mosquito abundance and life cycle dynamics are typically acquired from ground-based weather stations; however, data availability and completeness are often limited by sparse networks and resource availability. In contrast, environmental measurements from satellite remote sensing are more spatially continuous and can be retrieved automatically. This study compared environmental measurements from the NASA Advanced Microwave Scanning Radiometer on EOS (AMSR-E) and in situ weather station data to examine their ability to predict the abundance of two important mosquito species (Aedes vexans and Culex tarsalis) in Sioux Falls, South Dakota, USA from 2005 to 2010. The AMSR-E land parameters included daily surface water inundation fraction, surface air temperature, soil moisture, and microwave vegetation opacity. The AMSR-E derived models had better fits and higher forecasting accuracy than models based on weather station data despite the relatively coarse (25-km) spatial resolution of the satellite data. In the AMSR-E models, air temperature and surface water fraction were the best predictors of Aedes vexans, whereas air temperature and vegetation opacity were the best predictors of Cx. tarsalis abundance. The models were used to extrapolate spatial, seasonal, and interannual patterns of climatic suitability for mosquitoes across eastern South Dakota. Our findings demonstrate that environmental metrics derived from satellite passive microwave radiometry are suitable for predicting mosquito population dynamics and can potentially improve the effectiveness of mosquito-borne disease early warning systems.