Landscape, demographic, entomological, and climatic associations with human disease incidence of West Nile virus in the state of Iowa, USA

Impact of climate change on the global circulation of West Nile virus and adaptation responses: a scoping review

BACKGROUND

West Nile virus (WNV), the most widely distributed flavivirus causing encephalitis globally, is a vector-borne pathogen of global importance. The changing climate is poised to reshape the landscape of various infectious diseases, particularly vector-borne ones like WNV. Understanding the anticipated geographical and range shifts in disease transmission due to climate change, alongside effective adaptation strategies, is critical for mitigating future public health impacts. This scoping review aims to consolidate evidence on the impact of climate change on WNV and to identify a spectrum of applicable adaptation strategies.

MAIN BODY

We systematically analyzed research articles from PubMed, Web of Science, Scopus, and EBSCOhost. Our criteria included English-language research articles published between 2007 and 2023, focusing on the impacts of climate change on WNV and related adaptation strategies. We extracted data concerning study objectives, populations, geographical focus, and specific findings. Literature was categorized into two primary themes: 1) climate-WNV associations, and 2) climate change impacts on WNV transmission, providing a clear understanding. Out of 2168 articles reviewed, 120 met our criteria. Most evidence originated from North America (59.2%) and Europe (28.3%), with a primary focus on human cases (31.7%). Studies on climate-WNV correlations (n = 83) highlighted temperature (67.5%) as a pivotal climate factor. In the analysis of climate change impacts on WNV (n = 37), most evidence suggested that climate change may affect the transmission and distribution of WNV, with the extent of the impact depending on local and regional conditions. Although few studies directly addressed the implementation of adaptation strategies for climate-induced disease transmission, the proposed strategies (n = 49) fell into six categories: 1) surveillance and monitoring (38.8%), 2) predictive modeling (18.4%), 3) cross-disciplinary collaboration (16.3%), 4) environmental management (12.2%), 5) public education (8.2%), and 6) health system readiness (6.1%). Additionally, we developed an accessible online platform to summarize the evidence on climate change impacts on WNV transmission ( https://2xzl2o-neaop.shinyapps.io/WNVScopingReview/ ).

CONCLUSIONS

This review reveals that climate change may affect the transmission and distribution of WNV, but the literature reflects only a small share of the global WNV dynamics. There is an urgent need for adaptive responses to anticipate and respond to the climate-driven spread of WNV. Nevertheless, studies focusing on these adaptation responses are sparse compared to those examining the impacts of climate change. Further research on the impacts of climate change and adaptation strategies for vector-borne diseases, along with more comprehensive evidence synthesis, is needed to inform effective policy responses tailored to local contexts.

Temporal and Spatial Synchronicity in West Nile Virus Cases Along the Central Flyway, USA

This study of West Nile virus (WNV) examined the possibility of avian transmission to explain synchronicity in the year-to-year variability of WNV case numbers from Texas northward to the Dakotas, and reasons for the large case numbers on the northern Great Plains. We determined correlation coefficients between annual disease incidence per 100,000 people among states within the Great Plains Region, as well as the Central Flyway. There was spatial and temporal synchronicity, as evidenced by Pearson "r," with values along the core of the Central Flyway (Oklahoma, Kansas, Nebraska, and South Dakota) varying between 0.69 and 0.79. Correlations for North Dakota (r = 0.6), however, were affected by local conditions. The concept of relative amplification is helpful in explaining why northerly states along the Central Flyway have larger annual case numbers per 100,000 than Texas but preserve the temporal signal. States differed in their capacity for amplifying the temporal signal in case numbers. For example, Nebraska, South Dakota, and North Dakota case numbers were commonly amplified relative to Texas, with Oklahoma and Kansas deamplified. Relative amplification factors for all states increased as a function of increasing case numbers in Texas. Thus, increased numbers of initially infected birds in Texas likely led to the rapid intensification of the zoonotic cycle as compared to more typical years. The study also confirmed the importance of winter weather in locally modulating disease cases. North Dakota appeared most impacted by these factors to the extent of reducing WNV case numbers in colder years and years with deep snow.

Assessing the Influence of Climate on the Spatial Pattern of West Nile Virus Incidence in the United States

BACKGROUND

West Nile virus (WNV) is the leading cause of mosquito-borne disease in humans in the United States. Since the introduction of the disease in 1999, incidence levels have stabilized in many regions, allowing for analysis of climate conditions that shape the spatial structure of disease incidence.

OBJECTIVES

Our goal was to identify the seasonal climate variables that influence the spatial extent and magnitude of WNV incidence in humans.

METHODS

We developed a predictive model of contemporary mean annual WNV incidence using U.S. county-level case reports from 2005 to 2019 and seasonally averaged climate variables. We used a random forest model that had an out-of-sample model performance of R2=0.61.

RESULTS

Our model accurately captured the V-shaped area of higher WNV incidence that extends from states on the Canadian border south through the middle of the Great Plains. It also captured a region of moderate WNV incidence in the southern Mississippi Valley. The highest levels of WNV incidence were in regions with dry and cold winters and wet and mild summers. The random forest model classified counties with average winter precipitation levels <23.3mm/month as having incidence levels over 11 times greater than those of counties that are wetter. Among the climate predictors, winter precipitation, fall precipitation, and winter temperature were the three most important predictive variables.

DISCUSSION

We consider which aspects of the WNV transmission cycle climate conditions may benefit the most and argued that dry and cold winters are climate conditions optimal for the mosquito species key to amplifying WNV transmission. Our statistical model may be useful in projecting shifts in WNV risk in response to climate change. https://doi.org/10.1289/EHP10986.

An assessment of remotely sensed environmental variables on Dengue epidemiology in Central India

In recent decades, dengue has been expanding rapidly in the tropical cities. Even though environmental factors and landscape features profoundly impact dengue vector abundance and disease epidemiology, significant gaps exist in understanding the role of local environmental heterogeneity on dengue epidemiology in India. In this study, we assessed the role of remotely sensed climatic factors (rainfall, temperature and humidity) and landscape variables (land use pattern, vegetation and built up density) on dengue incidence (2012–2019) in Bhopal city, Central India. Dengue hotspots in the city were assessed through geographical information system based spatial statistics. Dengue incidence increased from 0.59 cases in 2012 to 9.11 cases in 2019 per 10,000 inhabitants, and wards located in Southern Bhopal were found to be dengue hotspots. Distributed lag non-linear model combined with quasi Poisson regression was used to assess the exposure-response association, relative risk (RR), and delayed effects of environmental factors on dengue incidence. The analysis revealed a non-linear relationship between meteorological variables and dengue cases. The model shows that the risk of dengue cases increases with increasing mean temperature, rainfall and absolute humidity. The highest RR of dengue cases (~2.0) was observed for absolute humidity ≥60 g/m³ with a 5–15 week lag. Rapid urbanization assessed by an increase in the built-up area (a 9.1% increase in 2020 compared to 2014) could also be a key factor driving dengue incidence in Bhopal city. The study sheds important insight into the synergistic effects of both the landscape and climatic factors on the transmission dynamics of dengue. Furthermore, the study provides key baseline information on the climatic variables that can be used in the micro-level dengue prediction models in Bhopal and other cities with similar climatic conditions.

Dengue, a viral disease transmitted by infected Aedes mosquitoes, is a major public health concern globally. In addition to its increased incidence in recent years, dengue is also spreading to new geographical regions. Local environmental factors are known to modify the mosquito vector density that directly impacts dengue virus transmission. Understanding the influence of environmental factors (meteorological conditions and landscape features) on dengue epidemiology in local settings is important for focused dengue intervention. Here, by utilizing dengue incidence and remotely sensed environmental data from 2012–2019, we have assessed the role of environmental factors in driving dengue virus transmission in the city of Bhopal in Central India. During the study period, a 14.5 fold increase in dengue incidence was observed in Bhopal city, which is way higher than the 2.3 fold increase reported at the national level. The risk of dengue virus transmission was higher with higher temperature and absolute humidity. An increase in built-up area, a proxy for urbanization, was found to be another predictor of increased dengue incidence in Bhopal. These findings can provide a stepping-stone for the development of dengue prediction models and the identification of dengue hotspots in order to improve vector control of this disease in cities with similar environmental conditions.

Relative Influence of Land Use, Mosquito Abundance, and Bird Communities in Defining West Nile Virus Infection Rates in Culex Mosquito Populations

Since its introduction to North America in 1999, the West Nile virus (WNV) has resulted in over 50,000 human cases and 2400 deaths. WNV transmission is maintained via mosquito vectors and avian reservoir hosts, yet mosquito and avian infections are not uniform across ecological landscapes. As a result, it remains unclear whether the ecological communities of the vectors or reservoir hosts are more predictive of zoonotic risk at the microhabitat level. We examined this question in central Iowa, representative of the midwestern United States, across a land use gradient consisting of suburban interfaces with natural and agricultural habitats. At eight sites, we captured mosquito abundance data using New Jersey light traps and monitored bird communities using visual and auditory point count surveys. We found that the mosquito minimum infection rate (MIR) was better predicted by metrics of the mosquito community than metrics of the bird community, where sites with higher proportions of Culex pipiens group mosquitoes during late summer (after late July) showed higher MIRs. Bird community metrics did not significantly influence mosquito MIRs across sites. Together, these data suggest that the microhabitat suitability of Culex vector species is of greater importance than avian community composition in driving WNV infection dynamics at the urban and agricultural interface.

Spatiotemporal Modeling of Zoonotic Arbovirus Transmission in Northeastern Florida Using Sentinel Chicken Surveillance and Earth Observation Data

The irregular timing and spatial variation in the zoonotic arbovirus spillover from vertebrate hosts to humans and livestock present challenges to predicting spillover occurrence over time and across broader geographic areas, compromising effective prevention and control strategies. The objective of this study was to quantify the effects of the landscape composition and configuration and dynamic weather events on the 2018 spatiotemporal distribution of eastern equine encephalitis virus (EEEV) (Togaviridae, Alphavirus) and West Nile virus (WNV) (Flaviviridae, Flavivirus) sentinel chicken seroconversion in northeastern Florida. We used a modeling framework that explicitly accounts for joint spatial and temporal effects and incorporates key EO (Earth Observation) information on the climate and landscape in order to more accurately quantify the environmental effects on the transmission to sentinel chickens. We investigated the environmental effects using Bernoulli generalized linear mixed effects models (GLMMs), including a site-level random effect, and then added spatial random effects and spatiotemporal random effects in subsequent runs. The models were executed using an integrated nested Laplace approximation (INLA) and a stochastic partial differential equation (SPDE) approach in R-INLA. The GLMMs that included a spatiotemporal random effect performed better relative to models that included only spatial random effects and also performed better than non-spatial models. The results indicated a strong spatiotemporal structure in the seroconversion for both viruses, but EEEV exhibited a more punctuated and compact structure at the beginning of the sampling season, while WNV exhibited a more gradual and diffuse structure across the study area toward the end of the sampling season. The percentage of cypress–tupelo wetland land cover within 3500 m of coop sites and the edge density of the forest land cover within 500 m had a strong positive effect on the EEEV seroconversion, while the best fitting model for WNV was the intercept-only model with spatiotemporal random effects. The lagged climatic variables included in our study did not have a strong effect on the seroconversion for either virus when accounting for temporal autocorrelation, demonstrating the utility of capturing this structure to avoid type I errors. The predictive accuracy for out-of-sample data for the EEEV seroconversion demonstrates the potential to develop a framework that incorporates temporal dynamics in order to better predict arbovirus transmission.

Updated distribution maps of predominant Culex mosquitoes across the Americas

BACKGROUND

Estimates of the geographical distribution of Culex mosquitoes in the Americas have been limited to state and provincial levels in the United States and Canada and based on data from the 1980s. Since these estimates were made, there have been many more documented observations of mosquitoes and new methods have been developed for species distribution modeling. Moreover, mosquito distributions are affected by environmental conditions, which have changed since the 1980s. This calls for updated estimates of these distributions to understand the risk of emerging and re-emerging mosquito-borne diseases.

METHODS

We used contemporary mosquito data, environmental drivers, and a machine learning ecological niche model to create updated estimates of the geographical range of seven predominant Culex species across North America and South America: Culex erraticus, Culex nigripalpus, Culex pipiens, Culex quinquefasciatus, Culex restuans, Culex salinarius, and Culex tarsalis.

RESULTS

We found that Culex mosquito species differ in their geographical range. Each Culex species is sensitive to both natural and human-influenced environmental factors, especially climate and land cover type. Some prefer urban environments instead of rural ones, and some are limited to tropical or humid areas. Many are found throughout the Central Plains of the USA.

CONCLUSIONS

Our updated contemporary Culex distribution maps may be used to assess mosquito-borne disease risk. It is critical to understand the current geographical distributions of these important disease vectors and the key environmental predictors structuring their distributions not only to assess current risk, but also to understand how they will respond to climate change. Since the environmental predictors structuring the geographical distribution of mosquito species varied, we hypothesize that each species may have a different response to climate change.

Exploring the socio-economic and environmental components of infectious diseases using multivariate geovisualization: West Nile Virus

Background

This study postulates that underlying environmental conditions and a susceptible population's socio-economic status should be explored simultaneously to adequately understand a vector borne disease infection risk. Here we focus on West Nile Virus (WNV), a mosquito borne pathogen, as a case study for spatial data visualization of environmental characteristics of a vector's habitat alongside human demographic composition for understanding potential public health risks of infectious disease. Multiple efforts have attempted to predict WNV environmental risk, while others have documented factors related to human vulnerability to the disease. However, analytical modeling that combines the two is difficult due to the number of potential explanatory variables, varying spatial resolutions of available data, and differing research questions that drove the initial data collection. We propose that the use of geovisualization may provide a glimpse into the large number of potential variables influencing the disease and help distill them into a smaller number that might reveal hidden and unknown patterns. This geovisual look at the data might then guide development of analytical models that can combine environmental and socio-economic data.

Methods

Geovisualization was used to integrate an environmental model of the disease vector's habitat alongside human risk factors derived from socio-economic variables. County level WNV incidence rates from California, USA, were used to define a geographically constrained study area where environmental and socio-economic data were extracted from 1,133 census tracts. A previously developed mosquito habitat model that was significantly related to WNV infected dead birds was used to describe the environmental components of the study area. Self-organizing maps found 49 clusters, each of which contained census tracts that were more similar to each other in terms of WNV environmental and socio-economic data. Parallel coordinate plots permitted visualization of each cluster's data, uncovering patterns that allowed final census tract mapping exposing complex spatial patterns contained within the clusters.

Results

Our results suggest that simultaneously visualizing environmental and socio-economic data supports a fuller understanding of the underlying spatial processes for risks to vector-borne disease. Unexpected patterns were revealed in our study that would be useful for developing future multilevel analytical models. For example, when the cluster that contained census tracts with the highest median age was examined, it was determined that those census tracts only contained moderate mosquito habitat risk. Likewise, the cluster that contained census tracts with the highest mosquito habitat risk had populations with moderate median age. Finally, the cluster that contained census tracts with the highest WNV human incidence rates had unexpectedly low mosquito habitat risk.

West Nile Virus: An Update on Pathobiology, Epidemiology, Diagnostics, Control and "One Health" Implications

West Nile virus (WNV) is an important zoonotic flavivirus responsible for mild fever to severe, lethal neuroinvasive disease in humans, horses, birds, and other wildlife species. Since its discovery, WNV has caused multiple human and animal disease outbreaks in all continents, except Antarctica. Infections are associated with economic losses, mainly due to the cost of treatment of infected patients, control programmes, and loss of animals and animal products. The pathogenesis of WNV has been extensively investigated in natural hosts as well as in several animal models, including rodents, lagomorphs, birds, and reptiles. However, most of the proposed pathogenesis hypotheses remain contentious, and much remains to be elucidated. At the same time, the unavailability of specific antiviral treatment or effective and safe vaccines contribute to the perpetuation of the disease and regular occurrence of outbreaks in both endemic and non-endemic areas. Moreover, globalisation and climate change are also important drivers of the emergence and re-emergence of the virus and disease. Here, we give an update of the pathobiology, epidemiology, diagnostics, control, and “One Health” implications of WNV infection and disease.

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.

Epidemic West Nile Virus Infection Rates and Endemic Population Dynamics Among South Dakota Mosquitoes: A 15-yr Study from the United States Northern Great Plains

Mosquito surveillance has been conducted across South Dakota (SD) to record and track potential West Nile virus (WNV) vectors since 2004. During this time, communities from 29 counties collected nearly 5.5 million mosquitoes, providing data from over 60,000 unique trapping nights. The nuisance mosquito, Aedes vexans (Meigen) was the most abundant species in the state (39.9%), and most abundant in most regions. The WNV vector, Culex tarsalis Coquillett (Diptera: Culicidae), was the second most abundant species (20.5%), and 26 times more abundant than the other Culex species that also transmit WNV. However, geographic variation did exist between WNV vector species, as well as relative abundance of vector and nuisance mosquitoes. The abundance of Ae. vexans decreased from east to west in South Dakota, resulting in an increase in the relative abundance of Cx. tarsalis. Other species are reported in this study, with various relative abundances throughout the different regions of South Dakota. WNV infection rates of mosquitoes showed that Cx. tarsalis had the most positive sampling pools and the highest vector index of all the species tested. This study addressed the need for an updated summary of the predominant mosquito species present in the United States Northern Great Plain and provides infection rate data for WNV among these predominant species.

Influence of climatic variables on the Aedes aegypti and Culex quinquefasciatus populations in Mato Grosso, Brazil

INTRODUCTION

Aedes aegypti and Culex quinquefasciatus are vector species responsible for the transmission of important arboviruses.

METHODS

Adult mosquitoes were collected in the urban areas of four municipalities in Mato Grosso within 1 year.

RESULTS

A total of 19,110 mosquitoes were collected. Among them, 16,578 (86,8%) were C. quinquefasciatus (44% female and 56% male); 2,483 (13%), A. (Stegomyia) aegypti (54% female and 46% male); and 49 (0,30%), from the genus Psorophora, Anopheles, Coquilettidia, and Sabethes. A significant correlation was observed between the number of mosquitoes from all species and dew point (female mosquitoes, p = 0.001; male mosquitoes, p = 0.001).

CONCLUSIONS

The results of this study may be used as environmental indicators of mosquito populations.

A 15 Year Evaluation of West Nile Virus in Wisconsin: Effects on Wildlife and Human Health

West Nile virus (WNV) is the most important and widespread mosquito-borne virus in the United States (U.S.). WNV has the ability to spread rapidly and effectively, infecting more than 320 bird and mammalian species. An examination of environmental conditions and the health of keystone species may help predict the susceptibility of various habitats to WNV and reveal key risk factors, annual trends, and vulnerable regions. Since 2002, WNV outbreaks in Wisconsin varied by species, place, and time, significantly affected by unique climatic, environmental, and geographical factors. During a 15 year period, WNV was detected in 71 of 72 counties, resulting in 239 human and 1397 wildlife cases. Controlling for population and sampling efforts in Wisconsin, rates of WNV are highest in the western and northwestern rural regions of the state. WNV incidence rates were highest in counties with low human population densities, predominantly wetland, and at elevations greater than 1000 feet. Resources for surveillance, prevention, and detection of WNV were lowest in rural counties, likely resulting in underestimation of cases. Overall, increasing mean temperature and decreasing precipitation showed positive influence on WNV transmission in Wisconsin. This study incorporates the first statewide assessment of WNV in Wisconsin.

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.

Crossover Dynamics of Culex (Diptera: Culicidae) Vector Populations Determine WNV Transmission Intensity

First introduced into the United States in 1999, West Nile virus (WNV) has become endemic and has established itself as the predominant mosquito-borne arbovirus in North America. Transmitted by mosquitoes of the genus Culex, regional landscapes influence local vector species abundance, creating different mosquito ecologies that drive local transmission dynamics. In central Iowa, two mosquito species, Culex restuans Theobald and Culex pipiens Linnaeus, serve as the predominant mosquito vectors. Importantly, these mosquito populations are influenced by seasonal patterns in their abundance, with Cx. restuans preferring cool, early spring temperatures, while Cx. pipiens prefer the warmer, mid- to late-summer months. The point of the season at which Cx. pipiens becomes the dominant species is generally referred to as a 'crossover' period. To better understand the influence of crossover dynamics on WNV transmission, we examined environmental and mosquito abundance data, as well as mosquito infection rates and human disease cases from 2016 to 2018. We demonstrate that temperature influences the timing and duration of the crossover period, influencing mosquito abundance and human disease transmission. Together, these results suggest that Culex species crossover is an important variable of WNV transmission dynamics, which may provide an early warning indicators of increased WNV transmission.

West Nile Virus Mosquito Vectors in North America

In North America, the geographic distribution, ecology, and vectorial capacity of a diverse assemblage of mosquito species belonging to the genus Culex determine patterns of West Nile virus transmission and disease risk. East of the Mississippi River, mostly ornithophagic Culex pipiens L. complex mosquitoes drive intense enzootic transmission with relatively small numbers of human cases. Westward, the presence of highly competent Culex tarsalis (Coquillett) under arid climate and hot summers defines the regions with the highest human risk. West Nile virus human risk distribution is not uniform geographically or temporally within all regions. Notable geographic 'hotspots' persist with occasional severe outbreaks. Despite two decades of comprehensive research, several questions remain unresolved, such as the role of non-Culex bridge vectors, which are not involved in the enzootic cycle, but may be involved in virus transmission to humans. The absence of bridge vectors also may help to explain the frequent lack of West Nile virus 'spillover' into human populations despite very intense enzootic amplification in the eastern United States. This article examines vectorial capacity and the eco-epidemiology of West Nile virus mosquito vectors in four geographic regions of North America and presents some of the unresolved questions.

Risk factors associated with sustained circulation of six zoonotic arboviruses: a systematic review for selection of surveillance sites in non-endemic areas

Arboviruses represent a significant burden to public health and local economies due to their ability to cause unpredictable and widespread epidemics. To maximize early detection of arbovirus emergence in non-endemic areas, surveillance efforts should target areas where circulation is most likely. However, identifying such hotspots of potential emergence is a major challenge. The ecological conditions leading to arbovirus outbreaks are shaped by complex interactions between the virus, its vertebrate hosts, arthropod vector, and abiotic environment that are often poorly understood. Here, we systematically review the ecological risk factors associated with the circulation of six arboviruses that are of considerable concern to northwestern Europe. These include three mosquito-borne viruses (Japanese encephalitis virus, West Nile virus, Rift Valley fever virus) and three tick-borne viruses (Crimean-Congo hemorrhagic fever virus, tick-borne encephalitis virus, and louping-ill virus). We consider both intrinsic (e.g. vector and reservoir host competence) and extrinsic (e.g. temperature, precipitation, host densities, land use) risk factors, identify current knowledge gaps, and discuss future directions. Our systematic review provides baseline information for the identification of regions and habitats that have suitable ecological conditions for endemic circulation, and therefore may be used to target early warning surveillance programs aimed at detecting multi-virus and/or arbovirus emergence.

Using Earth observation images to inform risk assessment and mapping of climate change-related infectious diseases

The number of human cases of several climate-related infectious diseases, including tick- and mosquito-borne diseases, has increased in Canada and other parts of the world since the end of the last century. Predicting and mapping the risks associated with these diseases using environmental and climatic determinants derived from satellite images is an emerging method that can support research, surveillance, prevention and control activities and help to better assess the impacts of climate change in Canada. Earth observation images can be used to systematically monitor changes in the Earth's surface and atmosphere at different scales of time and space. These images can inform estimation and monitoring of environmental and climatic determinants, and thus disease prediction and risk mapping. The current array of Earth observation satellites provides access to a large quantity and variety of data. These data have different characteristics in terms of spatial, temporal and thematic precision and resolution. The objectives of this overview are to describe how Earth observation images may inform risk assessment and mapping of tick-borne and mosquito-borne diseases in Canada, their potential benefits and limitations, the implications and next steps.

Long-term surveillance defines spatial and temporal patterns implicating Culex tarsalis as the primary vector of West Nile virus

West Nile virus (WNV) has become the most epidemiologically important mosquito-borne disease in the United States, causing ~50,000 cases since its introduction in 1999. Transmitted primarily by Culex species, WNV transmission requires the complex interplay between bird reservoirs and mosquito vectors, with human cases the result of epizootic spillover. To better understand the intrinsic factors that drive these interactions, we have compiled infection data from sentinel chickens, mosquito vectors, and human cases in Iowa over a 15 year period (2002-2016) to better understand the spatial and temporal components that drive WNV transmission. Supplementing these findings with mosquito abundance, distribution, and host preferences data, we provide strong support that Culex tarsalis is the most important vector of human WNV infections in the region. Together, our analysis provides new insights into WNV infection patterns in multiple hosts and highlights the importance of long-term surveillance to understand the dynamics of mosquito-borne-disease transmission.

Surveillance of Mosquitoes (Diptera: Culicidae) in Southern Iowa, 2016

The mosquito fauna of Iowa has been extensively investigated over several decades, providing a wealth of information regarding species distributions, relative abundance, temporal activity patterns, and identifying vectors of medical importance. However, these investigations have had unequal coverage, leaving the mosquito fauna in some parts of the state, including southern Iowa, largely uncharacterized. With the heightened public health threat of Zika virus in the summer of 2016, greater emphasis was placed on surveying for two potential Zika virus vectors: Aedes (Stegomyia) albopictus (Skuse) and Aedes (Stegomyia) aegypti (Linnaeus). Southern Iowa became an area of interest due to the range of Ae. Albopictus, potentially extending into this part of the state. Employing CO2-baited Centers for Disease Control and Prevention light traps and BG-Sentinel traps, our targeted trapping efforts in southern Iowa did not yield either Ae. albopictus or Ae. aegypti. However, the geographical expansion of our trapping efforts did lend valuable insights into the mosquito fauna of southern Iowa. Mosquito species such as Aedes atropalpus (Coquillett), Culex erraticus (Dyar and Knab), and several Psorophora species once presumed rare or uncommon in the state were found to be more prevalent in this ecologically diverse region, augmenting our understanding of mosquito distributions in the state. Moreover, these surveillance efforts established baseline data for continued monitoring of the potential introduction and spread of invasive mosquito species in Iowa as part of an integrated mosquito management program.

Predictive Modeling for West Nile Virus and Mosquito Surveillance in Lubbock, Texas

West Nile virus (WNV) was first detected in North America during 1999, and has since spread throughout the contiguous USA. West Nile virus causes West Nile fever and the more severe West Nile neuroinvasive disease. As part of a WNV vector surveillance program, we collected mosquitoes in Lubbock, Texas, using CO₂-baited encephalitic vector survey (EVS) traps. During 219 wk from 2009 through 2017, EVS traps were operated for 1,748 trap nights, resulting in more than 101,000 mosquitoes captured. Weekly, selected female mosquito specimens were pooled by species and trap site, and screened for WNV using reverse transcription-polymerase chain reaction assay. Mosquitoes positive for WNV were detected during 16.9% (37/219) of the weeks. Using this information, we constructed a statistical model to predict the probability of detecting an infection within a mosquito pool as a factor of weather variables. The final model indicated that detection of WNV in mosquitoes was negatively associated with the week of year squared and average wind from 3 wk prior to sampling, and was positively associated with week of year, average visibility, average humidity from 2 wk prior to sampling, and average dew point from 4 wk prior to sampling. The model developed in this study may aid public health and vector control programs in swift and effective decision making relative to city-wide mosquito control efforts by predicting when the chances of mosquitoes having WNV are at their greatest.

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.

Spatio-Temporal Distribution of Vector-Host Contact (VHC) Ratios and Ecological Niche Modeling of the West Nile Virus Mosquito Vector, Culex quinquefasciatus, in the City of New Orleans, LA, USA

The consistent sporadic transmission of West Nile Virus (WNV) in the city of New Orleans justifies the need for distribution risk maps highlighting human risk of mosquito bites. We modeled the influence of biophysical and socioeconomic metrics on the spatio-temporal distributions of presence/vector-host contact (VHC) ratios of WNV vector, Culex quinquefasciatus, within their flight range. Biophysical and socioeconomic data were extracted within 5-km buffer radii around sampling localities of gravid female Culex quinquefasciatus. The spatio-temporal correlations between VHC data and 33 variables, including climate, land use-land cover (LULC), socioeconomic, and land surface terrain were analyzed using stepwise linear regression models (RM). Using MaxEnt, we developed a distribution model using the correlated predicting variables. Only 12 factors showed significant correlations with spatial distribution of VHC ratios (R² = 81.62, p < 0.01). Non-forested wetland (NFWL), tree density (TD) and residential-urban (RU) settings demonstrated the strongest relationship. The VHC ratios showed monthly environmental resilience in terms of number and type of influential factors. The highest prediction power of RU and other urban and built up land (OUBL), was demonstrated during May-August. This association was positively correlated with the onset of the mosquito WNV infection rate during June. These findings were confirmed by the Jackknife analysis in MaxEnt and independently collected field validation points. The spatial and temporal correlations of VHC ratios and their response to the predicting variables are discussed.

West Nile virus and its vectors

West Nile virus (WNV Flaviviridae; Flavivrus) is the most geographically widespread arbovirus in the world and the leading cause of arboviral encephalitis globally. Worldwide, WNV is maintained in an enzootic cycle between primarily Culex spp. mosquitoes and birds, with human infection and disease resulting from enzootic spillover. Dynamic and complex intrinsic and extrinsic factors contribute to the temporal and spatial variability in WNV transmission. The most current information on the relative contribution of each of these factors is reviewed and a case to incorporate detailed and localized environmental and genetic data into predictive models is presented.

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.

Application of landscape epidemiology to assess potential public health risk due to poor sanitation

Clear identification of areas vulnerable to waterborne diseases is essential for protecting community health. This is particularly important in developing countries where unsafe disposal of domestic wastewater and limited potable water supply pose potential public health risks. However, data paucity can be a compounding issue. Under these circumstances, landscape epidemiology can be applied as a resource efficient approach for mapping potential disease risk areas associated with poor sanitation. However, in order to realise the full potential offered by this approach, an in-depth understanding of the impact of different classes of an explanatory variable on a target disease and the validity of hotspot analysis using limited datasets is needed. Accordingly, this research study focused on typhoid and diarrhoea incidence with respect to different classes of elevation, flood inundation, land use, soil permeability, population density and rainfall as explanatory variables. An integrated methodology consisting of hot spot analysis and Poisson regression was employed to map potential disease risk areas. The study findings confirmed the significant differences in the influence exerted by the various classes of an explanatory variable in relation to a target disease. The results also confirmed the feasibility of the hotspot analysis for identifying areas vulnerable to the target diseases using a limited dataset. The study outcomes are expected to contribute to creating an in-depth understanding of the relationship between disease prevalence and associated landscape factors for the delineation of disease risk zones in the context of data paucity.

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

BACKGROUND

The 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.

METHODS

We 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.

RESULTS

LSR 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).

CONCLUSIONS

The 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.

Transmission Dynamics of the West Nile Virus in Mosquito Vector Populations under the Influence of Weather Factors in the Danube Delta, Romania

Mosquitoes were collected in the Danube Delta during the active seasons of 2011-2013. For Culex spp. mosquitoes, the abundance was calculated. Culex pipiens (sensu lato), (s.l.) and Culex modestus pools were tested for the presence of West Nile virus (WNV) genome, and the maximum likelihood of the infection rate was established. Mean daily temperatures and precipitation were obtained for the closest meteorological station. A negative binominal model was used to evaluate linkages between the temperature/precipitation and mosquito population size. A zero-inflated negative binomial model was used to test the relationship between the temperature and the infection rate. A single complex model for infection rate prediction was also used. The linkages were calculated for lag 0 and for 10 days earlier (lag 1), 20 days earlier (lag 2), and 30 days earlier (lag 3). Significant positive linkages (P < 0.001) were detected between temperature and mosquito population size for lag 1, lag 2, and lag 3. The linkages between temperature and infection rates were positive and significant for lag 2 and lag 3. Negative significant (P < 0.001) results were detected between precipitation and infection rates for lags 1, 2, and 3. The complex model showed that the best predictors for infection rate are the temperature, 20 days earlier (positive linkage) and the precipitation, 30 days earlier (negative linkage). Positive temperature anomalies in spring and summer and rainfall decrease contributed to the increase in the Culex spp. abundance and accelerated the WNV amplification in mosquito vector populations in the following weeks.

Climatic, ecological, and socioeconomic factors associated with West Nile virus incidence in Atlanta, Georgia, U.S.A

The integrated effects of the many risk factors associated with West Nile virus (WNV) incidence are complex and not well understood. We studied an array of risk factors in and around Atlanta, GA, that have been shown to be linked with WNV in other locations. This array was comprehensive and included climate and meteorological metrics, vegetation characteristics, land use / land cover analyses, and socioeconomic factors. Data on mosquito abundance and WNV mosquito infection rates were obtained for 58 sites and covered 2009-2011, a period following the combined storm water - sewer overflow remediation in that city. Risk factors were compared to mosquito abundance and the WNV vector index (VI) using regression analyses individually and in combination. Lagged climate variables, including soil moisture and temperature, were significantly correlated (positively) with vector index as were forest patch size and percent pine composition of patches (both negatively). Socioeconomic factors that were most highly correlated (positively) with the VI included the proportion of low income households and homes built before 1960 and housing density. The model selected through stepwise regression that related risk factors to the VI included (in the order of decreasing influence) proportion of houses built before 1960, percent of pine in patches, and proportion of low income households.

Ecological niche modeling of mosquito vectors of West Nile virus in St. John's County, Florida, USA

Background

The lack of available vaccines and consistent sporadic transmission of WNV justify the need for mosquito vector control and prediction of their geographic distribution. However, the distribution of WNV transmission is dependent on the mosquito vector and the ecological requirements, which vary from one place to another.

Methods

Presence/density data of two WNV mosquito vectors, Culex nigripalpus and Cx. quinquefasciatus, was extracted within 5 km buffer zones around seropositive records of sentinel chickens in order to delineate their predicting variables and model the habitat suitability of probable infective mosquito using MaxEnt software. Different correlations between density data of the extracted mosquito vectors and 27 climate, land use-land cover, and land surface terrain variables were analyzed using linear regression analysis. Accordingly, the correlated predicting variables were used in building up habitat suitability model for the occurrence records of both mosquito vectors using MaxEnt.

Results

The density of both WNV mosquito vectors showed variation in their ecological requirements. Eight predicting variables, out of 27, had significant influence on density of Cx. nigripalpus. Precipitation of driest months was shown to be the best predicting variable for the density of this vector (R² = 41.70). Whereas, two variables were proven to predict the distribution of Cx. quinquefasciatus density. Vegetation showed the maximum predicting gain to the density of this mosquito vector (R² = 15.74), where nestling birds, in particular exotics, are found. Moreover, Jackknife analysis in MaxEnt demonstrated that urbanization and vegetation data layers significantly contribute in predicting habitat suitability of Cx. nigripalpus and Cx. quinquefasciatus occurrence, respectively, which justifies the contribution of the former in urban and the latter in epizootic transmission cycles of WNV. In addition, habitat suitability risk maps were produced for both vectors in response to their predicting variables.

Conclusions

For the first time in the study area, a quantitative relationship between 27 predicting variables and two WNV mosquito vectors within their foraging habitats was highlighted at the local scale. Accordingly, the predicting variables were used to produce a practical distribution map of probable infective mosquito vectors. This substantially helps in determining where suitable habitats are found. This will potentially help in designing target surveillance and control programmes, saving money, time and man-power. However, the suitability risk maps should be updated when serological and entomological data updates are available.

Climate change impacts on West Nile virus transmission in a global context

West Nile virus (WNV), the most widely distributed virus of the encephalitic flaviviruses, is a vector-borne pathogen of global importance. The transmission cycle exists in rural and urban areas where the virus infects birds, humans, horses and other mammals. Multiple factors impact the transmission and distribution of WNV, related to the dynamics and interactions between pathogen, vector, vertebrate hosts and environment. Hence, among other drivers, weather conditions have direct and indirect influences on vector competence (the ability to acquire, maintain and transmit the virus), on the vector population dynamic and on the virus replication rate within the mosquito, which are mostly weather dependent. The importance of climatic factors (temperature, precipitation, relative humidity and winds) as drivers in WNV epidemiology is increasing under conditions of climate change. Indeed, recent changes in climatic conditions, particularly increased ambient temperature and fluctuations in rainfall amounts, contributed to the maintenance (endemization process) of WNV in various locations in southern Europe, western Asia, the eastern Mediterranean, the Canadian Prairies, parts of the USA and Australia. As predictions show that the current trends are expected to continue, for better preparedness, any assessment of future transmission of WNV should take into consideration the impacts of climate change.

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.

Environmental predictors of West Nile fever risk in Europe

Background

West Nile virus (WNV) is a mosquito-borne pathogen of global public health importance. Transmission of WNV is determined by abiotic and biotic factors. The objective of this study was to examine environmental variables as predictors of WNV risk in Europe and neighboring countries, considering the anomalies of remotely sensed water and vegetation indices and of temperature at the locations of West Nile fever (WNF) outbreaks reported in humans between 2002 and 2013.

Methods

The status of infection by WNV in relationship to environmental and climatic risk factors was analyzed at the district level using logistic regression models. Temperature, remotely sensed Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Water Index (MNDWI) anomalies, as well as population, birds’ migratory routes, and presence of wetlands were considered as explanatory variables.

Results

The anomalies of temperature in July, of MNDWI in early June, the presence of wetlands, the location under migratory routes, and the occurrence of a WNF outbreak the previous year were identified as risk factors. The best statistical model according to the Akaike Information Criterion was used to map WNF risk areas in 2012 and 2013. Model validations showed a good level of prediction: area under Receiver Operator Characteristic curve = 0.854 (95% Confidence Interval 0.850-0.856) for internal validation and 0.819 (95% Confidence Interval 0.814-0.823) (2012) and 0.853 (95% Confidence Interval 0.850-0.855) (2013) for external validations, respectively.

Conclusions

WNF incidence is increasing in Europe and WNV is expanding into new areas where it had never been observed before. Our model can be used to direct surveillance activities and public health interventions for the upcoming WNF season.

Material proximities and hotspots: toward an anthropology of viral hemorrhagic fevers

This article outlines a research program for an anthropology of viral hemorrhagic fevers (collectively known as VHFs). It begins by reviewing the social science literature on Ebola, Marburg, and Lassa fevers and charting areas for future ethnographic attention. We theoretically elaborate the hotspot as a way of integrating analysis of the two routes of VHF infection: from animal reservoirs to humans and between humans. Drawing together recent anthropological investigations of human-animal entanglements with an ethnographic interest in the social production of space, we seek to enrich conceptualizations of viral movement by elaborating the circumstances through which viruses, humans, objects, and animals come into contact. We suggest that attention to the material proximities-between animals, humans, and objects-that constitute the hotspot opens a frontier site for critical and methodological development in medical anthropology and for future collaborations in VHF management and control.

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.

Examination of the geographical variation in human West Nile virus: a spatial filtering approach

This paper examines the importance of environmental factors (mosquito pools and home foreclosures) in human West Nile virus (WNV) transmission in California and Colorado. The role of environmental factors is investigated by applying an instrumental variable technique to a spatial filtering random-effects negative binomial model to correct for both spatial autocorrelation and endogeneity. The results suggest that mosquito pools and home foreclosures are significant in explaining the prevalence of human WNV. An innovative aspect of this research is that it emphasizes the role of home foreclosures in WNV transmission and in the allocation of resources. Knowledge of the factors associated with WNV prevalence is crucial for abatement of future outbreaks. The results suggest that more resources should be allocated to areas that have a high number of home foreclosures and mosquito pools for surveillance and mitigation of the disease.

Nutrient enrichment affects immature mosquito abundance and species composition in field-based mesocosms in the coastal plain of Georgia

This study is the first to examine the relationship between nutrient enrichment and oviposition preference as measured by larval mosquito abundance using field-based mesocosms adjacent to wetlands in the Gulf Coastal Plain of Georgia. Agricultural wetlands in this region are known to have higher levels of nutrients and suspended sediments compared with forested wetlands, and previous studies have shown differences in mosquito communities in agricultural and forested wetlands. The purpose of this study was to determine whether nutrient enrichment contributes to the differences in mosquito oviposition preferences as reflected by larval mosquito presence and abundance in wetlands. We predicted that adding nutrients to mesocosms similar to concentrations in agricultural wetlands would favor responses of mosquito species often associated with nutrient-rich agricultural wetlands. Results indicated vegetation height, vegetation stem density, and phosphate levels were greater in fertilized mesocosms compared with nonfertilized mesocosms. The abundance of Aedes albopictus (Skuse) and Culex restuans Theobald was greater in mesocosms treated with fertilizer compared with nonfertilized mesocosms. Nutrient enrichment influenced oviposition and larval abundance of some mosquitoes of medical concern. This study provides evidence that can be used to predict the influence of nutrient enrichment on distribution and abundance of disease vectors and other nuisance mosquito species within an agricultural landscape.

The incidence of West Nile disease in Russia in relation to climatic and environmental factors

Since 1999, human cases of West Nile fever/neuroinvasive disease (WND) have been reported annually in Russia. The highest incidence has been recorded in three provinces of southern European Russia (Volgograd, Astrakhan and Rostov Provinces), yet in 2010-2012 the distribution of human cases expanded northwards considerably. From year to year, the number of WND cases varied widely, with major WND outbreaks in 1999, 2007, 2010, and 2012. The present study was aimed at identifying the most important climatic and environmental factors potentially affecting WND incidence in the three above-mentioned provinces and at building simple prognostic models, using those factors, by the decision trees method. The effects of 96 variables, including mean monthly temperature, relative humidity, precipitation, Normalized Difference Vegetation Index, etc. were taken into account. The findings of this analysis show that an increase of human WND incidence, compared to the previous year, was mostly driven by higher temperatures in May and/or in June, as well as (to a lesser extent) by high August-September temperatures. Declining incidence was associated with cold winters (December and/or January, depending on the region and type of model). WND incidence also tended to decrease during year following major WND outbreaks. Combining this information, the future trend of WND may be, to some extent, predicted, in accordance with the climatic conditions observed before the summer peak of WND incidence.

Use of spatial epidemiology and hot spot analysis to target women eligible for prenatal women, infants, and children services

OBJECTIVES

We used a geographic information system and cluster analyses to determine locations in need of enhanced Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) Program services.

METHODS

We linked documented births in the 2010 California Birth Statistical Master File with the 2010 data from the WIC Integrated Statewide Information System. Analyses focused on the density of pregnant women who were eligible for but not receiving WIC services in California's 7049 census tracts. We used incremental spatial autocorrelation and hot spot analyses to identify clusters of WIC-eligible nonparticipants.

RESULTS

We detected clusters of census tracts with higher-than-expected densities, compared with the state mean density of WIC-eligible nonparticipants, in 21 of 58 (36.2%) California counties (P < .05). In subsequent county-level analyses, we located neighborhood-level clusters of higher-than-expected densities of eligible nonparticipants in Sacramento, San Francisco, Fresno, and Los Angeles Counties (P < .05).

CONCLUSIONS

Hot spot analyses provided a rigorous and objective approach to determine the locations of statistically significant clusters of WIC-eligible nonparticipants. Results helped inform WIC program and funding decisions, including the opening of new WIC centers, and offered a novel approach for targeting public health services.

Exploring the spatio-temporal dynamics of reservoir hosts, vectors, and human hosts of West Nile virus: a review of the recent literature

Over the last two decades West Nile Virus (WNV) has been responsible for significant disease outbreaks in humans and animals in many parts of the World. Its extremely rapid global diffusion argues for a better understanding of its geographic extent. The purpose of this inquiry was to explore spatio-temporal patterns of WNV using geospatial technologies to study populations of the reservoir hosts, vectors, and human hosts, in addition to the spatio-temporal interactions among these populations. Review of the recent literature on spatial WNV disease risk modeling led to the conclusion that numerous environmental factors might be critical for its dissemination. New Geographic Information Systems (GIS)-based studies are monitoring occurrence at the macro-level, and helping pinpoint areas of occurrence at the micro-level, where geographically-targeted, species-specific control measures are sometimes taken and more sophisticated methods of surveillance have been used.

Ecological niche modelling of potential West Nile virus vector mosquito species and their geographical association with equine epizootics in Italy

In Italy, West Nile virus (WNV) equine outbreaks have occurred annually since 2008. Characterizing WNV vector habitat requirements allows for the identification of areas at risk of viral amplification and transmission. Maxent-based ecological niche models were developed using literature records of 13 potential WNV Italian vector mosquito species to predict their habitat suitability range and to investigate possible geographical associations with WNV equine outbreak occurrence in Italy from 2008 to 2010. The contribution of different environmental variables to the niche models was also assessed. Suitable habitats for Culex pipiens, Aedes albopictus, and Anopheles maculipennis were widely distributed; Culex modestus, Ochlerotatus geniculatus, Ochlerotatus caspius, Coquillettidia richiardii, Aedes vexans, and Anopheles plumbeus were concentrated in north-central Italy; Aedes cinereus, Culex theileri, Ochlerotatus dorsalis, and Culiseta longiareolata were restricted to coastal/southern areas. Elevation, temperature, and precipitation variables showed the highest predictive power. Host population and landscape variables provided minor contributions. WNV equine outbreaks had a significantly higher probability to occur in habitats suitable for Cx. modestus and Cx. pipiens, providing circumstantial evidence that the potential distribution of these two species coincides geographically with the observed distribution of the disease in equines.

Landscape determinants of Saint Louis encephalitis human infections in Córdoba city, Argentina during 2010

Saint Louis encephalitis virus (SLEV) is endemic in Argentina. During 2005 an outbreak occurred in Córdoba. From January to April of 2010 a new outbreak occurred in Córdoba city with a lower magnitude than the one reported in 2005. Understanding the association of different landscape elements related to SLEV hosts and vectors in urban environments is important for identifying high risk areas for human infections, which was here evaluated. The current study uses a case-control approach at a household geographical location, considering symptomatic and asymptomatic human infections produced by SLEV during 2010 in Córdoba city. Geographical information systems and logistic regression analysis were used to study the distribution of infected human cases and their proximity to water bodies, vegetation abundance, agricultural fields and housing density classified as high/low density urban constructions. Population density at a neighborhood level was also analyzed as a demographic variable. Logistic regression analysis revealed vegetation abundance was significantly (p<0.01) associated with the presence of human infections by SLEV. A map of probability of human infections in Córdoba city was derived from the logistic model. The model highlights areas that are more likely to experience SLEV infections. Landscape variables contributing to the outbreak were the proximity to places with vegetation abundance (parks, squares, riversides) and the presence of low density urban constructions, like residential areas. The population density analysis shows that SLEV infections are more likely to occur when population density by neighborhood is lower. These findings and the predictive map developed could be useful for public health surveillance and to improve prevention of vector-borne diseases.

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.

National and regional associations between human West Nile virus incidence and demographic, landscape, and land use conditions in the coterminous United States

The incidence of human West Nile virus (WNV) varies spatially and temporally and is influenced by a wide range of biotic and abiotic factors. There are numerous important vector species, with variable geographic ranges and ecologies, considered crucial to the transmission of WNV in the coterminous United States. To date there has been a lack of a systematic investigation in the United States, at a regional scale, of the wide variety of landscape, land use, and demographic influences on WNV incidence. In this study, we use published vector species distribution maps, as well as prominent landscape features, to define six distinct regions of the coterminous United States. We relate data on demographic, landscape, and land use conditions to the incidence of human WNV by region recorded at county level in the coterminous United States from 2002-2009. The observed relationships varied by region with the Great Plains, Northwest, and Southwest regions showing high WNV incidence associated with rural irrigated landscapes, indicating the importance of Culex tarsalis as the primary vector. In the Southeast, the percent of the population in poverty was positively associated with high WNV incidence, potentially indicating the quality of housing in relation to the vector Culex quinquefasciatus, a mosquito that often feeds indoors. The Northeast region human WNV incidence was positively associated with agricultural landscapes, potentially implying the importance of Culex restuans in a region generally thought of as being dominated by Culex pipiens transmission. There was strong spatial autocorrelation in most of the regions, but with a spatial autologistic term accounted for in binary logistic regression models, there were significant landscape, land use, and demographic covariates for each region.

Habitat associations of eastern equine encephalitis transmission in Walton County Florida

Eastern Equine Encephalitis virus (EEEV; family Togaviridae, genus Alphavirus) a highly pathogenic mosquito-borne virus is endemic to eastern North America. The ecology of EEEV in Florida differs from that in other parts of the United States; EEEV in the northeastern United States is historically associated with freshwater wetlands. No formal test of habitat associations of EEEV in Florida has been reported. Geographical Information Sciences (GIS) was used in conjunction with sentinel chicken EEEV seroconversion rate data as a means to examine landscape features associated with EEEV transmission in Walton County, FL. Sentinel sites were categorized as enzootic, periodically enzootic, and negative based on the number of chicken seroconversions to EEEV from 2005 to 2009. EEEV transmission was then categorized by land cover usage using Arc GIS 9.3. The land classification data were analyzed using the Kruskal-Wallis test for each land use class to determine which habitats may be associated with virus transmission as measured by sentinel chicken seroconversion rates. The habitat class found to be most significantly associated with EEEV transmission was tree plantations. The ecological factor most commonly associated with reduced levels of EEEV transmission was vegetated nonforest wetlands. Culiseta melanura (Coquillett), the species generally considered to be the major enzootic EEEV vector, was relatively evenly distributed across all habitat classes, while Aedes vexans (Meigen) and Anopheles crucians Weidemann were most commonly associated with tree plantation habitats.

Climatic controls on West Nile virus and Sindbis virus transmission and outbreaks in South Africa

The processes influencing the magnitude of West Nile virus (WNV) transmission from 1 year to the next require thorough investigation. The intensity of WNV transmission is related to the dynamics and interactions between the pathogen, vector, vertebrate hosts, and environment. Climatic variability is one process that can influence interannual disease transmission. South Africa has a long WNV and Sindbis virus (SINV) record where consistent climate and disease relationships can be identified. We relate climate conditions to historic mosquito infection rates. Next, we detect similar associations with reported human outbreaks dating back to 1941. Both concurrent summer precipitation and the change in summer precipitation from the previous to the current summer were strongly associated with WNV and SINV transmission and recorded human outbreaks. Each 100 mm interannual summer precipitation change increased WNV infection rates by 0.39 WNV-positive Culex univittatus/1000 tested Cx. univittatus. An improved understanding of biotic and abiotic disease transmission dynamics may help anticipate and mitigate future outbreaks.

The demographic and socioeconomic factors predictive for populations at high-risk for La Crosse virus infection in West Virginia

Although a large body of literature exists for the environmental risk factors for La Crosse virus (LACV) transmission, the demographic and socioeconomic risk factors for developing LACV infection have not been investigated. Therefore, this study investigated the demographic and socioeconomic risk factors for LACV infection in West Virginia from 2003 to 2007, using two forward stepwise discriminant analyses. The discriminant analyses were used to evaluate a number of demographic and socioeconomic factors for their ability to predict: 1) those census tracts with at least one reported case of LACV infection versus those census tracts with no reported cases of LACV infection and 2) to evaluate significantly high-risk clusters for LACV infection versus significantly low-risk clusters for LACV infection. In the first model, a high school education diploma or a general education diploma or less and a lower housing density

were found to be predictive of those census tracts with at least one case of LACV infection. A high school or a general education diploma or less, lower housing density, and housing built in 1969 and earlier were all found to be predictive of those census tracts displaying high-risk clusters versus census tracts displaying low-risk clusters in the second model. The cluster discriminant analysis was found to be more predictive than the census tract discriminant analysis as indicated by the Eigenvalues, canonical correlation, and grouping accuracy. The results of this study indicate that socioeconomically disadvantaged populations are at the highest risk for LACV infection and should be a focus of LACV infection prevention efforts.