Landscape, demographic and climatic associations with human West Nile virus occurrence regionally in 2012 in the United States of America

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

BACKGROUND

West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement.

METHODS

We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill.

RESULTS

Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill.

CONCLUSIONS

Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases).

The community-wide effectiveness of municipal larval control programs for West Nile virus risk reduction in Connecticut, USA

BACKGROUND

Mosquito larval control through the use of insecticides is the most common strategy for suppressing West Nile virus (WNV) vector populations in Connecticut (CT), USA. To evaluate the ability of larval control to reduce entomological risk metrics associated with WNV, we performed WNV surveillance and assessments of municipal larvicide application programs in Milford and Stratford, CT in 2019 and 2020. Each town treated catch basins and nonbasin habitats (Milford only) with biopesticide products during both WNV transmission seasons. Adult mosquitoes were collected weekly with gravid and CO₂ -baited light traps and tested for WNV; larvae and pupae were sampled weekly from basins within 500 m of trapping sites, and Culex pipiens larval mortality was determined with laboratory bioassays of catch basin water samples.

RESULTS

Declines in 4th instar larvae and pupae were observed in catch basins up to 2-week post-treatment, and we detected a positive relationship between adult female C. pipiens collections in gravid traps and pupal abundance in basins. We also detected a significant difference in total light trap collections between the two towns. Despite these findings, C. pipiens adult collections and WNV mosquito infection prevalence in gravid traps were similar between towns.

CONCLUSION

Larvicide applications reduced pupal abundance and the prevalence of host-seeking adults with no detectable impact on entomological risk metrics for WNV. Further research is needed to better determine the level of mosquito larval control required to reduce WNV transmission risk.

First Detection of the West Nile Virus Koutango Lineage in Sandflies in Niger

West Nile virus (WNV), belonging to the Flaviviridae family, causes a mosquito-borne disease and shows great genetic diversity, with at least eight different lineages. The Koutango lineage of WNV (WN-KOUTV), mostly associated with ticks and rodents in the wild, is exclusively present in Africa and shows evidence of infection in humans and high virulence in mice. In 2016, in a context of Rift Valley fever (RVF) outbreak in Niger, mosquitoes, biting midges and sandflies were collected for arbovirus isolation using cell culture, immunofluorescence and RT-PCR assays. Whole genome sequencing and in vivo replication studies using mice were later conducted on positive samples. The WN-KOUTV strain was detected in a sandfly pool. The sequence analyses and replication studies confirmed that this strain belonged to the WN-KOUTV lineage and caused 100% mortality of mice. Further studies should be done to assess what genetic traits of WN-KOUTV influence this very high virulence in mice. In addition, given the risk of WN-KOUTV to infect humans, the possibility of multiple vectors as well as birds as reservoirs of WNV, to spread the virus beyond Africa, and the increasing threats of flavivirus infections in the world, it is important to understand the potential of WN-KOUTV to emerge.

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.

The knowns and unknowns of West Nile virus in Europe: what did we learn from the 2018 outbreak?

Introduction: West Nile virus (WNV) is a mosquito-borne human and animal pathogen with nearly worldwide distribution. In Europe, the virus is endemic with seasonal regional outbreaks that have increased in frequency over the last 10 years. A massive outbreak occurred across southern and central Europe in 2018 with the number of confirmed human cases increasing up to 7.2-fold from the previous year, and expanding to include previously virus-free regions.Areas covered: This review focuses on potential causes that may explain the 2018 European WNV outbreak. We discuss the role genetic, ecological, and environmental aspects may have played in the increased activity during the 2018 transmission season, summarizing the latest epidemiological and virological publications.Expert opinion: Optimal environmental conditions, specifically increased temperature, were most likely responsible for the observed outbreak. Other factors cannot be ruled out due to limited available information, including factors that may influence host/vector abundance and contact. Europe will likely experience even larger-scale outbreaks in the coming years. Increased surveillance efforts should be implemented with a focus on early-warning detection methods, and large-scale host and vector surveys should continue to fill gaps in knowledge.

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.

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.

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.

Association of spring-summer hydrology and meteorology with human West Nile virus infection in West Texas, USA, 2002-2016

Background

The emergence of West Nile virus (WNV) in the Western Hemisphere has motivated research into the processes contributing to the incidence and persistence of the disease in the region. Meteorology and hydrology are fundamental determinants of vector-borne disease transmission dynamics of a region. The availability of water influences the population dynamics of vector and host, while temperature impacts vector growth rates, feeding habits, and disease transmission potential. Characterization of the temporal pattern of environmental factors influencing WNV risk is crucial to broaden our understanding of local transmission dynamics and to inform efforts of control and surveillance.

Methods

We used hydrologic, meteorological and WNV data from west Texas (2002–2016) to analyze the relationship between environmental conditions and annual human WNV infection. A Bayesian model averaging framework was used to evaluate the association of monthly environmental conditions with WNV infection.

Results

Findings indicate that wet conditions in the spring combined with dry and cool conditions in the summer are associated with increased annual WNV cases. Bayesian multi-model inference reveals monthly means of soil moisture, specific humidity and temperature to be the most important variables among predictors tested. Environmental conditions in March, June, July and August were the leading predictors in the best-fitting models.

Conclusions

The results significantly link soil moisture and temperature in the spring and summer to WNV transmission risk. Wet spring in association with dry and cool summer was the temporal pattern best-describing WNV, regardless of year. Our findings also highlight that soil moisture may be a stronger predictor of annual WNV transmission than rainfall.

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.

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.

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.

The Effect of Sharrows, Painted Bicycle Lanes and Physically Protected Paths on the Severity of Bicycle Injuries Caused by Motor Vehicles

We conducted individual and ecologic analyses of prospectively collected data from 839 injured bicyclists who collided with motorized vehicles and presented to Bellevue Hospital, an urban Level-1 trauma center in New York City, from December 2008 to August 2014. Variables included demographics, scene information, rider behaviors, bicycle route availability, and whether the collision occurred before the road segment was converted to a bicycle route. We used negative binomial modeling to assess the risk of injury occurrence following bicycle path or lane implementation. We dichotomized U.S. National Trauma Data Bank Injury Severity Scores (ISS) into none/mild (0-8) versus moderate, severe, or critical (>8) and used adjusted multivariable logistic regression to model the association of ISS with collision proximity to sharrows (i.e., bicycle lanes designated for sharing with cars), painted bicycle lanes, or physically protected paths. Negative binomial modeling of monthly counts, while adjusting for pedestrian activity, revealed that physically protected paths were associated with 23% fewer injuries. Painted bicycle lanes reduced injury risk by nearly 90% (IDR 0.09, 95% CI 0.02-0.33). Holding all else equal, compared to no bicycle route, a bicycle injury nearby sharrows was nearly twice as likely to be moderate, severe, or critical (adjusted odds ratio 1.94; 95% confidence interval (CI) 0.91-4.15). Painted bicycle lanes and physically protected paths were 1.52 (95% CI 0.85-2.71) and 1.66 (95% CI 0.85-3.22) times as likely to be associated with more than mild injury respectively.

Real-Time RT-PCR Assays for Detection and Genotyping of West Nile Virus Lineages Circulating in Africa

West Nile virus (WNV) is an emerging arbovirus, circulating worldwide between birds and mosquitoes, which impacts human and animal health. Since the mid-1990s, WNV outbreaks have emerged in Europe and America and represent currently the primary cause of encephalitis in the United States. WNV exhibits a great genetic diversity with at least eight different lineages circulating in the world, and four (1, 2, Koutango, and putative new) are present in Africa. These different WNV lineages are not readily differentiated by serology, and thus, rapid molecular tools are required for diagnostic. We developed here real-time RT-PCR assays for detection and genotyping of African WNV lineages. The specificity of the assays was tested using other flaviviruses circulating in Africa. The sensitivity was determined by testing serial 10-fold dilutions of viruses and RNA standards. The assays provided good specificity and sensitivity and the analytical detection limit was 10 copies/reaction. The RT-PCR assays allowed the detection and genotyping of all WNV isolates in culture medium, human serum, and vertebrate tissues, as well as in field and experimental mosquito samples. Comparing the ratios of genome copy number/infectious virion (plaque-forming units), our study finally revealed new insight on the replication of these different WNV lineages in mosquito cells. Our RT-PCR assays are the first ones allowing the genotyping of all WNV African variants, and this may have important applications in surveillance and epidemiology in Africa and also for monitoring of their emergence in Europe and other continents.

Development and validation of a climate-based ensemble prediction model for West Nile Virus infection rates in Culex mosquitoes, Suffolk County, New York

Background

West Nile Virus (WNV) is an endemic public health concern in the United States that produces periodic seasonal epidemics. Underlying these outbreaks is the enzootic cycle of WNV between mosquito vectors and bird hosts. Identifying the key environmental conditions that facilitate and accelerate this cycle can be used to inform effective vector control.

Results

Here, we model and forecast WNV infection rates among mosquito vectors in Suffolk County, New York using readily available meteorological and hydrological conditions. We first validate a statistical model built with surveillance data between 2001 and 2009 (m09) and specify a set of new statistical models using surveillance data from 2001 to 2012 (m12). This ensemble of new models is then used to make predictions for 2013–2015, and multimodel inference is employed to provide a formal probabilistic interpretation across the disparate individual model predictions. The findings of the m09 and m12 models align; with the ensemble of m12 models indicating an association between warm, dry early spring (April) conditions and increased annual WNV infection rates in Culex mosquitoes.

Conclusions

This study shows that real-time climate information can be used to predict WNV infection rates in Culex mosquitoes prior to its seasonal peak and before WNV spillover transmission risk to humans is greatest.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-016-1720-1) contains supplementary material, which is available to authorized users.

Genetic Variability of West Nile Virus in U.S. Blood Donors from the 2012 Epidemic Season

West Nile virus (WNV) is an arbovirus maintained in nature in a bird-mosquito enzootic cycle which can also infect other vertebrates including humans. WNV is now endemic in the United States (U.S.), causing yearly outbreaks that have resulted in an estimated total of 4-5 million human infections. Over 41,700 cases of West Nile disease, including 18,810 neuroinvasive cases and 1,765 deaths, were reported to the CDC between 1999 and 2014. In 2012, the second largest West Nile outbreak in the U.S. was reported, which caused 5,674 cases and 286 deaths. WNV continues to evolve, and three major WNV lineage I genotypes (NY99, WN02, and SW/WN03) have been described in the U.S. since introduction of the virus in 1999. We report here the WNV sequences obtained from 19 human samples acquired during the 2012 U.S. outbreak and our examination of the evolutionary dynamics in WNV isolates sequenced from 1999-2012. Maximum-likelihood and Bayesian methods were used to perform the phylogenetic analyses. Selection pressure analyses were performed with the HyPhy package using the Datamonkey web-server. Using different codon-based and branch-site selection models, we detected a number of codons subjected to positive pressure in WNV genes. Thirteen of the 19 completely sequenced isolates from 10 U.S. states were genetically similar, sharing up to 55 nucleotide mutations and 4 amino acid substitutions when compared with the prototype isolate WN-NY99. Overall, these analyses showed that following a brief contraction in 2008-2009, WNV genetic divergence in the U.S. continued to increase in 2012, and that closely related variants were found across a broad geographic range of the U.S., coincident with the second-largest WNV outbreak in U.S.

Epidemiological analysis of bovine ephemeral fever in 2012-2013 in the subtropical islands of Japan

Background

Bovine ephemeral fever (BEF) is a febrile disease of cattle that is transmitted by arthropod vectors such as mosquitoes and Culicoides biting midges. An outbreak of BEF recently occurred in Ishigaki Island and surrounding islands that are located southwest of Japan. In this study, an epidemiological analysis was conducted to understand the temporal and spatial characteristics of the outbreak. Factors associated with the disease spread within Ishigaki Island were investigated by hierarchical Bayesian models. The possibility of between-island transmission by windborne vectors and transmission by long-distance migration of infected vectors were examined using atmospheric dispersion models.

Results

In September 2012, the first case of the disease was detected in the western part of Ishigaki Island. In 1 month, it had rapidly spread to the southern part of the island and to surrounding islands, and led to 225 suspected cases of BEF during the outbreak. The dispersion model demonstrated the high possibility of between-island transmission by wind. Spatial analysis showed that paddy fields, farmlands, and slope gradients had a significant impact on the 1-km cell-level incidence risk. These factors may have influenced the habitats and movements of the vectors with regard to the spread of BEF. A plausible incursion event of infected vectors from Southeast Asia to Ishigaki Island was estimated to have occurred at the end of August.

Conclusion

This study revealed that the condition of a terrain and land use significantly influenced disease transmission. These factors are important in assessing favorable environments for related vectors. The results of the dispersion model indicated the likely transmission of the infected vectors by wind on the local scale and on the long-distance scale. These findings would be helpful for developing a surveillance program and developing preventive measures against BEF.