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

A stochastic multi-host model for West Nile virus transmission

When initially introduced into a susceptible population, a disease may die out or result in a major outbreak. We present a Continuous-Time Markov Chain model for enzootic WNV transmission between two avian host species and a single vector, and use multitype branching process theory to determine the probability of disease extinction based upon the type of infected individual initially introducing the disease into the population - an exposed vector, infectious vector, or infectious host of either species. We explore how the likelihood of disease extinction depends on the ability of each host species to transmit WNV, vector biting rates on host species, and the relative abundance of host species, as well as vector abundance. Theoretical predictions are compared to the outcome of stochastic simulations. We find the community composition of hosts and vectors, as well as the means of disease introduction, can greatly affect the probability of disease extinction.

Spatio-Temporal distribution of a vector of cutaneous leishmaniasis: Pintomyia longiflocosa, in a population from the Colombian Andean Mountains

BACKGROUND

Leishmaniasis, a neglected disease and public health concern, is associated with various factors such as biological, social, economical conditions and climate, increasing the risk of human infection. Understanding the population dynamics of the vectors, like Pintomyia longiflocosa, and its relationship with ecological variables is crucial for developing effective strategies to control sand fly populations and combat cutaneous leishmaniasis in a tropical country like Colombia.

METHODOLOGY

Adult sand flies were collected in three different sample locations: outdoor, indoor, and peri-domestic areas in three houses located in the rural settlement of Campoalegre (Huila) between February 2020 and February 2021, using the CDC light traps. The sand fly density was quantified and associated with the sample locations and the sampling months using Analysis of Variance and Pearson correlations.

PRINCIPAL FINDINGS

In the period of the sample, 98.86% of sand fly collected was identified as Pi. longiflocosa. The density of this species was significantly different between males and females, the latter contributing more to density in all sample locations (P<0.0001). The outdoor was the sample location with the highest and most significative density in this study (70%, P = 0.04). The density of these sand flies is related to the seasonality of Campoalegre, revealing a density peak from February and June to October (P < 0.05). Finally, precipitation is the environmental variable prominently linked to the density pattern, showing a negative correlation with it. Months with the highest precipitations show the lowest values of Pi. longiflocosa abundance.

CONCLUSIONS/SIGNICANCE

Our investigation reveals a inverse correlation between precipitation levels and the abundance of Pi. longiflocosa in Campoalegre (Huila), particularly in outdoor areas. This suggests that vector control strategies to periods of reduced precipitation in outdoor settings could offer an effective approach to minimizing cases of cutaneous leishmaniasis in the region.

Daytime Resting Activity of Aedes Aegypti and Culex Quinquefasciatus Populations in Northern Mexico

Aedes aegypti and Culex quinquefasciatus are disease vectors distributed throughout much of the world and are responsible for a high burden of vector-borne disease, which has increased during the last 2 decades. Most pathogens vectored by these mosquitoes do not have therapeutic remedies; thus, combating these diseases is dependent upon vector control. Improvements in vector control strategies are urgently needed, but these hinge on understanding the biology and ecology of Ae. aegypti and Cx. quinquefasciatus. Both species have been extensively investigated, but further knowledge on diel resting activity of these vectors can improve vector surveillance and control tools for targeting resting vector populations. From April to December 2021, we determined outdoor daytime resting habits of Ae. aegypti and Cx. quinquefasciatus male, female, and blood-fed female populations in Reynosa, Mexico, using large red odor-baited wooden box traps. The daytime resting activity for Ae. aegypti males, females, and blood-fed females was restricted to a period between 0900 h and 1300 h, with a peak at 0900 h, while the resting activity of Cx. quinquefasciatus male, female, and blood-fed females was between 0700 h and 1100 h, with a peak at 0700 h. A generalized additive model was developed to relate relative humidity and temperature to resting Cx. quinquefasciatus and Ae. aegypti male, female, and blood-fed populations caught in traps. This study advances the understanding of outdoor resting behavior for 2 important vector mosquito species and discusses future studies to fill additional knowledge gaps.

Trends in mosquito species distribution modeling: insights for vector surveillance and disease control

Species distribution modeling (SDM) has become an increasingly common approach to explore questions about ecology, geography, outbreak risk, and global change as they relate to infectious disease vectors. Here, we conducted a systematic review of the scientific literature, screening 563 abstracts and identifying 204 studies that used SDMs to produce distribution estimates for mosquito species. While the number of studies employing SDM methods has increased markedly over the past decade, the overwhelming majority used a single method (maximum entropy modeling; MaxEnt) and focused on human infectious disease vectors or their close relatives. The majority of regional models were developed for areas in Africa and Asia, while more localized modeling efforts were most common for North America and Europe. Findings from this study highlight gaps in taxonomic, geographic, and methodological foci of current SDM literature for mosquitoes that can guide future efforts to study the geography of mosquito-borne disease risk.

Predicting Suitable Areas for African Swine Fever Outbreaks in Wild Boars in South Korea and Their Implications for Managing High-Risk Pig Farms

African swine fever (ASF) is a highly contagious disease affecting domestic pigs and wild boars, with no effective vaccine or treatment available. In South Korea, extensive measures have been implemented to prevent ASF transmission between wild boars and ASF spillover from wild boars to pig farm sectors, including the search for ASF-infected carcasses in mountainous forests and the installation of fences across wide areas of these forests. To determine the priority search range for infected carcasses and establish pig farm-centered quarantine measures, it is necessary to predict the specific path of ASF outbreaks in wild boars and identify pig farms at high risk of ASF spillover from wild boars. Here, we aimed to predict suitable areas and geographical paths for ASF outbreaks in wild boars using the MaxEnt model and shortest-path betweenness centrality analysis. The analysis identified a high frequency of ASF outbreaks in areas with a suitability value ≥0.4 on the suitability map and in areas within a 1.8 km range from the path on the shortest-path map, indicating these areas were high-risk zones for ASF outbreaks. Among the 5063 pig farms analyzed, 37 were in the high-risk zone on the suitability map, 499 were in the high-risk zone on the shortest-path map, and 9 were in both risk zones. Of the 51 pig farm sectors with a dense distribution of pig farms (kernel density ≥ 8), 25 sectors were in contact with or partially overlapped the high risk zone on the suitability map, 18 sectors were located within the high risk zone on the shortest-path map, and 14 sectors were located within both risk zones. These findings aided in determining the priority range for searches for wild boar carcasses and enabled the establishment of preemptive ASF prevention measures around the pig farming sectors that are at risk of ASF spillover from wild boars.

Knowledge, attitudes, and practices towards mosquito control and used vehicle tire dumping by median household income, in metropolitan New Orleans, Louisiana

Background

Discarded vehicle tires are an important artificial habitat for the larvae of many container-breeding mosquito species worldwide, including in the United States. Unmanaged discarded vehicle tires create health, environmental and social costs, and with budget and staffing constraints, effective management of discarded used vehicle tires a mosquito larval habitat depends in part on the knowledge, attitude, and practices (KAP) of community residents.

Objectives

This study aims to examine the knowledge, attitude and practices of New Orleans, Louisiana residents toward illegally discarded vehicle tires, and larval mosquito control.

Methods

A descriptive cross-sectional design study was used where 422 households were selected using a two-stage cluster random sampling procedure in New Orleans, Louisiana. Heads of households or a person aged 18 years or older self-administered the survey. The questionnaire comprised five parts: screening, tire sightings, preferred communication method, knowledge, attitude and precautionary measures against mosquito control, disease risk and illegal discarding. We then statistically compared above and below median income household responses to identify likely causes of detected differences. The data were analyzed using ordinal regression models via IBM SPSS statistics V.26.0. Statistical significance was set at p < 0.05.

Results

Out of 290 responding households, 95.5% strongly agree or agree that mosquitoes can spread serious diseases like West Nile, Zika or Dengue. Only 2.3% of the sample had high knowledge of illegally discarded tires dumping and mosquito larval control. Those employed were 1.0 times more likely to possess good knowledge than the unemployed (p < 0.001). Despite low knowledge levels regarding mosquito breeding and polluted water in discarded tires, 29.9% of respondents had positive attitude and 20.5% reported sufficient practices. Among the socio-demographic variables, only home ownership and being employed were predictors of knowledge and attitude towards mosquito breeding in illegally discarded tires (p < 0.05).

Conclusions

Despite the observed increasing number of illegally discarded vehicle tires in New Orleans, the knowledge of people about illegal tire dumping and their associated risk factors as suitable larval habitants was low. Therefore, there is a need for developing community-based and place-based tailored sensitization campaigns to prevent illegal used tire dumping, and larval control.

Worldwide impacts of landscape anthropization on mosquito abundance and diversity: A meta-analysis

In recent decades, the emergence and resurgence of vector-borne diseases have been well documented worldwide, especially in tropical regions where protection and defense tools for human populations are still very limited. In this context, the dynamics of pathogens are influenced by landscape anthropization (i.e., urbanization, deforestation, and agricultural development), and one of the mechanisms through which this occurs is a change in the abundance and/or diversity of the vectors. An increasing number of empirical studies have described heterogeneous effects of landscape anthropization on vector communities; therefore, it is difficult to have an overall picture of these effects on a global scale. Here, we performed a meta-analysis to quantify the impacts of landscape anthropization on a global scale on the presence/abundance and diversity of mosquitoes, the most important arthropods affecting human health. We obtained 338 effect sizes on 132 mosquito species, compiled from 107 studies in 52 countries that covered almost every part of the world. The results of the meta-analysis showed an overall decline of mosquito presence/abundance and diversity in response to urbanization, deforestation, and agricultural development, except for a few mosquito species that have been able to exploit landscape anthropization well. Our results highlighted that these few favored mosquito species are those of global concern. They, thus, provide a better understanding of the overall effect of landscape anthropization on vector communities and, more importantly, suggest a greater risk of emergence and transmission of vector-borne diseases in human-modified landscapes.

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.

Modified Mosquito Programs’ Surveillance Needs and An Image-Based Identification Tool to Address Them

Effective mosquito surveillance and control relies on rapid and accurate identification of mosquito vectors and confounding sympatric species. As adoption of modified mosquito (MM) control techniques has increased, the value of monitoring the success of interventions has gained recognition and has pushed the field away from traditional ‘spray and pray’ approaches. Field evaluation and monitoring of MM control techniques that target specific species require massive volumes of surveillance data involving species-level identifications. However, traditional surveillance methods remain time and labor-intensive, requiring highly trained, experienced personnel. Health districts often lack the resources needed to collect essential data, and conventional entomological species identification involves a significant learning curve to produce consistent high accuracy data. These needs led us to develop MosID: a device that allows for high-accuracy mosquito species identification to enhance capability and capacity of mosquito surveillance programs. The device features high-resolution optics and enables batch image capture and species identification of mosquito specimens using computer vision. While development is ongoing, we share an update on key metrics of the MosID system. The identification algorithm, tested internally across 16 species, achieved 98.4 ± 0.6% % macro F1-score on a dataset of known species, unknown species used in training, and species reserved for testing (species, specimens respectively: 12, 1302; 12, 603; 7, 222). Preliminary user testing showed specimens were processed with MosID at a rate ranging from 181-600 specimens per hour. We also discuss other metrics within technical scope, such as mosquito sex and fluorescence detection, that may further support MM programs.

Habitat Segregation Patterns of Container Breeding Mosquitos: The Role of Urban Heat Islands, Vegetation Cover, and Income Disparity in Cemeteries of New Orleans

Aedes aegypti and Aedes albopictus are important pathogen-carrying vectors that broadly exhibit similar habitat suitability, but that differ at fine spatial scales in terms of competitive advantage and tolerance to urban driven environmental parameters. This study evaluated how spatial and temporal patterns drive the assemblages of these competing species in cemeteries of New Orleans, LA, applying indicators of climatic variability, vegetation, and heat that may drive habitat selection at multiple scales. We found that Ae. aegypti was well predicted by urban heat islands (UHI) at the cemetery scale and by canopy cover directly above the cemetery vase. As predicted, UHI positively correlate to Ae. aegypti, but contrary to predictions, Ae. aegypti, was more often found under the canopy of trees in high heat cemeteries. Ae. albopictus was most often found in low heat cemeteries, but this relationship was not statistically significant, and their overall abundances in the city were lower than Ae. aegypti. Culex quinquefasciatus, another important disease vector, was also an abundant mosquito species during the sampling year, but we found that it was temporally segregated from Aedes species, showing a negative association to the climatic variables of maximum and minimum temperature, and these factors positively correlated to its more direct competitor Ae. albopictus. These findings help us understand the mechanism by which these three important vectors segregate both spatially and temporally across the city. Our study found that UHI at the cemetery scale was highly predictive of Ae. aegypti and strongly correlated to income level, with low-income cemeteries having higher UHI levels. Therefore, the effect of excessive heat, and the proliferation of the highly competent mosquito vector, Ae. aegypti, may represent an unequal disease burden for low-income neighborhoods of New Orleans that should be explored further. Our study highlights the importance of considering socioeconomic aspects as indirectly shaping spatial segregation dynamics of urban mosquito species.

West Nile virus in Spain: Forecasting the geographical distribution of risky areas with an ecological niche modelling approach

West Nile virus (WNV), a well-known emerging vector-borne arbovirus with a zoonotic life cycle, represents a threat to both public and animal health. Transmitted by ornithophilic mosquitoes, its transmission is difficult to predict and even more difficult to prevent. The massive and unprecedented number of human cases and equid outbreaks in Spain during 2020 interpellates for new approaches. For the first time, we present an integrate analysis from a niche perspective to provide an insight to the situation of West Nile disease (WND) in Spain. Our modelling approach benefits from the combined use of global occurrence records of outbreaks of WND in equids and of its two alleged main vectors in Spain, Culex pipiens and Cx. perexiguus. Maps of the climatic suitability for the presence of the two vectors species and for the circulation of WNV are provided. The main outcome of our study is a map delineating the areas under certain climatic risk of transmission. Our analyses indicate that the climatic risk of transmission of WND is medium in areas nearby the south Atlantic coastal area of the Cadiz Gulf and the Mediterranean coast, and high in southwestern Spain. The higher risk of transmission in the basins of the rivers Guadiana and Guadalquivir cannot be attributed exclusively to the local abundance of Cx. pipiens, but could be ascribed to the presence and abundance of Cx. perexiguus. Furthermore, this integrated analysis suggests that the WNV presents an ecological niche of its own, not fully overlapping the ones of its hosts or vector, and thus requiring particular environmental conditions to succeed in its infection cycle.

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.

Estimations of Fine-Scale Species Distributions of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in Eastern Florida

Many species distribution maps indicate the ranges of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) overlap in Florida despite the well-documented range reduction of Ae. aegypti. Within the last 30 yr, competitive displacement of Ae. aegypti by Ae. albopictus has resulted in partial spatial segregation of the two species, with Ae. aegypti persisting primarily in urban refugia. We modeled fine-scale distributions of both species, with the goal of capturing the outcome of interspecific competition across space by building habitat suitability maps. We empirically parameterized models by sampling 59 sites in south and central Florida over time and incorporated climatic, landscape, and human population data to identify predictors of habitat suitability for both species. Our results show human density, precipitation, and urban land cover drive Ae. aegypti habitat suitability, compared with exclusively climatic variables driving Ae. albopictus habitat suitability. Remotely sensed variables (macrohabitat) were more predictive than locally collected metrics (microhabitat), although recorded minimum daily temperature showed significant, inverse relationships with both species. We detected minor Aedes habitat segregation; some periurban areas that were highly suitable for Ae. albopictus were unsuitable for Ae. aegypti. Fine-scale empirical models like those presented here have the potential for precise risk assessment and the improvement of operational applications to control container-breeding Aedes mosquitoes.

Mosquito Vector Production across Socio-Economic Divides in Baton Rouge, Louisiana

We investigated the role of socio-economic factors in the proliferation of mosquito vectors in two adjacent but socio-economically contrasting neighborhoods in Baton Rouge, LA, USA. We surveyed mosquito larvae habitat, mosquito larvae, and adult mosquitoes during the summer of 2020. We also evaluated the number of requests for mosquito abatement services in the years preceding the study for each area. While we did not find differences in terms of the most abundant species, Culex quinquefasicatus (F_1,30 = 0.329, p = 0.57), we did find a higher abundance of mosquito habitats, particularly discarded tires, as well as larvae (z = 13.83, p < 0.001) and adults (F_1,30 = 4.207, p = 0.049) of the species Aedes albopictus in the low-income neighborhood. In contrast, mosquito abatement requests were significantly higher in the high socio-economic neighborhood (z = −8.561, p < 0.001). This study shows how factors such as adjudicated properties, discarded tires and pest abatement requests can influence the abundance of mosquito vectors, disproportionately affecting low-income groups. This study also highlights how Aedes spp. may be better indicators than Culex spp. of socio-economic differences between nearby neighborhoods, due to their short flight range and habitat preferences, and this should be considered in future studies attempting to detect such disparities in the future.

Factors associated with spatial distribution of severe fever with thrombocytopenia syndrome

Severe fever with thrombocytopenia syndrome (SFTS) was firstly identified in mainland China in 2009 and the geographic distribution has expanded in recent years. In this study, we constructed ecological niche models (ENM) of SFTS with meteorological factors, environmental factor, and density of domestic animals using MaxEnt. We found four significant associated factors including altitude, yearly average temperature, yearly accumulated precipitation, and yearly average relative humidity which accounted for 94.1% percent contribution. SFTS occurrence probability was high when altitude was between -100 m and 100 m, and the probability was nearly 0 when altitude was beyond 3000 m. Response curves of SFTS to the yearly average temperature, yearly accumulated precipitation, and yearly average relative humidity were all reversed V-shape. SFTS occurrence probability was high where the yearly average temperature, yearly accumulated precipitation, and yearly relative humidity were 12.5-17.5 °C, 700-2250 mm and 63-82%, respectively. ENMs predicted that the potential high-risk areas were mainly distributed in eastern areas and central areas of China. But there were some predicted potential high-risk areas where no SFTS case was reported up to date. More researches should be done to make clear whether SFTS case had occurred in these areas.

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.

The Role of Temperature in Transmission of Zoonotic Arboviruses

We reviewed the literature on the role of temperature in transmission of zoonotic arboviruses. Vector competence is affected by both direct and indirect effects of temperature, and generally increases with increasing temperature, but results may vary by vector species, population, and viral strain. Temperature additionally has a significant influence on life history traits of vectors at both immature and adult life stages, and for important behaviors such as blood-feeding and mating. Similar to vector competence, temperature effects on life history traits can vary by species and population. Vector, host, and viral distributions are all affected by temperature, and are generally expected to change with increased temperatures predicted under climate change. Arboviruses are generally expected to shift poleward and to higher elevations under climate change, yet significant variability on fine geographic scales is likely. Temperature effects are generally unimodal, with increases in abundance up to an optimum, and then decreases at high temperatures. Improved vector distribution information could facilitate future distribution modeling. A wide variety of approaches have been used to model viral distributions, although most research has focused on the West Nile virus. Direct temperature effects are frequently observed, as are indirect effects, such as through droughts, where temperature interacts with rainfall. Thermal biology approaches hold much promise for syntheses across viruses, vectors, and hosts, yet future studies must consider the specificity of interactions and the dynamic nature of evolving biological systems.

Spatial distribution and spread potential of sixteen Leptospira serovars in a subtropical region of Brazil

Leptospirosis is a bacterial disease that represents a major problem in animal and public health due to its high prevalence and widespread distribution. This zoonotic disease is most prevalent in tropical environments where conditions favour pathogen survival. The ecological preferences of Leptospira serovars are poorly understood, limiting our knowledge of where and when outbreaks can occur, which may result in misinformed prevention and control plans. While the disease can occur consistently in time and space in tropical regions, research on the ecology of leptospirosis remains limited in subtropical regions. This research gap regarding Leptospira ecology brings public and veterinary health problems, impacting local economies. To fill this gap of knowledge, we suggest to assess geographic and ecological features among Leptospira serovars in a subtropical area of Brazil where leptospirosis is endemic to (a) highlight environmental conditions that facilitate or limit Leptospira spread and survival and (b) reconstruct its geographic distribution. An ecological niche modelling framework was used to characterize and compare Leptospira serovars in both geographic and environmental space. Our results show that despite the geographic overlap exhibited by the different serovars assessed, we found ecological divergence among their occupied ecological niches. Ecological divergences were expressed as ranges of potential distributions and environmental conditions found suitably by serovar, Sejroe being the most asymmetric (<0.15). Most important predictors for the potential distribution of most serovars were soil pH (31.7%) and landscape temperature (24.2%). Identification of environmental preferences will allow epidemiologists to better infer the presence of a serovar based on the environmental characteristics of regions rather than inferences based solely on historical epidemiological records. Including geographic and ecological ranges of serovars also may help to forecast transmission potential of Leptospira in public health and the food animal practice.

Spatiotemporal Bayesian modeling of West Nile virus: Identifying risk of infection in mosquitoes with local-scale predictors

Monitoring and control of West Nile virus (WNV) presents a challenge to state and local vector control managers. Models of mosquito presence and viral incidence have revealed that variations in mosquito autecology and land use patterns introduce unique dynamics of disease at the scale of a county or city, and that effective prediction requires locally parameterized models. We applied Bayesian spatiotemporal modeling to West Nile surveillance data from 49 mosquito trap sites in Nassau County, New York, from 2001 to 2015 and evaluated environmental and sociological predictors of West Nile virus incidence in Culex pipiens-restuans. A Bayesian spike-and-slab variable selection algorithm was used to help select influential independent variables. This method can be used to identify locally-important predictors. The best model predicted West Nile positives well, with an Area Under Curve (AUC) of 0.83 on holdout data. The temporal trend was nonlinear and increased throughout the year. The spatial component identified increased West Nile incidence odds in the northwestern portion of the county, with lower odds in wetlands on the south shore of Long Island. High Normalized Difference Vegetation Index (NDVI) areas, wetlands, and areas of high urban development had negative associations with WNV incidence. In this study we demonstrate a method for improving spatiotemporal models of West Nile virus incidence for decision making at the county and community scale, which empowers disease and vector control organizations to prioritize and evaluate prevention efforts.

Usutu virus induced mass mortalities of songbirds in Central Europe: Are habitat models suitable to predict dead birds in unsampled regions?

The Usutu virus (USUV) is a mosquito-borne flavivirus closely related to the better known West Nile virus, and it can cause mass mortalities of song birds. In the present paper, a dataset of georeferenced locations of USUV-positive birds was compiled and then used to map the geographical distribution of suitable USUV habitats in Central Europe. Six habitat models, comprising BIOCLIM, DOMAIN, maximum entropy model (MAXENT), generalized linear model (GLM), boosted regression trees model (BRT), and random forests model (RF), were selected and tested for their performance ability to predict cases of disease in unsampled areas. Suitability index maps, a diagram depicting model performance by the Area Under the Curve (AUC) vs. the True Skill Statistic (TSS), and a diagram ranking sensitivity vs. specificity as well as correct classification ratio (CCR) vs. misclassification ratio (MCR) were presented. Of the models tested GLM, BRT, RF, and MAXENT were shown suitable to predict USUV-positive dead birds in unsampled regions, with BRT the highest predictive accuracy (AUC = 0.75, TSS = 0.50). However, the four models classified major parts of the model domain as USUV-suitable, although USUV was never confirmed there so far (MCR=0.49 to 0.61). DOMAIN and especially BIOCLIM can only be recommended for interpolating point observations to raster files, i.e. for analyzing observed USUV distributions (MCR = 0.10). Habitat models can be a helpful tool for informing veterinary authorities about the possible distribution of a given mosquito-borne disease. Nevertheless, it should be taken in consideration, that the spatial and temporal scales, the selection of an appropriate model, the availability of significant predictive variables as well as the representativeness and completeness of collected species or disease cases may strongly influence the modeling results.

Systematic Review: Land Cover, Meteorological, and Socioeconomic Determinants of Aedes Mosquito Habitat for Risk Mapping

Asian tiger and yellow fever mosquitoes (Aedes albopictus and Ae. aegypti) are global nuisances and are competent vectors for viruses such as Chikungunya (CHIKV), Dengue (DV), and Zika (ZIKV). This review aims to analyze available spatiotemporal distribution models of Aedes mosquitoes and their influential factors. A combination of five sets of 3-5 keywords were used to retrieve all relevant published models. Five electronic search databases were used: PubMed, MEDLINE, EMBASE, Scopus, and Google Scholar through 17 May 2017. We generated a hierarchical decision tree for article selection. We identified 21 relevant published studies that highlight different combinations of methodologies, models and influential factors. Only a few studies adopted a comprehensive approach highlighting the interaction between environmental, socioeconomic, meteorological and topographic systems. The selected articles showed inconsistent findings in terms of number and type of influential factors affecting the distribution of Aedes vectors, which is most likely attributed to: (i) limited availability of high-resolution data for physical variables, (ii) variation in sampling methods; Aedes feeding and oviposition behavior; (iii) data collinearity and statistical distribution of observed data. This review highlights the need and sets the stage for a rigorous multi-system modeling approach to improve our knowledge about Aedes presence/abundance within their flight range in response to the interaction between environmental, socioeconomic, and meteorological systems.