Transmission of West Nile and five other temperate mosquito-borne viruses peaks at temperatures between 23°C and 26°C

Warm winters are associated to more intense West Nile virus circulation in southern Spain

West Nile virus (WNV) is the most widely distributed mosquito-borne flavivirus in the world. This flavivirus can infect humans causing in some cases a fatal neurological disease and birds are the main reservoir hosts. WNV is endemic in Spain, and human cases have been reported since 2004. Although different studies analyse how climatic conditions can affect the dynamics of WNV infection, very few use long-term datasets. Between 2003 and 2020 a total of 2,724 serum samples from 1,707 common coots (Fulica atra) were analysed for the presence of WNV-specific antibodies. Mean (SD) annual seroprevalence was 24.67% (0.28) but showed high year-to-year variations ranging from 5.06% (0.17) to 68.89% (0.29). Significant positive correlations (p < 0.01) were observed between seroprevalence and maximum winter temperature and mean spring temperature. The unprecedented WNV outbreak in humans in the south of Spain in 2020 was preceded by a prolonged period of escalating WNV local circulation. Given current global and local climatic trends, WNV circulation is expected to increase in the next decades. This underscores the necessity of implementing One Health approaches to reduce the risk of future WNV outbreaks in humans. Our results suggest that higher winter and spring temperatures may be used as an early warning signal of more intense WNV circulation among wildlife in Spain, and consequently highlight the need of more intense vector control and surveillance in human inhabited areas.

Present and future suitability of invasive and urban vectors through an environmentally driven mosquito reproduction number

Temperature and water availability significantly influence mosquito population dynamics. We have developed a method, integrating experimental data with insights from mosquito and thermal biology, to calculate the basic reproduction number ([Formula: see text]) for urban mosquito species Aedes albopictus and Aedes aegypti. [Formula: see text] represents the number of female mosquitoes produced by one female during her lifespan, indicating suitability for growth. Environmental conditions, including temperature, rainfall and human density, influence [Formula: see text] by altering key mosquito life cycle traits. Validation using data from Spain and Europe confirms the approach's reliability. Our analysis suggests that temperature increases may not uniformly benefit Ae. albopictus proliferation but could boost Ae. aegypti expansion. We suggest using vector [Formula: see text] maps, leveraging climate and environmental data, to predict areas susceptible to invasive mosquito population growth. These maps aid resource allocation for intervention strategies, supporting effective vector surveillance and management efforts.

Remote sensing of temperature-dependent mosquito and viral traits predicts field surveillance-based disease risk

Mosquito-borne diseases contribute substantially to the global burden of disease, and are strongly influenced by environmental conditions. Ongoing and rapid environmental change necessitates improved understanding of the response of mosquito-borne diseases to environmental factors like temperature, and novel approaches to mapping and monitoring risk. Recent development of trait-based mechanistic models has improved understanding of the temperature dependence of transmission, but model predictions remain challenging to validate in the field. Using West Nile virus (WNV) as a case study, we illustrate the use of a novel remote sensing-based approach to mapping temperature-dependent mosquito and viral traits at high spatial resolution and across the diurnal cycle. We validate the approach using mosquito and WNV surveillance data controlling for other key factors in the ecology of WNV, finding strong agreement between temperature-dependent traits and field-based metrics of risk. Moreover, we find that WNV infection rate in mosquitos exhibits a unimodal relationship with temperature, peaking at ~24.6-25.2°C, in the middle of the 95% credible interval of optimal temperature for transmission of WNV predicted by trait-based mechanistic models. This study represents one of the highest resolution validations of trait-based model predictions, and illustrates the utility of a novel remote sensing approach to predicting mosquito-borne disease risk.

No universal mathematical model for thermal performance curves across traits and taxonomic groups

In ectotherms, the performance of physiological, ecological and life-history traits universally increases with temperature to a maximum before decreasing again. Identifying the most appropriate thermal performance model for a specific trait type has broad applications, from metabolic modelling at the cellular level to forecasting the effects of climate change on population, ecosystem and disease transmission dynamics. To date, numerous mathematical models have been designed, but a thorough comparison among them is lacking. In particular, we do not know if certain models consistently outperform others and how factors such as sampling resolution and trait or organismal identity influence model performance. To fill this knowledge gap, we compile 2,739 thermal performance datasets from diverse traits and taxa, to which we fit a comprehensive set of 83 existing mathematical models. We detect remarkable variation in model performance that is not primarily driven by sampling resolution, trait type, or taxonomic information. Our results reveal a surprising lack of well-defined scenarios in which certain models are more appropriate than others. To aid researchers in selecting the appropriate set of models for any given dataset or research objective, we derive a classification of the 83 models based on the average similarity of their fits.

Host-feeding preferences and temperature shape the dynamics of West Nile virus: A mathematical model to predict the impacts of vector-host interactions and vector management on R0

West Nile virus (WNV) is prevalent across the United States, but its transmission patterns and spatio-temporal intensity vary significantly, particularly in the Eastern United States. For instance, Chicago has long been a hotspot for WNV cases due to its high cumulative incidence of infection, with the number of cases varying considerably from year to year. The abilities of host species to maintain and disseminate WNV, along with eco-epidemiological factors that influence vector-host contact rates underlie WNV transmission potential. There is growing evidence that several vectors exhibit strong feeding preferences towards different host communities. In our research study, we construct a process based weather driven ordinary differential equation (ODE) model to understand the impact of one vector species (Culex pipiens), its preferred avian and non-preferred human hosts on the basic reproduction number (R0). In developing this WNV transmission model, we account for the feeding index, which is defined as the relative preference of the vectors for taking blood meals from a competent avian host versus a non-competent mammalian host. We also include continuous introduction of infected agents into the model during the simulations as the introduction of WNV is not a single event phenomenon. We derive an analytic form of R0 to predict the conditions under which there will be an outbreak of WNV and the relationship between the feeding index and the efficacy of adulticide is highly nonlinear. In our mechanistic model, we also demonstrate that adulticide treatments produced significant reductions in the Culex pipiens population. Sensitivity analysis demonstrates that feeding index and rate of introduction of infected agents are two important factors beside the efficacy of adulticide. We validate our model by comparing simulations to surveillance data collected for the Culex pipiens complex in Cook County, Illinois, USA. Our results reveal that the interaction between the feeding index and mosquito abatement strategy is intricate, especially considering the fluctuating temperature conditions. This induces heterogeneous transmission patterns that need to be incorporated when modelling multi-host, multi-vector transmission models.

A weather-driven mathematical model of Culex population abundance and the impact of vector control interventions

Even as the incidence of mosquito-borne diseases like West Nile Virus (WNV) in North America has risen over the past decade, effectively modelling mosquito population density or, the abundance has proven to be a persistent challenge. It is critical to capture the fluctuations in mosquito abundance across seasons in order to forecast the varying risk of disease transmission from one year to the next. We develop a process-based mechanistic weather-driven Ordinary Differential Equation (ODE) model to study the population biology of both aqueous and terrestrial stages of mosquito population. The progression of mosquito lifecycle through these stages is influenced by different factors, including temperature, daylight hours, intra-species competition and the availability of aquatic habitats. Weather-driven parameters are utilised in our work, are a combination of laboratory research and literature data. In our model, we include precipitation data as a substitute for evaluating additional mortality in the mosquito population. We compute the Basic offspring number of the associated model and perform sensitivity analysis. Finally, we employ our model to assess the effectiveness of various adulticides strategies to predict the reduction in mosquito population. This enhancement in modelling of mosquito abundance can be instrumental in guiding interventions aimed at reducing mosquito populations and mitigating mosquito-borne diseases such as the WNV.

Spatiotemporally Explicit Epidemic Model for West Nile Virus Outbreak in Germany: An Inversely Calibrated Approach

Since the first autochthonous transmission of West Nile Virus was detected in Germany (WNV) in 2018, it has become endemic in several parts of the country and is continuing to spread due to the attainment of a suitable environment for vector occurrence and pathogen transmission. Increasing temperature associated with a changing climate has been identified as a potential driver of mosquito-borne disease in temperate regions. This scenario justifies the need for the development of a spatially and temporarily explicit model that describes the dynamics of WNV transmission in Germany. In this study, we developed a process-based mechanistic epidemic model driven by environmental and epidemiological data. Functional traits of mosquitoes and birds of interest were used to parameterize our compartmental model appropriately. Air temperature, precipitation, and relative humidity were the key climatic forcings used to replicate the fundamental niche responsible for supporting mosquito population and infection transmission risks in the study area. An inverse calibration method was used to optimize our parameter selection. Our model was able to generate spatially and temporally explicit basic reproductive number (R0) maps showing dynamics of the WNV occurrences across Germany, which was strongly associated with the deviation from daily means of climatic forcings, signaling the impact of a changing climate in vector-borne disease dynamics. Epidemiological data for human infections sourced from Robert Koch Institute and animal cases collected from the Animal Diseases Information System (TSIS) of the Friedrich-Loeffler-Institute were used to validate model-simulated transmission rates. From our results, it was evident that West Nile Virus is likely to spread towards the western parts of Germany with the rapid attainment of environmental suitability for vector mosquitoes and amplifying host birds, especially short-distance migratory birds. Locations with high risk of WNV outbreak (Baden-Württemberg, Bavaria, Berlin, Brandenburg, Hamburg, North Rhine-Westphalia, Rhineland-Palatinate, Saarland, Saxony-Anhalt and Saxony) were shown on R0 maps. This study presents a path for developing an early warning system for vector-borne diseases driven by climate change.

Temperature dependence of mosquitoes: Comparing mechanistic and machine learning approaches

Mosquito vectors of pathogens (e.g., Aedes, Anopheles, and Culex spp. which transmit dengue, Zika, chikungunya, West Nile, malaria, and others) are of increasing concern for global public health. These vectors are geographically shifting under climate and other anthropogenic changes. As small-bodied ectotherms, mosquitoes are strongly affected by temperature, which causes unimodal responses in mosquito life history traits (e.g., biting rate, adult mortality rate, mosquito development rate, and probability of egg-to-adult survival) that exhibit upper and lower thermal limits and intermediate thermal optima in laboratory studies. However, it remains unknown how mosquito thermal responses measured in laboratory experiments relate to the realized thermal responses of mosquitoes in the field. To address this gap, we leverage thousands of global mosquito occurrences and geospatial satellite data at high spatial resolution to construct machine-learning based species distribution models, from which vector thermal responses are estimated. We apply methods to restrict models to the relevant mosquito activity season and to conduct ecologically plausible spatial background sampling centered around ecoregions for comparison to mosquito occurrence records. We found that thermal minima estimated from laboratory studies were highly correlated with those from the species distributions (r = 0.87). The thermal optima were less strongly correlated (r = 0.69). For most species, we did not detect thermal maxima from their observed distributions so were unable to compare to laboratory-based estimates. The results suggest that laboratory studies have the potential to be highly transportable to predicting lower thermal limits and thermal optima of mosquitoes in the field. At the same time, lab-based models likely capture physiological limits on mosquito persistence at high temperatures that are not apparent from field-based observational studies but may critically determine mosquito responses to climate warming. Our results indicate that lab-based and field-based studies are highly complementary; performing the analyses in concert can help to more comprehensively understand vector response to climate change.

A flexible model for thermal performance curves

Temperature responses of many biological traits-including population growth, survival, and development-are described by thermal performance curves (TPCs) with phenomenological models like the Briere function or mechanistic models related to chemical kinetics. Existing TPC models are either simple but inflexible in shape, or flexible yet difficult to interpret in biological terms. Here we present flexTPC: a model that is parameterized exclusively in terms of biologically interpretable quantities, including the thermal minimum, optimum, and maximum, and the maximum trait value. FlexTPC can describe unimodal temperature responses of any skewness and thermal breadth, enabling direct comparisons across populations, traits, or taxa with a single model. We apply flexTPC to various microbial and entomological datasets, compare results with the Briere model, and find that flexTPC often has better predictive performance. The interpretability of flexTPC makes it ideal for modeling how thermal responses change with ecological stressors or evolve over time.

Effects of climate change and human activities on vector-borne diseases

Vector-borne diseases are transmitted by haematophagous arthropods (for example, mosquitoes, ticks and sandflies) to humans and wild and domestic animals, with the largest burden on global public health disproportionately affecting people in tropical and subtropical areas. Because vectors are ectothermic, climate and weather alterations (for example, temperature, rainfall and humidity) can affect their reproduction, survival, geographic distribution and, consequently, ability to transmit pathogens. However, the effects of climate change on vector-borne diseases can be multifaceted and complex, sometimes with ambiguous consequences. In this Review, we discuss the potential effects of climate change, weather and other anthropogenic factors, including land use, human mobility and behaviour, as possible contributors to the redistribution of vectors and spread of vector-borne diseases worldwide.

High temperatures reduce growth, infection, and transmission of a naturally occurring fungal plant pathogen

Climate change is rapidly altering the distribution of suitable habitats for many species as well as their pathogenic microbes. For many pathogens, including vector-borne diseases of humans and agricultural pathogens, climate change is expected to increase transmission and lead to pathogen range expansions. However, if pathogens have a lower heat tolerance than their host, increased warming could generate so-called thermal refugia for hosts. Predicting the outcomes of warming on disease transmission requires detailed knowledge of the thermal tolerances of both the host and the pathogen. Such thermal tolerance studies are generally lacking for fungal pathogens of wild plant populations, despite the fact that plants form the base of all terrestrial communities. Here, we quantified three aspects of the thermal tolerance (growth, infection, and propagule production) of the naturally occurring fungal pathogen Microbotryum lychnidis-dioicae, which causes a sterilizing anther-smut disease on the herbaceous plant Silene latifolia. We also quantified two aspects of host thermal tolerance: seedling survival and flowering rate. We found that temperatures >30°C reduced the ability of anther-smut spores to germinate, grow, and conjugate in vitro. In addition, we found that high temperatures (30°C) during or shortly after the time of inoculation strongly reduced the likelihood of infection in seedlings. Finally, we found that high summer temperatures in the field temporarily cured infected plants, likely reducing transmission. Notably, high temperatures did not reduce survival or flowering of the host plants. Taken together, our results show that the fungus is considerably more sensitive to high temperatures than its host plant. A warming climate could therefore result in reduced disease spread or even local pathogen extirpation, leading to thermal refugia for the host.

Population-specific thermal responses contribute to regional variability in arbovirus transmission with changing climates

Temperature is increasing globally, and vector-borne diseases are particularly responsive to such increases. While it is known that temperature influences mosquito life history traits, transmission models have not historically considered population-specific effects of temperature. We assessed the interaction between Culex pipiens population and temperature in New York State (NYS) and utilized novel empirical data to inform predictive models of West Nile virus (WNV) transmission. Genetically and regionally distinct populations from NYS were reared at various temperatures, and life history traits were monitored and used to inform trait-based models. Variation in Cx. pipiens life history traits and population-dependent thermal responses account for a predicted 2.9°C difference in peak transmission that is reflected in regional differences in WNV prevalence. We additionally identified genetic signatures that may contribute to distinct thermal responses. Together, these data demonstrate how population variation contributes to significant geographic variability in arbovirus transmission with changing climates.

Climate change and disorders of the nervous system

Anthropogenic climate change is affecting people's health, including those with neurological and psychiatric diseases. Currently, making inferences about the effect of climate change on neurological and psychiatric diseases is challenging because of an overall sparsity of data, differing study methods, paucity of detail regarding disease subtypes, little consideration of the effect of individual and population genetics, and widely differing geographical locations with the potential for regional influences. However, evidence suggests that the incidence, prevalence, and severity of many nervous system conditions (eg, stroke, neurological infections, and some mental health disorders) can be affected by climate change. The data show broad and complex adverse effects, especially of temperature extremes to which people are unaccustomed and wide diurnal temperature fluctuations. Protective measures might be possible through local forecasting. Few studies project the future effects of climate change on brain health, hindering policy developments. Robust studies on the threats from changing climate for people who have, or are at risk of developing, disorders of the nervous system are urgently needed.

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.

Immunoinformatics assisted profiling of West Nile virus proteome to determine immunodominant epitopes for the development of next-generation multi-peptide vaccine

Emerging infectious diseases represent a significant threat to global health, with West Nile virus (WNV) being a prominent example due to its potential to cause severe neurological disorders alongside mild feverish conditions. Particularly prevalent in the continental United States, WNV has emerged as a global concern, with outbreaks indicating the urgent need for effective prophylactic measures. The current problem is that the absence of a commercial vaccine against WNV highlights a critical gap in preventive strategies against WNV. This study aims to address this gap by proposing a novel, multivalent vaccine designed using immunoinformatics approaches to elicit comprehensive humoral and cellular immune responses against WNV. The objective of the study is to provide a theoretical framework for experimental scientists to formulate of vaccine against WNV and tackle the current problem by generating an immune response inside the host. The research employs reverse vaccinology and subtractive proteomics methodologies to identify NP_041724.2 polyprotein and YP_009164950.1 truncated flavivirus polyprotein NS1 as the prime antigens. The selection process for epitopes focused on B and T-cell reactivity, antigenicity, water solubility, and non-allergenic properties, prioritizing candidates with the potential for broad immunogenicity and safety. The designed vaccine construct integrates these epitopes, connected via GPGPG linkers, and supplemented with an adjuvant with the help of another linker EAAAK, to enhance immunogenicity. Preliminary computational analyses suggest that the proposed vaccine could achieve near-universal coverage, effectively targeting approximately 99.74% of the global population, with perfect coverage in specific regions such as Sweden and Finland. Molecular docking and immune simulation studies further validate the potential efficacy of the vaccine, indicating strong binding affinity with toll-like receptor 3 (TLR-3) and promising immune response profiles, including significant antibody-mediated and cellular responses. These findings present the vaccine construct as a viable candidate for further development and testing. While the theoretical and computational results are promising, advancing from in-silico predictions to a tangible vaccine requires comprehensive laboratory validation. This next step is essential to confirm the vaccine's efficacy and safety in eliciting an immune response against WNV. Through this study, we propose a novel approach to vaccine development against WNV and contribute to the broader field of immunoinformatics, showcasing the potential to accelerate the design of effective vaccines against emerging viral threats. The journey from hypothesis to practical solution embodies the interdisciplinary collaboration essential for modern infectious disease management and prevention strategies.

The effect of temperature on the boundary conditions of West Nile virus circulation in Europe

West Nile virus (WNV) is a vector-borne flavivirus that causes an increasing number of human and equine West Nile fever cases in Europe. While the virus has been present in the Mediterranean basin and the Balkans since the 1960s, recent years have witnessed its northward expansion, with the first human cases reported in Germany in 2018 and the Netherlands in 2020. WNV transmission and amplification within mosquitoes are temperature-dependent. This study applies a mathematical modelling approach to assess the conditions under which WNV circulation occurs based on the proportion of mosquito bites on WNV-competent birds (dilution), vector-host ratios, mosquito season length and the observed daily temperature data. We modelled five distinct European regions where previous WNV circulation has been observed within the Netherlands, Germany, Spain, Italy, and Greece. We observed that the number of days in which the basic reproduction number (R0) is above one, increased over the last 40 years in all five regions. In the Netherlands, the number of days in which the R0 is above one, is 70% lower than in Spain. The temperature in Greece, Spain and Italy allowed for circulation under low vector-host ratios, and at a high dilution. On the other hand in the Netherlands and Germany, given the observed daily temperature, the thresholds for circulation requires a lower dilution and higher vector-host ratios. For the Netherlands, a short window of introductions between late May and mid-June would result in detectable outbreaks. Our findings revealed that the temperate maritime climate of the Netherlands allows WNV circulation primarily during warmer summers, and only under high vector-host ratios. This research contributes valuable insights into the dynamic relationship between temperature, vector properties, and WNV transmission, offering guidance for proactive strategies in addressing this emerging health threat in Europe.

Long-term trends and spatial patterns of West Nile Virus emergence in California, 2004-2021

AIMS

West Nile Virus (WNV) has remained a persistent source of vector-borne disease risk in California since first being identified in the state in 2003. The geographic distribution of WNV activity is relatively widespread, but varies considerably across different regions within the state. Spatial variation in human WNV infection depends upon social-ecological factors that influence mosquito populations and virus transmission dynamics. Measuring changes in spatial patterns over time is necessary for uncovering the underlying regional drivers of disease risk.

METHODS AND RESULTS

In this study, we utilized statewide surveillance data to quantify temporal changes and spatial patterns of WNV activity in California. We obtained annual WNV mosquito surveillance data from 2004 through 2021 from the California Arbovirus Surveillance Program. Geographic coordinates for mosquito pools were analysed using a suite of spatial statistics to identify and classify patterns in WNV activity over time.

CONCLUSIONS

We detected clear patterns of non-random WNV risk during the study period, including emerging hot spots in the Central Valley and non-random periods of oscillating WNV risk in Southern and Northern California subregions. Our findings offer new insights into 18 years of spatio-temporal variation in WNV activity across California, which may be used for targeted surveillance efforts and public health interventions.

Estimating the effects of temperature on transmission of the human malaria parasite, Plasmodium falciparum

Despite concern that climate change could increase the human risk to malaria in certain areas, the temperature dependency of malaria transmission is poorly characterized. Here, we use a mechanistic model fitted to experimental data to describe how Plasmodium falciparum infection of the African malaria vector, Anopheles gambiae, is modulated by temperature, including its influences on parasite establishment, conversion efficiency through parasite developmental stages, parasite development rate, and overall vector competence. We use these data, together with estimates of the survival of infected blood-fed mosquitoes, to explore the theoretical influence of temperature on transmission in four locations in Kenya, considering recent conditions and future climate change. Results provide insights into factors limiting transmission in cooler environments and indicate that increases in malaria transmission due to climate warming in areas like the Kenyan Highlands, might be less than previously predicted.

Landscape level associations between birds, mosquitoes and microclimates: possible consequences for disease transmission?

BACKGROUND

Mosquito-borne diseases are on the rise. While climatic factors have been linked to disease occurrences, they do not explain the non-random spatial distribution in disease outbreaks. Landscape-related factors, such as vegetation structure, likely play a crucial but hitherto unquantified role.

METHODS

We explored how three critically important factors that are associated with mosquito-borne disease outbreaks: microclimate, mosquito abundance and bird communities, vary at the landscape scale. We compared the co-occurrence of these three factors in two contrasting habitat types (forest versus grassland) across five rural locations in the central part of the Netherlands between June and September 2021.

RESULTS

Our results show that forest patches provide a more sheltered microclimate, and a higher overall abundance of birds. When accounting for differences in landscape characteristics, we also observed that the number of mosquitoes was higher in isolated forest patches.

CONCLUSIONS

Our findings indicate that, at the landscape scale, variation in tree cover coincides with suitable microclimate and high Culex pipiens and bird abundance. Overall, these factors can help understand the non-random spatial distribution of mosquito-borne disease outbreaks.

Accelerating targeted mosquito control efforts through mobile West Nile virus detection

BACKGROUND

Different mosquito control strategies have been implemented to mitigate or prevent mosquito-related public health situations. Modern mosquito control largely relies on multiple approaches, including targeted, specific treatments. Given this, it is becoming increasingly important to supplement these activities with rapid and mobile diagnostic capacities for mosquito-borne diseases. We aimed to create and test the applicability of a rapid diagnostic system for West Nile virus that can be used under field conditions.

METHODS

In this pilot study, various types of adult mosquito traps were applied within the regular mosquito monitoring activity framework for mosquito control. Then, the captured specimens were used for the detection of West Nile virus RNA under field conditions with a portable qRT-PCR approach within 3-4 h. Then, positive samples were subjected to confirmatory RT-PCR or NGS sequencing in the laboratory to obtain genome information of the virus. We implemented phylogenetic analysis to characterize circulating strains.

RESULTS

A total of 356 mosquito individuals representing 7 species were processed in 54 pools, each containing up to 20 individuals. These pools were tested for the presence of West Nile virus, and two pools tested positive, containing specimens from the Culex pipiens and Anopheles atroparvus mosquito species. As a result of subsequent sequencing, we present the complete genome of West Nile virus and Bagaza virus.

CONCLUSIONS

The rapid identification of infected mosquitoes is the most important component of quick response adulticide or larvicide treatments to prevent human cases. The conceptual framework of real-time surveillance can be optimized for other pathogens and situations not only in relation to West Nile virus. We present an early warning system for mosquito-borne diseases and demonstrate its application to aid rapid-response mosquito control actions.

Mechanistic models for West Nile virus transmission: a systematic review of features, aims and parametrization

Mathematical models within the Ross-Macdonald framework increasingly play a role in our understanding of vector-borne disease dynamics and as tools for assessing scenarios to respond to emerging threats. These threats are typically characterized by a high degree of heterogeneity, introducing a range of possible complexities in models and challenges to maintain the link with empirical evidence. We systematically identified and analysed a total of 77 published papers presenting compartmental West Nile virus (WNV) models that use parameter values derived from empirical studies. Using a set of 15 criteria, we measured the dissimilarity compared with the Ross-Macdonald framework. We also retrieved the purpose and type of models and traced the empirical sources of their parameters. Our review highlights the increasing refinements in WNV models. Models for prediction included the highest number of refinements. We found uneven distributions of refinements and of evidence for parameter values. We identified several challenges in parametrizing such increasingly complex models. For parameters common to most models, we also synthesize the empirical evidence for their values and ranges. The study highlights the potential to improve the quality of WNV models and their applicability for policy by establishing closer collaboration between mathematical modelling and empirical work.

Temperature and intraspecific variation affect host-parasite interactions

Parasites play key roles in regulating aquatic ecosystems, yet the impact of climate warming on their ecology and disease transmission remains poorly understood. Isolating the effect of warming is challenging as transmission involves multiple interacting species and potential intraspecific variation in temperature responses of one or more of these species. Here, we leverage a wide-ranging mosquito species and its facultative parasite as a model system to investigate the impact of temperature on host-parasite interactions and disease transmission. We conducted a common garden experiment measuring parasite growth and infection rates at seven temperatures using 12 field-collected parasite populations and a single mosquito population. We find that both free-living growth rates and infection rates varied with temperature, which were highest at 18-24.5 °C and 13 °C, respectively. Further, we find intraspecific variation in peak performance temperature reflecting patterns of local thermal adaptation-parasite populations from warmer source environments typically had higher thermal optima for free-living growth rates. For infection rates, we found a significant interaction between parasite population and nonlinear effects of temperature. These findings underscore the need to consider both host and parasite thermal responses, as well as intraspecific variation in thermal responses, when predicting the impacts of climate change on disease in aquatic ecosystems.

Mosquito thermal tolerance is remarkably constrained across a large climatic range

How mosquitoes may respond to rapid climate warming remains unknown for most species, but will have major consequences for their future distributions, with cascading impacts on human well-being, biodiversity and ecosystem function. We investigated the adaptive potential of a wide-ranging mosquito species, Aedes sierrensis, across a large climatic gradient by conducting a common garden experiment measuring the thermal limits of mosquito life-history traits. Although field-collected populations originated from vastly different thermal environments that spanned over 1200 km, we found limited variation in upper thermal tolerance between populations. In particular, the upper thermal limits of all life-history traits varied by less than 3°C across the species range and, for most traits, did not differ significantly between populations. For one life-history trait-pupal development rate-we did detect significant variation in upper thermal limits between populations, and this variation was strongly correlated with source temperatures, providing evidence of local thermal adaptation for pupal development. However, we found that maximum environmental temperatures across most of the species' range already regularly exceed the highest upper thermal limits estimated under constant temperatures. This result suggests that strategies for coping with and/or avoiding thermal extremes are likely key components of current and future mosquito thermal tolerance.

Climate warming is expanding dengue burden in the Americas and Asia

Climate change poses significant threats to public health, with dengue representing a growing concern due to its high existing burden and sensitivity to climatic conditions. Yet, the quantitative impacts of temperature warming on dengue, both in the past and in the future, remain poorly understood. In this study, we quantify how dengue responds to climatic fluctuations, and use this inferred temperature response to estimate the impacts of historical warming and forecast trends under future climate change scenarios. To estimate the causal impact of temperature on the spread of dengue in the Americas and Asia, we assembled a dataset encompassing nearly 1.5 million dengue incidence records from 21 countries. Our analysis revealed a nonlinear relationship between temperature and dengue incidence with the largest marginal effects at lower temperatures (around 15°C), peak incidence at 27.8°C (95% CI: 27.3 - 28.2°C), and subsequent declines at higher temperatures. Our findings indicate that historical climate change has already increased dengue incidence 18% (12 - 25%) in the study region, and projections suggest a potential increase of 40% (17 - 76) to 57% (33 - 107%) by mid-century depending on the climate scenario, with some areas seeing up to 200% increases. Notably, our models suggest that lower emissions scenarios would substantially reduce the warming-driven increase in dengue burden. Together, these insights contribute to the broader understanding of how long-term climate patterns influence dengue, providing a valuable foundation for public health planning and the development of strategies to mitigate future risks due to climate change.

Editorial: Climate Change and the Spread of Vector-Borne Diseases, Including Dengue, Malaria, Lyme Disease, and West Nile Virus Infection

The major health threats from climate change include increasing temperatures, air pollution, extreme weather events, changes in the spread of infectious diseases, antimicrobial resistance, emerging pathogens, and an increase in vector-borne disease. Between October and December 2023, in 200 medical journal, epidemiologists, clinicians, healthcare policymakers, and journal editors published an emergency call to action to health professionals, the United Nations, and political leaders on climate change and its effects on the ecosystem and human health. Also, in December 2023, the Intergovernmental Panel on Climate Change (IPCC) published its sixth Assessment Report (AR6) that summarizes current knowledge, impacts, and health risks from climate change, as well as suggestions for mitigation and adaptation. For over a decade, the IPCC has reported that the prevalence of vector-borne diseases has increased and highlighted the importance of monitoring dengue, malaria, Lyme disease, West Nile virus infection, and other vector-borne diseases. This editorial aims to provide an update on the association between climate change and the spread of vector-borne diseases and highlights the urgent need for public health and disease prevention and treatment strategies to control the rise in vector-borne diseases.

Phenotypic adaptation to temperature in the mosquito vector, Aedes aegypti

Most models exploring the effects of climate change on mosquito-borne disease ignore thermal adaptation. However, if local adaptation leads to changes in mosquito thermal responses, "one size fits all" models could fail to capture current variation between populations and future adaptive responses to changes in temperature. Here, we assess phenotypic adaptation to temperature in Aedes aegypti, the primary vector of dengue, Zika, and chikungunya viruses. First, to explore whether there is any difference in existing thermal response of mosquitoes between populations, we used a thermal knockdown assay to examine five populations of Ae. aegypti collected from climatically diverse locations in Mexico, together with a long-standing laboratory strain. We identified significant phenotypic variation in thermal tolerance between populations. Next, to explore whether such variation can be generated by differences in temperature, we conducted an experimental passage study by establishing six replicate lines from a single field-derived population of Ae. aegypti from Mexico, maintaining half at 27°C and the other half at 31°C. After 10 generations, we found a significant difference in mosquito performance, with the lines maintained under elevated temperatures showing greater thermal tolerance. Moreover, these differences in thermal tolerance translated to shifts in the thermal performance curves for multiple life-history traits, leading to differences in overall fitness. Together, these novel findings provide compelling evidence that Ae. aegypti populations can and do differ in thermal response, suggesting that simplified thermal performance models might be insufficient for predicting the effects of climate on vector-borne disease transmission.

The 2023 report of the Lancet Countdown on health and climate change: the imperative for a health-centred response in a world facing irreversible harms

The Lancet Countdown is an international research collaboration that independently monitors the evolving impacts of climate change on health, and the emerging health opportunities of climate action. In its eighth iteration, this 2023 report draws on the expertise of 114 scientists and health practitioners from 52 research institutions and UN agencies worldwide to provide its most comprehensive assessment yet.

In 2022, the Lancet Countdown warned that people’s health is at the mercy of fossil fuels and stressed the transformative opportunity of jointly tackling the concurrent climate change, energy, cost-of-living, and health crises for human health and wellbeing. This year’s report finds few signs of such progress. At the current 10-year mean heating of 1·14°C above pre-industrial levels, climate change is increasingly impacting the health and survival of people worldwide, and projections show these risks could worsen steeply with further inaction. However, with health matters gaining prominence in climate change negotiations, this report highlights new opportunities to deliver health-promoting climate change action and a safe and thriving future for all.

Temperature dependence of mosquitoes: comparing mechanistic and machine learning approaches

Mosquito vectors of pathogens (e.g., Aedes , Anopheles , and Culex spp. which transmit dengue, Zika, chikungunya, West Nile, malaria, and others) are of increasing concern for global public health. These vectors are geographically shifting under climate and other anthropogenic changes. As small-bodied ectotherms, mosquitoes are strongly affected by temperature, which causes unimodal responses in mosquito life history traits (e.g., biting rate, adult mortality rate, mosquito development rate, and probability of egg-to-adult survival) that exhibit upper and lower thermal limits and intermediate thermal optima in laboratory studies. However, it remains unknown how mosquito thermal responses measured in laboratory experiments relate to the realized thermal responses of mosquitoes in the field. To address this gap, we leverage thousands of global mosquito occurrences and geospatial satellite data at high spatial resolution to construct machine-learning based species distribution models, from which vector thermal responses are estimated. We apply methods to restrict models to the relevant mosquito activity season and to conduct ecologically-plausible spatial background sampling centered around ecoregions for comparison to mosquito occurrence records. We found that thermal minima estimated from laboratory studies were highly correlated with those from the species distributions (r = 0.90). The thermal optima were less strongly correlated (r = 0.69). For most species, we did not detect thermal maxima from their observed distributions so were unable to compare to laboratory-based estimates. The results suggest that laboratory studies have the potential to be highly transportable to predicting lower thermal limits and thermal optima of mosquitoes in the field. At the same time, lab-based models likely capture physiological limits on mosquito persistence at high temperatures that are not apparent from field-based observational studies but may critically determine mosquito responses to climate warming.

Mosquito thermal tolerance is remarkably constrained across a large climatic range

How mosquitoes may respond to rapid climate warming remains unknown for most species, but will have major consequences for their future distributions, with cascading impacts on human well-being, biodiversity, and ecosystem function. We investigated the adaptive potential of a wide-ranging mosquito species, Aedes sierrensis, across a large climatic gradient by conducting a common garden experiment measuring the thermal limits of mosquito life history traits. Although field-collected populations originated from vastly different thermal environments that spanned over 1,200 km, we found remarkably limited variation in upper thermal tolerance between populations, with the upper thermal limits of fitness varying by <1°C across the species range. For one life history trait-pupal development rate-we did detect significant variation in upper thermal limits between populations, and this variation was strongly correlated with source temperatures, providing evidence of local thermal adaptation for pupal development. However, we found environmental temperatures already regularly exceed our highest estimated upper thermal limits throughout most of the species range, suggesting limited potential for mosquito thermal tolerance to evolve on pace with warming. Strategies for avoiding high temperatures such as diapause, phenological shifts, and behavioral thermoregulation are likely important for mosquito persistence.

Multi-Model Prediction of West Nile Virus Neuroinvasive Disease With Machine Learning for Identification of Important Regional Climatic Drivers

West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental United States (CONUS). Spatial heterogeneity in historical incidence, environmental factors, and complex ecology make prediction of spatiotemporal variation in WNV transmission challenging. Machine learning provides promising tools for identification of important variables in such situations. To predict annual WNV neuroinvasive disease (WNND) cases in CONUS (2015-2021), we fitted 10 probabilistic models with variation in complexity from naïve to machine learning algorithm and an ensemble. We made predictions in each of nine climate regions on a hexagonal grid and evaluated each model's predictive accuracy. Using the machine learning models (random forest and neural network), we identified the relative importance and variation in ranking of predictors (historical WNND cases, climate anomalies, human demographics, and land use) across regions. We found that historical WNND cases and population density were among the most important factors while anomalies in temperature and precipitation often had relatively low importance. While the relative performance of each model varied across climatic regions, the magnitude of difference between models was small. All models except the naïve model had non-significant differences in performance relative to the baseline model (negative binomial model fit per hexagon). No model, including the ensemble or more complex machine learning models, outperformed models based on historical case counts on the hexagon or region level; these models are good forecasting benchmarks. Further work is needed to assess if predictive capacity can be improved beyond that of these historical baselines.

The utility of a Bayesian predictive model to forecast neuroinvasive West Nile virus disease in the United States of America, 2022

Arboviruses (arthropod-borne-viruses) are an emerging global health threat that are rapidly spreading as climate change, international business transport, and landscape fragmentation impact local ecologies. Since its initial detection in 1999, West Nile virus has shifted from being a novel to an established arbovirus in the United States of America. Subsequently, more than 25,000 cases of West Nile neuro-invasive disease have been diagnosed, cementing West Nile virus as an arbovirus of public health importance. Given its novelty in the United States of America, high-risk ecologies are largely underdefined making targeted population-level public health interventions challenging. Using the Centers for Disease Control and Prevention ArboNET neuroinvasive West Nile virus data from 2000-2021, this study aimed to predict neuroinvasive West Nile virus human cases at the county level for the contiguous USA using a spatio-temporal Bayesian negative binomial regression model. The model includes environmental, climatic, and demographic factors, as well as the distribution of host species. An integrated nested Laplace approximation approach was used to fit our model. To assess model prediction accuracy, annual counts were withheld, forecasted, and compared to observed values. The validated models were then fit to the entire dataset for 2022 predictions. This proof-of-concept mathematical, geospatial modelling approach has proven utility for national health agencies seeking to allocate funding and other resources for local vector control agencies tackling West Nile virus and other notifiable arboviral agents.

Ecological Niche and Positive Clusters of Two West Nile Virus Vectors in Ontario, Canada

West Nile virus (WNV) is a mosquito-borne pathogen associated with uncommon but severe neurological complications in humans, especially among the elderly and immune-compromised. In Northeastern North America, the Culex pipiens/restuans complex and Aedes vexans are the two principal vector mosquito species/species groups of WNV. Using a 10-year surveillance dataset of WNV vector captures at 118 sites across an area of 40,000 km2 in Eastern Ontario, Canada, the ecological niches of Cx. pipiens/restuans and Aedes vexans were modeled by random forest analysis. Spatiotemporal clusters of WNV-positive mosquito pools were identified using Kulldorf's spatial scan statistic. The study region encompasses land cover types and climate representative of highly populated Southeastern Canada. We found highest vector habitat suitability in the eastern half of the study area, where temperatures are generally warmer (variable importance > 0.40) and residential and agricultural cropland cover is more prominent (variable importance > 0.25). We found spatiotemporal clusters of high WNV infection rates around the city of Ottawa in both mosquito vector species. These results support the previous literature in the same region and elsewhere suggesting areas surrounding highly populated areas are also high-risk areas for vector-borne zoonoses such as the WNV.

Invasive hematophagous arthropods and associated diseases in a changing world

Biological invasions have increased significantly with the tremendous growth of international trade and transport. Hematophagous arthropods can be vectors of infectious and potentially lethal pathogens and parasites, thus constituting a growing threat to humans-especially when associated with biological invasions. Today, several major vector-borne diseases, currently described as emerging or re-emerging, are expanding in a world dominated by climate change, land-use change and intensive transportation of humans and goods. In this review, we retrace the historical trajectory of these invasions to better understand their ecological, physiological and genetic drivers and their impacts on ecosystems and human health. We also discuss arthropod management strategies to mitigate future risks by harnessing ecology, public health, economics and social-ethnological considerations. Trade and transport of goods and materials, including vertebrate introductions and worn tires, have historically been important introduction pathways for the most prominent invasive hematophagous arthropods, but sources and pathways are likely to diversify with future globalization. Burgeoning urbanization, climate change and the urban heat island effect are likely to interact to favor invasive hematophagous arthropods and the diseases they can vector. To mitigate future invasions of hematophagous arthropods and novel disease outbreaks, stronger preventative monitoring and transboundary surveillance measures are urgently required. Proactive approaches, such as the use of monitoring and increased engagement in citizen science, would reduce epidemiological and ecological risks and could save millions of lives and billions of dollars spent on arthropod control and disease management. Last, our capacities to manage invasive hematophagous arthropods in a sustainable way for worldwide ecosystems can be improved by promoting interactions among experts of the health sector, stakeholders in environmental issues and policymakers (e.g. the One Health approach) while considering wider social perceptions.

The (Re-)Emergence and Spread of Viral Zoonotic Disease: A Perfect Storm of Human Ingenuity and Stupidity

Diseases that are transmitted from vertebrate animals to humans are referred to as zoonotic diseases. Although microbial agents such as bacteria and parasites are linked to zoonotic events, viruses account for a high percentage of zoonotic diseases that have emerged. Worryingly, the 21st century has seen a drastic increase in the emergence and re-emergence of viral zoonotic disease. Even though humans and animals have coexisted for millennia, anthropogenic factors have severely increased interactions between the two populations, thereby increasing the risk of disease spill-over. While drivers such as climate shifts, land exploitation and wildlife trade can directly affect the (re-)emergence of viral zoonotic disease, globalisation, geopolitics and social perceptions can directly facilitate the spread of these (re-)emerging diseases. This opinion paper discusses the "intelligent" nature of viruses and their exploitation of the anthropogenic factors driving the (re-)emergence and spread of viral zoonotic disease in a modernised and connected world.

Humidity - The overlooked variable in the thermal biology of mosquito-borne disease

Vector-borne diseases cause significant financial and human loss, with billions of dollars spent on control. Arthropod vectors experience a complex suite of environmental factors that affect fitness, population growth and species interactions across multiple spatial and temporal scales. Temperature and water availability are two of the most important abiotic variables influencing their distributions and abundances. While extensive research on temperature exists, the influence of humidity on vector and pathogen parameters affecting disease dynamics are less understood. Humidity is often underemphasized, and when considered, is often treated as independent of temperature even though desiccation likely contributes to declines in trait performance at warmer temperatures. This Perspectives explores how humidity shapes the thermal performance of mosquito-borne pathogen transmission. We summarize what is known about its effects and propose a conceptual model for how temperature and humidity interact to shape the range of temperatures across which mosquitoes persist and achieve high transmission potential. We discuss how failing to account for these interactions hinders efforts to forecast transmission dynamics and respond to epidemics of mosquito-borne infections. We outline future research areas that will ground the effects of humidity on the thermal biology of pathogen transmission in a theoretical and empirical framework to improve spatial and temporal prediction of vector-borne pathogen transmission.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Human footprint is associated with shifts in the assemblages of major vector-borne diseases

Predicting how increasing intensity of human-environment interactions affects pathogen transmission is essential to anticipate changing disease risks and identify appropriate mitigation strategies. Vector-borne diseases (VBDs) are highly responsive to environmental changes, but such responses are notoriously difficult to isolate because pathogen transmission depends on a suite of ecological and social responses in vectors and hosts that may differ across species. Here we use the emerging tools of cumulative pressure mapping and machine learning to better understand how the occurrence of six medically important VBDs, differing in ecology from sylvatic to urban, respond to multidimensional effects of human pressure. We find that not only is human footprint-an index of human pressure, incorporating built environments, energy and transportation infrastructure, agricultural lands and human population density-an important predictor of VBD occurrence, but there are clear thresholds governing the occurrence of different VBDs. Across a spectrum of human pressure, diseases associated with lower human pressure, including malaria, cutaneous leishmaniasis and visceral leishmaniasis, give way to diseases associated with high human pressure, such as dengue, chikungunya and Zika. These heterogeneous responses of VBDs to human pressure highlight thresholds of land-use transitions that may lead to abrupt shifts in infectious disease burdens and public health needs.

A Habitat Model for Disease Vector Aedes aegypti in the Tampa Bay Area, FloridA

Within the contiguous USA, Florida is unique in having tropical and subtropical climates, a great abundance and diversity of mosquito vectors, and high rates of human travel. These factors contribute to the state being the national ground zero for exotic mosquito-borne diseases, as evidenced by local transmission of viruses spread by Aedes aegypti, including outbreaks of dengue in 2022 and Zika in 2016. Because of limited treatment options, integrated vector management is a key part of mitigating these arboviruses. Practical knowledge of when and where mosquito populations of interest exist is critical for surveillance and control efforts, and habitat predictions at various geographic scales typically rely on ecological niche modeling. However, most of these models, usually created in partnership with academic institutions, demand resources that otherwise may be too time-demanding or difficult for mosquito control programs to replicate and use effectively. Such resources may include intensive computational requirements, high spatiotemporal resolutions of data not regularly available, and/or expert knowledge of statistical analysis. Therefore, our study aims to partner with mosquito control agencies in generating operationally useful mosquito abundance models. Given the increasing threat of mosquito-borne disease transmission in Florida, our analytic approach targets recent Ae. aegypti abundance in the Tampa Bay area. We investigate explanatory variables that: 1) are publicly available, 2) require little to no preprocessing for use, and 3) are known factors associated with Ae. aegypti ecology. Out of our 4 final models, none required more than 5 out of the 36 predictors assessed (13.9%). Similar to previous literature, the strongest predictors were consistently 3- and 4-wk temperature and precipitation lags, followed closely by 1 of 2 environmental predictors: land use/land cover or normalized difference vegetation index. Surprisingly, 3 of our 4 final models included one or more socioeconomic or demographic predictors. In general, larger sample sizes of trap collections and/or citizen science observations should result in greater confidence in model predictions and validation. However, given disparities in trap collections across jurisdictions, individual county models rather than a multicounty conglomerate model would likely yield stronger model fits. Ultimately, we hope that the results of our assessment will enable more accurate and precise mosquito surveillance and control of Ae. aegypti in Florida and beyond.

Seasonality influences key physiological components contributing to Culex pipiens vector competence

Mosquitoes are the most important animal vector of disease on the planet, transmitting a variety of pathogens of both medical and veterinary importance. Mosquito-borne diseases display distinct seasonal patterns driven by both environmental and biological variables. However, an important, yet unexplored component of these patterns is the potential for seasonal influences on mosquito physiology that may ultimately influence vector competence. To address this question, we selected Culex pipiens, a primary vector of the West Nile virus (WNV) in the temperate United States, to examine the seasonal impacts on mosquito physiology by examining known immune and bacterial components implicated in mosquito arbovirus infection. Semi-field experiments were performed under spring, summer, and late-summer conditions, corresponding to historically low-, medium-, and high-intensity periods of WNV transmission, respectively. Through these experiments, we observed differences in the expression of immune genes and RNA interference (RNAi) pathway components, as well as changes in the distribution and abundance of Wolbachia in the mosquitoes across seasonal cohorts. Together, these findings support the conclusion that seasonal changes significantly influence mosquito physiology and components of the mosquito microbiome, suggesting that seasonality may impact mosquito susceptibility to pathogen infection, which could account for the temporal patterns in mosquito-borne disease transmission.

Understanding West Nile virus transmission: Mathematical modelling to quantify the most critical parameters to predict infection dynamics

West Nile disease is a vector-borne disease caused by West Nile virus (WNV), involving mosquitoes as vectors and birds as maintenance hosts. Humans and other mammals can be infected via mosquito bites, developing symptoms ranging from mild fever to severe neurological infection. Due to the worldwide spread of WNV, human infection risk is high in several countries. Nevertheless, there are still several knowledge gaps regarding WNV dynamics. Several aspects of transmission taking place between birds and mosquitoes, such as the length of the infectious period in birds or mosquito biting rates, are still not fully understood, and precise quantitative estimates are still lacking for the European species involved. This lack of knowledge affects the precision of parameter values when modelling the infection, consequently resulting in a potential impairment of the reliability of model simulations and predictions and in a lack of the overall understanding of WNV spread. Further investigations are thus needed to better understand these aspects, but field studies, especially those involving several wild species, such as in the case of WNV, can be challenging. Thus, it becomes crucial to identify which transmission processes most influence the dynamics of WNV. In the present work, we propose a sensitivity analysis to investigate which of the selected epidemiological parameters of WNV have the largest impact on the spread of the infection. Based on a mathematical model simulating WNV spread into the Lombardy region (northern Italy), the basic reproduction number of the infection was estimated and used to quantify infection spread into mosquitoes and birds. Then, we quantified how variations in four epidemiological parameters representing the duration of the infectious period in birds, the mosquito biting rate on birds, and the competence and susceptibility to infection of different bird species might affect WNV transmission. Our study highlights that knowledge gaps in WNV epidemiology affect the precision in several parameters. Although all investigated parameters affected the spread of WNV and the modelling precision, the duration of the infectious period in birds and mosquito biting rate are the most impactful, pointing out the need of focusing future studies on a better estimate of these parameters at first. In addition, our study suggests that a WNV outbreak is very likely to occur in all areas with suitable temperatures, highlighting the wide area where WNV represents a serious risk for public health.

Patterns of West Nile Virus in the Northeastern United States Using Negative Binomial and Mechanistic Trait-Based Models

West Nile virus (WNV) primarily infects birds and mosquitoes but has also caused over 2,000 human deaths, and >50,000 reported human cases in the United States. Expected numbers of WNV neuroinvasive cases for the present were described for the Northeastern United States, using a negative binomial model. Changes in temperature-based suitability for WNV due to climate change were examined for the next decade using a temperature-trait model. WNV suitability was generally expected to increase over the next decade due to changes in temperature, but the changes in suitability were generally small. Many, but not all, populous counties in the northeast are already near peak suitability. Several years in a row of low case numbers is consistent with a negative binomial, and should not be interpreted as a change in disease dynamics. Public health budgets need to be prepared for the expected infrequent years with higher-than-average cases. Low-population counties that have not yet had a case are expected to have similar probabilities of having a new case as nearby low-population counties with cases, as these absences are consistent with a single statistical distribution and random chance.

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).

Statistical Tools for West Nile Virus Disease Analysis

West Nile virus (WNV) is the most widespread arbovirus in the world and endemic to much of the United States. Its range continues to expand as land use patterns change, creating more habitable environments for the mosquito vector. Though WNV is endemic, the year-to-year risk is highly variable, thus making it difficult to understand the risk for human spillover events. Abatement districts monitor for infected mosquitoes to help understand these potential risks and to help guide our understanding of the risk posed by these observed infected mosquitoes. Creating optimal monitoring networks will provide more informed decision-making tools for abatement districts and policy makers. Investment in these monitoring networks that capture robust observations on mosquito infection rates will allow for environmentally informed inference systems to help guide decision-making and WNV risk. In turn, enhanced decision-making tools allow for faster response times of more targeted and economical surveillance and mosquito population reduction efforts and the overall reduction of WNV transmission. Here we discuss the data streams, their processing, and specifically three ways to calculate WNV infection rates in mosquitoes.

Decoding the Role of Temperature in RNA Virus Infections

RNA viruses include respiratory viruses, such as coronaviruses and influenza viruses, as well as vector-borne viruses, like dengue and West Nile virus. RNA viruses like these encounter various environments when they copy themselves and spread from cell to cell or host to host. Ex vivo differences, such as geographical location and humidity, affect their stability and transmission, while in vivo differences, such as pH and host gene expression, impact viral receptor binding, viral replication, and the host immune response against the viral infection. A critical factor affecting RNA viruses both ex vivo and in vivo, and defining the outcome of viral infections and the direction of viral evolution, is temperature. In this minireview, we discuss the impact of temperature on viral replication, stability, transmission, and adaptation, as well as the host innate immune response. Improving our understanding of how RNA viruses function, survive, and spread at different temperatures will improve our models of viral replication and transmission risk analyses.