The burden of climate-sensitive, mosquito-borne diseases, including dengue, has significantly increased in recent years. Understanding the temporal and spatial variations of these diseases is essential for effectively controlling potential outbreaks. In this study, we utilized Moderate Resolution Imaging Spectroradiometer (MODIS) satellite land surface temperature (LST) data (MOD11A2) and a temperature-dependent mechanistic model (R0) to predict the monthly suitability for dengue transmission in Nepal from 2001 to 2020 for both mosquito vectors, Aedes aegypti and Ae. albopictus. We divided the study period into two episodes: 2001-2010, which we characterized as the period of dengue emergence, and 2011-2020, identified as the period of rapid expansion. We compared the thermal suitability across these two time periods. The results indicated that approximately half of Nepal is thermally suitable for dengue transmission for at least one month, with the maximum transmission risk lasting up to nine months each year, a trend that has more or less remained stable over the past 20 years. However, strong temporal dynamics were observed in the hilly regions and around major urban centers such as Kathmandu and Pokhara, where the length of thermal suitability extended up to six months for both vector species. Consequently, the population exposed to thermal suitability increased significantly on a monthly basis. Compared to the emergence period, the proportion of the population exposed to a suitable thermal environment for six months or longer each year increased by 18% for Ae. aegypti and 20% for Ae. albopictus. These findings provide evidence-based insights that could assist health authorities in the control and management of dengue in Nepal.

The incidence of arboviral diseases like dengue, chikungunya, and yellow fever continues to rise in association with the expanding geographic ranges of their vectors, Aedes aegypti and Aedes albopictus. The distribution of these vectors is believed to be driven in part by climate change and increasing urbanization. Arboviruses navigate a wide range of temperatures as they transition from ectothermic vectors (from 15°C to 35°C) to humans (37°C) and back again, but the role that temperature plays in driving the evolution of arboviruses remains largely unknown. Here, we passaged replicate dengue serotype-2 virus populations 10 times at either 26°C (Low) or 37°C (High) in C6/36 Aedes albopictus cells to explore the differences in adaptation to these thermal environments. We then deep-sequenced the resulting passaged dengue virus populations and tested their replicative fitness in an all-cross temperature regime. We also assessed the ability of the passaged viruses to replicate in the insect vector. While viruses from both thermal regimes accumulated substitutions, only those reared in the 37°C treatments exhibited nonsynonymous changes, including several in the E, or envelope protein, and multiple non-structural genes. Passaging at the higher temperature also led to reduced replicative ability at 26°C in both cells and mosquitoes. One of the mutations in the E gene involved the loss of a glycosylation site previously shown to reduce infectivity in the vector. These findings suggest that viruses selected for growth at higher ambient temperatures may experience tradeoffs between thermostability and replication in the vector. Such associations might also have implications for the suitability of virus transmission under a changing climate.

Dengue virus, one of the most prevalent mosquito-borne flaviviruses affecting humans globally, is primarily transmitted by the Aedes aegypti mosquito, which thrives in densely populated urban environments. Dengue incidence has surged in recent decades, becoming a major public health concern in many regions, particularly in Brazil, which has experienced recurrent outbreaks and reported over 6.6 million probable cases in the year of 2024. While the link between the mosquito vector and dengue transmission is well understood, the effects of different DENV types and their interactions with the vector capacity of natural mosquito populations are crucial for understanding disease dynamics. Here we report findings from experiments designed to analyze and compare the infectivity and dissemination of the DENV-1 strain among five Ae. aegypti populations collected from different regions of Brazil. When exposed to DENV-infected AG129 mice for blood feeding, these populations exhibited variations in infection rates and dissemination efficiency. Eight days post-infection, all populations demonstrated high infection rates, underscoring the substantial capacity of Brazilian Ae. aegypti populations to support the locally circulating DENV-1 strain. Our results demonstrate variation in Ae. aegypti vector competence across Brazil, revealing distinct patterns of DENV transmission efficiency. These findings highlight the necessity for geographically tailored control strategies, particularly in high-risk urban areas where outbreak potential is greatest.

Temperature shapes the geographic distribution, seasonality, and magnitude of mosquito-borne disease outbreaks. Models predicting transmission often use mosquito and pathogen thermal responses measured at constant temperatures. However, mosquitoes live in fluctuating temperatures. Rate summation--non-linear averaging of trait values measured at constant temperatures-is commonly used to infer performance in fluctuating environments, but its accuracy is rarely validated. We measured three traits that impact transmission-bite rate, survival, fecundity-in a malaria mosquito (Anopheles stephensi) across three diurnal temperature ranges (0, 9, and 12 °C). We compared transmission thermal suitability models with temperature-trait relationships observed under constant temperatures, fluctuating temperatures, and those predicted by rate summation. We mapped results across An. stephenesi's native Asian and invasive African ranges. We found: 1) daily temperature fluctuation trait values substantially differ from both constant temperature experiments and rate summation; 2) rate summation partially captured decreases in performance near thermal optima, yet incorrectly predicted increases near thermal limits; and 3) while thermal suitability across constant temperatures did not perfectly capture fluctuating environments, it was better than rate summation for estimating and mapping thermal limits. Our study provides insight into methods for predicting mosquito-borne disease risk and emphasizes the need to improve understanding of organismal performance under fluctuating conditions.

Urbanization can influence disease vectors by altering larval habitat, microclimates, and host abundance. The global increase in urbanization, especially in Africa, is likely to alter vector abundance and pathogen transmission. We investigated the effect of urbanization and weather on the abundance of two mosquitoes, Aedes aegypti and Aedes albopictus, and infection with dengue, chikungunya, and Zika viruses at 63 sites in six cities spanning a 900-km latitudinal range in Cameroon, Central Africa.

We used human landing catches and backpack-mounted aspirators to sample mosquitoes and collected larval habitat, host availability, and weather (temperature, precipitation, humidity) data for each site in each city. We analyzed land use and land cover information and satellite photos at varying radii around sites (100 m to 2 km) to quantify the extent of urbanization and the number of structures around each site. We used a continuous urbanization index (UI; range 0-100) that increased with impermeable surface and decreased with forest cover.

Urbanization increased larval habitat, human host availability, and Ae. aegypti mosquito abundance. Aedes aegypti abundance increased 1.7% (95% CI 0.69-2.7%) with each 1 unit increase in the urbanization index in all six cities (Douala, Kribi, Yaounde, Ngaoundere, Garoua, and Maroua) with a 5.4-fold increase from UI = 0 to UI = 100, and also increased with rainfall. In contrast, Ae. albopictus abundance increased with urbanization in one city, but showed no influence of urbanization in two other cites. Across three cities, Ae. albopictus abundance increased with rainfall, temperature, and humidity. Finally, we did not detect Zika, dengue, or chikungunya viruses in any specimens, and found weak evidence of interspecific competition in analyses of adult population growth rates.

These results show that urbanization consistently increases Ae. aegypti abundance across a broad range of habitats in Central Africa, while effects on Ae. albopictus were more variable and the abundance of both species were influenced by rainfall. Future urbanization of Africa will likely increase Ae. aegypti abundance, and climate change will likely alter abundance of both species through changes in precipitation and temperature.

The complex relationship between temperature and schistosomiasis, an environmentally mediated neglected tropical disease affecting 250 million people globally, with hyperendemicity mostly in Africa, is poorly characterized. Here, we explored how seasonal temperature fluctuation affects the persistence, dynamics, and geographic distribution of schistosomiasis in Africa. We used a temperature-sensitive, mechanistic model of schistosomiasis dynamics that accounts for the adaptive behaviors of intermediate snail hosts and derived the disease's thermal response curve for different patterns of seasonal temperature fluctuations. Changing the amplitude of seasonal temperature fluctuations can influence both the thermal optimum and critical thermal thresholds which imply accurately drawing the thermal response curves requires accounting for seasonality in addition to mean annual temperature. Moreover, our simulations can reproduce the documented persistence of schistosomiasis at locations with strong seasonal temperature fluctuations and mean annual temperatures near or above the critical thermal maxima for snail hosts only when snail adaptive behavior (e.g., aestivation, movement into cooler depths or shade) is included in the model. These results suggest that future climate change impacting the amplitude and timing of these fluctuations will likely alter the future geographic distribution of schistosomiasis in African regions. Our work demonstrates that a comprehensive understanding of schistosomiasis and, potentially, other environmentally mediated diseases in Africa, necessitates the inclusion of seasonal temperature fluctuations and host behavioral adaptations in process-based mechanistic models.

Climate change is profoundly reshaping the behavior, physiology, and distribution of insect vectors, with significant implications for vector-borne disease transmission. Rising temperatures, shifting precipitation patterns, and extreme weather events are driving behavioral adaptations such as altered host-seeking patterns, modified resting site preferences, and extended seasonal activity. Concurrently, vectors exhibit physiological plasticity, including enhanced thermal tolerance, desiccation resistance, and accelerated reproductive cycles, which contribute to increased survival and vector competence. This review synthesizes current research on climate-driven adaptations in major disease vectors, focusing on their epidemiological consequences and implications for public health interventions. A systematic literature review was conducted using major scientific databases to assess the impact of climate change on insect vector adaptation. Studies examining temperature-induced behavioral shifts, physiological modifications, and changes in vector competence were analyzed to identify emerging trends and knowledge gaps. Findings indicate that climate-driven vector adaptations are increasing the efficiency of disease transmission, enabling the geographic expansion of vector populations and prolonging transmission seasons. These changes challenge existing vector control strategies, necessitating innovative approaches such as genetic engineering, microbiome-based interventions, and climate-informed surveillance systems. Given the accelerating impact of climate change, there is an urgent need for adaptive, evidence-based control strategies to mitigate the growing threat of vector-borne diseases and enhance global health resilience.

West Nile virus (WNV), the most common mosquito-borne disease in the continental U.S., is vectored by Culex spp. mosquitoes. Since its introduction to New York State (NYS) in 1999, WNV has become endemic. NYS temperatures have risen by 0.14°C per decade since 1900, with larger increases linked to higher WNV transmission. Using surveillance and sequencing data, we find a significant correlation between rising temperatures, increased WNV genetic diversity, and higher prevalence. Given the experimentally demonstrated role of temperature influencing WNV fitness, we hypothesized that contemporary strains should exhibit greater fitness in mosquitoes at higher temperatures compared to historic strains. To test this, we analyzed genetically distinct WNV strains from mosquitoes collected during recent warm summers (2017 and 2018) and cooler historic summers (2003 and 2004). Assessing Culex pipiens vector competence and calculating the relative R₀ at 20°C, 24°C, and 28°C, we found that contemporary strains exhibit higher transmission potential at increased temperatures. Our results show that contemporary WNV strains possess greater phenotypic and genotypic diversity, facilitating the emergence of strains with enhanced transmission potential in a warming climate.

Temperature influences the transmission of mosquito-borne pathogens with significant implications for disease risk under climate change. Mathematical models of mosquito-borne infections rely on functions that capture mosquito-pathogen interactions in response to temperature to accurately estimate transmission dynamics. For deriving these functions, experimental studies provide valuable data on the temperature sensitivity of mosquito life-history traits and pathogen transmission. However, the scarcity of experimental data and inconsistencies in methodologies for analysing temperature responses across mosquito species, pathogens, and experiments present major challenges. Here, we introduce a new approach to address these challenges. We apply this framework to study the thermal biology of West Nile virus (WNV). We reviewed existing experimental studies, obtaining temperature responses for eight mosquito-pathogen traits across 15 mosquito species. Using these data, we employed Bayesian hierarchical models to estimate temperature response functions for each trait and their variation between species and experiments. We incorporated the resulting functions into mathematical models to estimate the temperature sensitivity of WNV transmission, focusing on six mosquito species of the genus Culex. Our study finds a general optimal transmission temperature around 24°C among Culex species with only small species-specific deviations. We demonstrate that differing mechanistic assumptions underlying published mosquito population models result in temperature optima estimates that differ by up to 3°C. Additionally, we find substantial variability between trait temperature responses across experiments on the same species, possibly indicating significant intra-species variation in trait performance. We identify mosquito biting rate, lifespan, and egg viability as priorities for future experiments, as they strongly influence estimates of temperature limits, optima, and overall uncertainty in transmission suitability. Experimental studies on vector competence traits are also essential, because limited data on these currently require model simplifications. These data would enhance the accuracy of our estimates, critical for anticipating future shifts in WNV risk under climate change.

The complex immune interactions produced by the tetravalent dengue vaccine Dengvaxia have foregrounded the important role of antibody-dependent enhancement (ADE) in dengue infection. Some evidence exists that ADE may extend beyond the four dengue serotypes to Zika, a closely related flavivirus transmitted by the same mosquito species as dengue, and may also account for the increased severity of some cases. Estimates of the public health impact of dengue vaccination may then need to include its effects on the transmission of Zika in addition to dengue. This study gathers primary references to build estimates of per-case economic cost and disease burden for dengue and Zika infection with and without ADE in the ten countries where clinical trials were held for Dengvaxia, under the hypothesis that severe outcomes are associated with ADE of disease. From these estimates, per-infection weighted averages are developed (without assumptions on transmission dynamics or case totals) which will facilitate population-level estimates of the potential impact of dengue vaccination on a dual outbreak using mathematical modeling. Results estimate that ADE amplifies the per-case toll of dengue by a factor of 2-16 but increases that of a Zika case by more than two orders of magnitude due to the greater risk of severe consequences. As expected, dengue vaccination affects per-infection dengue toll much more when high prior dengue seropositivity involves a different serotype than the one(s) circulating, but that same high dengue seropositivity makes vaccination exacerbate Zika toll less.

Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic disease within the genus Phlebovirus. Symptoms of the disease in animals range from moderate to severe febrile illness, which significantly impacts the livestock industry and causes severe health complications in humans. Similar to bunyaviruses in the genus Orthobunyavirus transmitted by mosquitoes, RVFV progression is dependent on the susceptibility of the physical, cellular, microbial, and immune response barriers of the vectors. These barriers, shaped by the genetic makeup of the mosquito species and the surrounding environmental temperature, exert strong selective pressure on the virus, affecting its replication, evolution, and spread. The changing climate coupled with the aforementioned bottlenecks are significant drivers of RVF epidemics and expansion into previously nonendemic areas. Despite the link between microclimatic changes and RVF outbreaks, there is still a dearth of knowledge on how these temperature effects impact RVF transmission and vector competence and virus persistence during interepidemic years. This intricate interdependence between the virus, larval habitat temperatures, and vector competence necessitates increased efforts in addressing RVFV disease burden. This review highlights recent advancements made in response to shifting demographics, weather patterns, and conveyance of RVFV. Additionally, ongoing studies related to temperature-sensitive variations in RVFV-vector interactions and knowledge gaps are discussed.

 This study examines the geographic distribution, temporal trends, and syndemic interactions between dengue and chikungunya outbreaks in India from 2014 to 2023, using data from the Integrated Disease Surveillance Programme (IDSP). Understanding trends offers critical insights to enhance public health responses to co-occurring vector-borne diseases.

 The study analyzes the trends, geographic distribution, and syndemic interactions between dengue and chikungunya. It highlights patterns, high-burden areas, and seasonal dynamics to inform public health interventions for mitigating the dual burden.

 This secondary data analysis used IDSP records from January 2014 to December 2023. Temporal trends in outbreaks were analyzed, and districts were categorized by severity through spatial mapping and bivariate analysis, employing statistical quartiles to assess the co-occurrence and syndemic nature of dengue and chikungunya.

 Dengue outbreaks increased significantly from 2014 to 2017, peaking at 175 outbreaks, followed by fluctuations until a peak of 200 outbreaks in 2023. In contrast, chikungunya outbreaks peaked in 2017 at 77 outbreaks and subsequently declined to 19 outbreaks by 2023. Geographic analysis indicated a high dengue burden in districts such as East Siang (Arunachal Pradesh), Birbhum (West Bengal), and Pune (Maharashtra), while chikungunya was most severe in Thanjavur, Theni, and Vellore (Tamil Nadu). A bivariate choropleth analysis identified regions with significant syndemic, such as Pune (Maharashtra), Tumkur (Karnataka), and Kamrup (Assam), which were classified as high-high. Additional districts such as Sangli and Satara (Maharashtra) were categorized as high-moderate, while Puducherry and Junagadh (Gujarat) were noted as moderate-high for dengue and chikungunya, respectively.

 The findings underscore significant variability in dengue and chikungunya syndemic across India, highlighting regions with severe dual burden. Enhanced surveillance for close watch on syndemic occurrence and its impact needs to be studied, which is essential to reduce both the incidence and study its compounded public health impacts.

The microbiome influences critical aspects of mosquito biology and variations in microbial composition can impact the outcomes of laboratory studies. To investigate how biotic and abiotic conditions in an insectary affect the composition of the mosquito microbiome, a single cohort of Aedes aegypti eggs was divided into three batches and transferred to three different climate-controlled insectaries within the Liverpool School of Tropical Medicine. The bacterial microbiome composition was compared as mosquitoes developed, the microbiome of the mosquitoes' food sources was characterised, environmental conditions over time in each insectary were measured, and mosquito development and survival were recorded. While developmental success was similar across all three insectaries, differences in microbiome composition were observed between mosquitoes from each insectary. Environmental conditions and bacterial input via food sources varied between insectaries, potentially contributing to the observed differences in microbiome composition. At both adult and larval stages, specific members of the mosquito microbiome were associated with particular insectaries; the insectary with less stable and cooler conditions resulted in a slower pupation rate and higher diversity of the larval microbiome. These findings underscore that even minor inconsistencies in rearing conditions can affect the composition of the mosquito microbiome, which may influence experimental outcomes.

Dengue fever (DF) has become a major public health concern in Nepal, with increasing outbreaks in recent years. Transmitted by Aedes mosquitoes, this climate-sensitive viral disease presents a significant challenge for healthcare providers and policymakers. Since 2004, Nepal has experienced a sharp increase in DF cases, peaking in 2022 with 54784 cases and 88 deaths. The surge, driven mainly by serotypes 1, 2, and 3, is exacerbated by climate change, which prolongs mosquito breeding seasons due to warmer temperatures and increased rainfall. This trend has even impacted previously unaffected hilly regions. Effective dengue control strategies must focus on climate change adaptation, strengthening healthcare system reinforcement, raising public awareness, and enhancing vector control measures. Government initiatives, like the national dengue control program, play a critical role, but research and community engagement are also vital for prevention and early detection. Integrating climate resilience into public health efforts is essential to reducing the dengue burden in Nepal.

Aedes aegypti are indoor-dwelling vectors of many arboviruses, including Zika (ZIKV) and chikungunya (CHIKV). The dynamics of these viruses within the mosquito are known to be temperature-dependent, and models that address risk and predictions of the transmission efficiency and patterns typically use meteorological temperature data. These data do not differentiate the temperatures experienced by mosquitoes in different microclimates, such as indoor vs. outdoor. Using temperature data collected from Neiva Colombia, we investigated the impact of two microclimate temperature profiles on ZIKV and CHIKV infection dynamics in Ae. aegypti. We found that the vector mortality was not significantly impacted by the difference in temperature profiles. Further, we found that the infection and dissemination rates were largely unaffected, with only ZIKV experiencing a significant increase in infection at outdoor temperatures at 21 days post-infection (dpi). Further, there was a significant increase in viral titers in the abdomens of ZIKV-infected mosquitoes at 21 dpi. With CHIKV, there was a significant titer difference in the abdomens of mosquitoes at both 7 and 14 dpi. While there were differences in vector infection kinetics that were not statistically significant, we developed a simple stochastic SEIR-SEI model to determine if the observed differences might translate to notable differences in simulated outbreaks. With ZIKV, while the probability of secondary transmission was high (>90%) under both microenvironmental scenarios, there was often only one secondary case. However, CHIKV differences between microenvironments were more prominent. With over 90% probability of secondary transmission, at indoor conditions, the peak of transmission was higher (over 850 cases) compared to the outdoor conditions (<350 cases). Further, the time-to-peak for indoor was 130 days compared to 217 days for outdoor scenarios. Further investigations into microenvironmental conditions, including temperature, may be key to increasing our understanding of the nuances of CHIKV and ZIKV vectorial capacity, epidemiology, and risk assessment, especially as it affects other aspects of transmission, such as biting rate. Overall, it is critical to understand the variability of how extrinsic factors affect transmission systems, and these data add to the growing catalog of knowledge of how temperature affects arboviral systems.

The incidence of human infections caused by arthropod-borne viruses, such as the chikungunya virus (CHIKV), has increased globally due to a number of factors, such as climate change and globalization. The exotic mosquito species Aedes albopictus is a significant vector for CHIKV, raising concerns about its transmission potential in temperate regions, including Central Europe. We have therefore investigated the vector competence of Ae. albopictus for CHIKV at constant and fluctuating temperatures between 15 °C and 24 °C to assess the transmission risk in Europe.

Aedes albopictus mosquitoes were reared and artificially infected with CHIKV. Infection rates and transmission efficiencies (TEs) were determined after 14 days of incubation at constant and fluctuating (± 5 °C) mean temperatures of 15 °C, 18 °C, 21 °C and 24 °C. In addition, mosquito locomotor activity was measured under the same fluctuating temperature conditions. A risk map for CHIKV transmission in Europe was generated combining temperature data and the current distribution of Ae. albopictus.

CHIKV transmission was observed at all tested temperatures. The highest TEs were recorded at fluctuating temperatures of 18 °C (54.3%) and 21 °C (58.6%), while the lowest TE was observed at a constant temperature of 15 °C (5.6%). TEs at fluctuating temperatures of 15 °C and 24 °C were the same (32.5%). Mosquito activity showed a nocturnal unimodal activity pattern with a peak during the start of the scotophase (hour 20). The proportion of active mosquitoes per hour increased with temperature and was nearly zero at 15 °C. The risk map indicated that regions in Southern and Central Europe, including recently invaded areas north of the Alps, have temperatures theoretically allowing CHIKV transmission for at least some days per year.

While CHIKV can be transmitted by Ae. albopictus at 15 °C, the activity of this mosquito is strongly decreased at this temperature, likely reducing the transmission risk. These findings emphasize the importance of considering both vector competence and mosquito activity when assessing the risk of arbovirus transmission in temperate regions. Further studies are needed to validate these laboratory findings under field conditions.

Dengue fever is a mosquito-transmitted disease of great public health importance. Dengue lacks adequate vaccine protection and insecticide-based methods of mosquito control are proving increasingly ineffective. Here we review the emerging use of mosquitoes transinfected with the obligate intracellular bacterium Wolbachia pipientis for vector control. Wolbachia often induces cytoplasmic incompatibility in its mosquito hosts, resulting in infertile progeny between an infected male and an uninfected female. Wolbachia infection also suppresses the replication of pathogens in the mosquito, a process known as "pathogen blocking". Two strategies have emerged. The first one releases Wolbachia carriers (both male and female) to replace the wild mosquito population, a process driven by cytoplasmic incompatibility and that becomes irreversible once a threshold is reached. This suppresses disease transmission mainly by pathogen blocking and frequently requires a single intervention. The second strategy floods the field population with an exclusively male population of Wolbachia-carrying mosquitoes to generate infertile hybrid progeny. In this case, transmission suppression depends largely on decreasing the population density of mosquitoes driven by infertility and requires continued mosquito release. The efficacy of both Wolbachia-based approaches has been conclusively demonstrated by randomized and non-randomized studies of deployments across the world. However, results conducted in one setting cannot be directly or easily extrapolated to other settings because dengue incidence is highly affected by the conditions into which the mosquitoes are released. Compared to traditional vector control methods, Wolbachia-based approaches are much more environmentally friendly and can be effective in the medium/long term. On the flip side, they are much more complex and cost-intensive operations, requiring a substantial investment, infrastructure, trained personnel, coordination between agencies, and community engagement. Finally, we discuss recent evidence suggesting that the release of Wolbachia-transinfected mosquitoes has a moderate potential risk of spreading potentially dangerous genes in the environment.

Dengue fever is one of the most prevalent mosquito-borne diseases in Cambodia. Until now, no specific vaccine nor antiviral treatment exists the virus causing Dengue fever. Consequently, its prevention relies only on vector control strategies. However, efficient vector control in turn relies on a good knowledge of the biology of the vector species. Therefore, this study aims to provide the first review of the distribution, ecology, meteorological impacts, trophic behavior, vector competence, vector control and insecticide resistance of dengue vector species in Cambodia.

A systematic search of the Google Scholar and PubMed databases was conducted for relevant published articles. Of the 610 published articles originally identified, 70 articles were ultimately selected for inclusion in this review. We also included new data from unpublished research conducted in Cambodia between 2017 and 2023 related to dengue vector bionomics.

Eleven Aedes (Stegomyia) mosquito species have been recorded in Cambodia, including a new species described in 2024. Four species are associated with dengue virus transmission, among which Aedes aegypti and Ae. albopictus are the main vectors and Ae. malayensis and Ae. scutellaris are considered to be potential vectors. Aedes aegypti and Ae. albopictus are present in all provinces of Cambodia. Aedes albopictus shows a preference for forest, rural and suburban areas, while Ae. aegypti is mostly found in urban and suburban areas. The distribution of these two species is also influenced by meteorological factors, seasonality and the availability of breeding habitats and blood meals. Both species are predominant during the rainy season, and their respective density is impacted by precipitation and temperature. Aedes aegypti is characterized as anthropophilic, while Ae. albopictus exhibits zooanthropophilic behavior, and both species have been observed to be predominantly diurnal. In addition, they were found to be highly resistant to the insecticides used in Cambodia for their control, such as temephos for larvae and deltamethrin and permethrin for adult mosquitoes.

This review provides extensive and important knowledge on dengue vectors in Cambodia. This knowledge is derived not only from published research articles but also from many recent studies in Cambodia on the bionomics of dengue vector species. The review provides valuable information for use by public health authorities on dengue virus transmission and to develop better vector control strategies in the country.

Temperature influences nearly every aspect of organismal function. Because aspects of global change such as urbanization and climate change influence temperature, researchers must consider how altering thermal regimes will impact biodiversity across the planet. To do so, they often measure temperature in natural and/or human-modified habitats, replicate those temperatures in laboratory experiments to understand organismal responses, and make predictions under models of future change. Consequently, accurately representing temperature in the laboratory is an important concern, yet few studies have assessed the consequences of simulating thermal conditions in different ways. We used nest temperatures for two urban-dwelling, invasive lizards (Anolis sagrei and A. cristatellus) to create two egg incubation treatments in the laboratory. Like most studies of thermal developmental plasticity, we created daily repeating thermal fluctuations; however, we used different methods to create temperature treatments that differed in the magnitude and breadth of thermal cycles, and then evaluated the effects of these different approaches on embryo development and hatchling phenotypes. Additionally, we measured embryo heart rate, a proxy for metabolism, across temperature to understand the immediate effects of treatments. We found that treatments had minimal effect on phenotypes likely because temperatures were within the optimal thermal range for each species and were similar in mean temperature. We conclude that slight differences in thermal treatments may be unimportant so long as temperatures are within a range appropriate for development, and we make several recommendations for future studies of developmental plasticity.

Dengue is a vector-borne viral infection caused by the dengue virus transmitted to humans primarily by Aedes aegypti. The year 2024 has been a historic year for dengue in Brazil, with the highest number of probable cases ever registered. Herein, we analyze the temporal trend and spatio-temporal dynamics of dengue cases in Brazil during the first nine epidemiological weeks (EW) of 2024.

This is an ecological study, including all probable cases of dengue in Brazil during the period, carried out in two steps: time series analysis to assess the temporal trend and spatial analysis to identify high-risk clusters.

1,345,801 probable cases of dengue were reported. The regions with the highest increasing trend were the Northeast with an average epidemiologic week percent change (AEPC) of 52.4 (95% CI: 45.5-59.7; p < 0.001) and the South with 35.9 (95% CI: 27.7-44.5; p < 0.001). There was a statistically significant increasing trend in all states, except Acre (AEPC = -4.1; 95% CI: -16.3-10; p = 0.55), Amapá (AEPC = 1.3; 95% CI: -16.2-22.3; p = 0.9) and Espírito Santo (AEPC = 8.9; 95% CI: -15.7-40.6; p = 0.5). The retrospective space-time analysis showed a cluster within the Northeast, Central-West and Southeast regions, with a radius of 515.3 km, in which 1,267 municipalities and 525,324 of the cases were concentrated (RR = 6.3; p < 0.001). Regarding the spatial variation of the temporal trend, 21 risk areas were found, all of them located in Southeast or Central-West states. The area with the highest relative risk was Minas Gerais state, where 5,748 cases were concentrated (RR = 8.1; p < 0.001). Finally, a purely spatial analysis revealed 25 clusters, the one with the highest relative risk being composed of two municipalities in Acre (RR = 6.9; p < 0.001).

We described a detailed temporal-spatial analysis of dengue cases in the first EWs of 2024 in Brazil, which were mainly concentrated in the Southeast and Central-West regions. Overall, it is recommended that governments adopt public policies to control the the vector population in high-risk areas, as well as to prevent the spread of dengue fever to other areas of Brazil.

Aedes aegypti, the vector for dengue, chikungunya, yellow fever, and Zika, poses a growing global epidemiological risk. Despite extensive research on Ae. aegypti's life history traits and behavior, critical knowledge gaps persist, particularly in integrating these findings across varied experimental contexts. The plasticity of Ae. aegypti's traits throughout its life cycle allows dynamic responses to environmental changes, yet understanding these variations within heterogeneous study designs remains challenging. A critical aspect often overlooked is the impact of using lab-adapted lines of Ae. aegypti, which may have evolved under laboratory conditions, potentially altering their life history traits and behavioral responses compared to wild populations. Therefore, incorporating field-derived populations in experimental designs is essential to capture the natural variability and adaptability of Ae. aegypti. The relationship between larval growing conditions and adult traits and behavior is significantly influenced by the specific context in which mosquitoes are studied. Laboratory conditions may not replicate the ecological complexities faced by wild populations, leading to discrepancies in observed traits and behavior. These discrepancies highlight the need for ecologically relevant experimental conditions, allowing mosquito traits and behavior to reflect field distributions. One effective approach is semi-field studies involving field-collected mosquitoes housed for fewer generations in the lab under ecologically relevant conditions. This growing trend provides researchers with the desired control over experimental conditions while maintaining the genetic diversity of field populations. By focusing on variations in life history traits and behavioral plasticity within these varied contexts, this review highlights the intricate relationship between larval growing conditions and adult traits and behavior. It underscores the significance of transstadial effects and the necessity of adopting study designs and reporting practices that acknowledge plasticity in adult traits and behavior, considering variations due to larval rearing conditions. Embracing such approaches paves the way for a comprehensive understanding of contextual variations in mosquito life history traits and behavior. This integrated perspective enables the synthesis of research findings across laboratory, semi-field, and field-based investigations, which is crucial for devising targeted intervention strategies tailored to specific ecological contexts to combat the health threat posed by this formidable disease vector effectively.

Temperature shapes the distribution, seasonality, and magnitude of mosquito-borne disease outbreaks. Mechanistic models predicting transmission often use mosquito and pathogen thermal responses from constant temperature experiments. However, mosquitoes live in fluctuating environments. Rate summation (nonlinear averaging) is a common approach to infer performance in fluctuating environments, but its accuracy is rarely validated. We measured three mosquito traits that impact transmission (bite rate, survival, fecundity) in a malaria mosquito (Anopheles stephensi) across temperature gradients with three diurnal temperature ranges (0, 9 and 12°C). We compared thermal suitability models with temperature-trait relationships observed under constant temperatures, fluctuating temperatures, and those predicted by rate summation. We mapped results across An. stephenesi's native Asian and invasive African ranges. We found: 1) daily temperature fluctuation significantly altered trait thermal responses; 2) rate summation partially captured decreases in performance near thermal optima, but also incorrectly predicted increases near thermal limits; and 3) while thermal suitability characterized across constant temperatures did not perfectly capture suitability in fluctuating environments, it was more accurate for estimating and mapping thermal limits than predictions from rate summation. Our study provides insight into methods for predicting mosquito-borne disease risk and emphasizes the need to improve understanding of organismal performance under fluctuating conditions.

For decades, dengue has posed a significant threat as a viral infectious disease, affecting numerous human lives globally, particularly in tropical regions, yet no cure has been discovered. The genetic trait of vector competence in Aedes mosquitoes, which facilitates dengue transmission, is difficult to measure and highly sensitive to environmental changes.

In this study we attempt, for the first time in a non-laboratory setting, to quantify the vector competence of Aedes mosquitoes assuming its homogeneity across both species; aegypti and albopictus and across the four Dengue serotypes. Estimating vector competence in relation to varying rainfall patterns was focused in this study to showcase the changes in this vector trait with respect to environmental variables. We quantify it using an existing mathematical model originally developed for malaria in a Bayesian inferencing setup. We conducted this study in the Colombo district of Sri Lanka where the highest number of human populations are threatened with dengue. Colombo district experiences continuous favorable temperature and humidity levels throughout the year creating ideal conditions for Aedes mosquitoes to thrive and transmit the Dengue disease. Therefore we only used the highly variable and seasonal rainfall as the primary environmental variable as it significantly influences the number of breeding sites and thereby impacting the population dynamics of Aedes.

Our research successfully deduced vector competence values for the four identified seasons based on Monsoon rainfalls experienced in Colombo within a year. We used dengue data from 2009 - 2022 to infer the estimates. These estimated values have been corroborated through experimental studies documented in the literature, thereby validating the malaria model to estimate vector competence for dengue disease.

Our research findings conclude that environmental conditions can amplify vector competence within specific seasons, categorized by their environmental attributes. Additionally, the deduced vector competence offers compelling evidence that it impacts disease transmission, irrespective of geographical location, climate, or environmental factors.

System Dynamics (SD) models have been used to understand complex, multi-faceted dengue transmission dynamics, but a gap persists between research and actionable public health tools for decision-making. Spain is an at-risk country of imported dengue outbreaks, but only qualitative assessments are available to guide public health action and control. We propose a modular SD model combining temperature-dependent vector population, transmission parameters, and epidemiological interactions to simulate outbreaks from imported cases accounting for heterogeneous local climate-related transmission patterns. Under our assumptions, 15 provinces sustain vector populations capable of generating outbreaks from imported cases, with heterogeneous risk profiles regarding seasonality, magnitude and risk window shifting from late Spring to early Autum. Results being relative to given vector-to-human populations allow flexibility when translating outcomes between geographic scales. The model and the framework are meant to serve public health by incorporating transmission dynamics and quantitative-qualitative input to the evidence-based decision-making chain. It is a flexible tool that can easily adapt to changing contexts, parametrizations and epidemiological settings thanks to the modular approach.

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.

The microbiome affects important aspects of mosquito biology and differences in microbial composition can affect the outcomes of laboratory studies. To determine how the biotic and abiotic conditions in an insectary affect the composition of the bacterial microbiome of mosquitoes we reared mosquitoes from a single cohort of eggs from one genetically homogeneous inbred Aedes aegypti colony, which were split into three batches, and transferred to each of three different insectaries located within the Liverpool School of Tropical Medicine. Using three replicate trays per insectary, we assessed and compared the bacterial microbiome composition as mosquitoes developed from these eggs. We also characterised the microbiome of the mosquitoes' food sources, measured environmental conditions over time in each climate-controlled insectary, and recorded development and survival of mosquitoes. While mosquito development was overall similar between all three insectaries, we saw differences in microbiome composition between mosquitoes from each insectary. Furthermore, bacterial input via food sources, potentially followed by selective pressure of temperature stability and range, did affect the microbiome composition. At both adult and larval stages, specific members of the mosquito microbiome were associated with particular insectaries; and the insectary with less stable and cooler conditions resulted in slower pupation rate and higher diversity of the larval microbiome. Tray and cage effects were also seen in all insectaries, with different bacterial taxa implicated between insectaries. These results highlight the necessity of considering the variability and effects of different microbiome composition even in experiments carried out in a laboratory environment starting with eggs from one batch; and highlights the impact of even minor inconsistencies in rearing conditions due to variation of temperature and humidity.

Enhanced phytoremediation offers a rapid and eco-friendly approach for cleaning agricultural soil contaminated with copper and cadmium which pose a direct threat to food scarcity and security. The current study aimed to compare the effectiveness of the two commonly used additives, IAA and EDTA, for the remediation of copper (Cu) and cadmium (Cd) contaminated soils using sunflower and maize. The plants were cultivated in pots under controlled conditions with four sets of treatments: control (0), Cu50/Cd50, Cu50/Cd50 + EDTA, and Cu50/Cd50 + IAA. The results showed that Cu50/Cd50 mg/kg drastically compromised the phytoremediation potential of both plants, as evident by reduced shoot and root length, and lower biomass. However, the augmentation of Cu50/Cd50 with EDTA or IAA improved the tested parameters. In sunflower, EDTA enhanced the accumulation of Cu and Cd by 58% and 21%, respectively, and improved plant biomass by 41%, compared to control treatment. However, IAA exhibited higher accumulation of Cu and Cd by 64% and 25%, respectively, and enhanced plant biomass by 43%. In case of maize, IAA was superior to EDTA which enhanced the accumulation of Cu and Cd by 87% and 32% respectively, and increased the plant biomass by 57%, compared to control treatment. Our findings demonstrate that foliar IAA is more effective than EDTA in enhancing the phytoremediation potential of sunflower and maize for Cu and Cd.

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.

Aedes aegypti is an important vector of dengue virus and other arboviruses that affect human health. After being ingested in an infectious bloodmeal, but before being transmitted from mosquito to human, dengue virus must disseminate from the vector midgut into the hemocoel and then the salivary glands. This process, the extrinsic incubation period, typically takes 6-14 days. Since older mosquitoes are responsible for transmission, understanding the age structure of vector populations is important. Transcriptional profiling can facilitate predictions of the age structures of mosquito populations, critical for estimating their potential for pathogen transmission. In this study, we utilized a two-gene transcript model to assess the age structure and daily survival rates of three populations (Key West, Marathon, and Key Largo) of Ae. aegypti from the Florida Keys, United States, where repeated outbreaks of autochthonous dengue transmission have recently occurred. We found that Key Largo had the youngest Ae. aegypti population with the lowest daily survival rate, while Key West had the oldest population and highest survival rate. Across sites, 22.67% of Ae. aegypti females were likely old enough to transmit dengue virus (at least 15 days post emergence). Computed estimates of the daily survival rate (0.8364 using loglinear and 0.8660 using non-linear regression), indicate that dengue vectors in the region experienced relatively low daily mortality. Collectively, our data suggest that Ae. aegypti populations across the Florida Keys harbor large numbers of older individuals, which likely contributes to the high risk of dengue transmission in the area.

Dengue is an increasing health burden that has spread throughout the tropics and sub-tropics. There is currently no effective vaccine and control is only possible through integrated vector management. Early warning systems (EWS) to alert potential dengue outbreaks are currently being explored but despite showing promise are yet to come to fruition. This study addresses the association of meteorological variables with both mosquito indices and dengue incidences and assesses the added value of additionally using mosquito indices for predicting dengue incidences.

Entomological surveys were carried out monthly for 14 months in six sites spread across three environmentally different cities of the Philippines. Meteorological and dengue data were acquired. Non-linear generalized additive models were fitted to test associations of the meteorological variables with both mosquito indices and dengue cases. Rain and the diurnal temperature range (DTR) contributed most to explaining the variation in both mosquito indices and number of dengue cases. DTR and minimum temperature also explained variation in dengue cases occurring one and two months later and may offer potentially useful variables for an EWS. The number of adult mosquitoes did associate with the number of dengue cases, but contributed no additional value to meteorological variables for explaining variation in dengue cases.

The use of meteorological variables to predict future risk of dengue holds promise. The lack of added value of using mosquito indices confirms several previous studies and given the onerous nature of obtaining such information, more effort should be placed on improving meteorological information at a finer scale to evaluate efficacy in early warning of dengue outbreaks.

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.

Aedes aegypti is the primary mosquito vector for several arboviruses, such as dengue, chikungunya and Zika viruses, which cause frequent outbreaks of human disease in tropical and subtropical regions. Control of these outbreaks relies on vector control, commonly in the form of insecticide sprays that target adult female mosquitoes. However, the spatial coverage and frequency of sprays needed to optimize effectiveness are unclear. In this study, we characterize the effect of ultra-low-volume (ULV) indoor spraying of pyrethroid insecticides on Ae. aegypti abundance within households. We also evaluate the effects of spray events during recent time periods or in neighboring households. Improved understanding of the duration and distance of the impact of a spray intervention on Ae. aegypti populations can inform vector control interventions, in addition to modeling efforts that contrast vector control strategies.

This project analyzes data from two large-scale experiments that involved six cycles of indoor pyrethroid spray applications in 2 years in the Amazonian city of Iquitos, Peru. We developed spatial multi-level models to disentangle the reduction in Ae. aegypti abundance that resulted from (i) recent ULV treatment within households and (ii) ULV treatment of adjacent or nearby households. We compared fits of models across a range of candidate weighting schemes for the spray effect, based on different temporal and spatial decay functions to understand lagged ULV effects.

Our results suggested that the reduction of Ae. aegypti in a household was mainly due to spray events occurring within the same household, with no additional effect of sprays that occurred in neighboring households. Effectiveness of a spray intervention should be measured based on time since the most recent spray event, as we found no cumulative effect of sequential sprays. Based on our model, we estimated the spray effect is reduced by 50% approximately 28 days after the spray event.

The reduction of Ae. aegypti in a household was mainly determined by the number of days since the last spray intervention in that same household, highlighting the importance of spray coverage in high-risk areas with a spray frequency determined by local viral transmission dynamics.

The geographical range of schistosomiasis is affected by the ecology of schistosome parasites and their obligate host snails, including their response to temperature. Previous models predicted schistosomiasis' thermal optimum at 21.7°C, which is not compatible with the temperature in sub-Saharan Africa (SSA) regions where schistosomiasis is hyperendemic. We performed an extensive literature search for empirical data on the effect of temperature on physiological and epidemiological parameters regulating the free-living stages of S. mansoni and S. haematobium and their obligate host snails, i.e., Biomphalaria spp. and Bulinus spp., respectively. We derived nonlinear thermal responses fitted on these data to parameterize a mechanistic, process-based model of schistosomiasis. We then re-cast the basic reproduction number and the prevalence of schistosome infection as functions of temperature. We found that the thermal optima for transmission of S. mansoni and S. haematobium range between 23.1-27.3°C and 23.6-27.9°C (95% CI) respectively. We also found that the thermal optimum shifts toward higher temperatures as the human water contact rate increases with temperature. Our findings align with an extensive dataset of schistosomiasis prevalence in SSA. The refined nonlinear thermal-response model developed here suggests a more suitable current climate and a greater risk of increased transmission with future warming for more than half of the schistosomiasis suitable regions with mean annual temperature below the thermal optimum.

The geographical range of schistosomiasis is affected by the ecology of schistosome parasites and their obligate host snails, including their response to temperature. Previous models predicted schistosomiasis' thermal optimum at 21.7 °C, which is not compatible with the temperature in sub-Saharan Africa (SSA) regions where schistosomiasis is hyperendemic. We performed an extensive literature search for empirical data on the effect of temperature on physiological and epidemiological parameters regulating the free-living stages of S. mansoni and S. haematobium and their obligate host snails, i.e., Biomphalaria spp. and Bulinus spp., respectively. We derived nonlinear thermal responses fitted on these data to parameterize a mechanistic, process-based model of schistosomiasis. We then re-cast the basic reproduction number and the prevalence of schistosome infection as functions of temperature. We found that the thermal optima for transmission of S. mansoni and S. haematobium range between 23.1-27.3 °C and 23.6-27.9 °C (95 % CI) respectively. We also found that the thermal optimum shifts toward higher temperatures as the human water contact rate increases with temperature. Our findings align with an extensive dataset of schistosomiasis prevalence in SSA. The refined nonlinear thermal-response model developed here suggests a more suitable current climate and a greater risk of increased transmission with future warming for more than half of the schistosomiasis suitable regions with mean annual temperature below the thermal optimum.

As a primary vector of bluetongue virus (BTV) in the US, seasonal abundance and diel flight activity of Culicoides sonorensis has been documented, but few studies have examined how time of host-seeking activity is impacted by environmental factors. This knowledge is essential for interpreting surveillance data and modeling pathogen transmission risk.

The diel host-seeking activity of C. sonorensis was studied on a California dairy over 3 years using a time-segregated trap baited with CO2. The relationship between environmental variables and diel host-seeking activity (start, peak, and duration of activity) of C. sonorensis was evaluated using multiple linear regression. Fisher's exact test and paired-sample z-test were used to evaluate the seasonal difference and parity difference on diel host-seeking activity.

Host-seeking by C. sonorensis began and reached an activity peak before sunset at a higher frequency during colder months relative to warmer months. The time that host-seeking activity occurred was associated low and high daily temperature as well as wind speed at sunset. Colder temperatures and a greater diurnal temperature range were associated with an earlier peak in host-seeking. Higher wind speeds at sunset were associated with a delayed peak in host-seeking and a shortened duration of host-seeking. Parous midges reached peak host-seeking activity slightly later than nulliparous midges, possibly because of the need for oviposition by gravid females before returning to host-seeking.

This study demonstrates that during colder months C. sonorensis initiates host-seeking and reaches peak host-seeking activity earlier relative to sunset, often even before sunset, compared to warmer months. Therefore, the commonly used UV light-baited traps are ineffective for midge surveillance before sunset. Based on this study, surveillance methods that do not rely on light trapping would provide a more accurate estimate of host-biting risk across seasons. The association of environmental factors to host-seeking shown in this study can be used to improve modeling or prediction of host-seeking activity. This study identified diurnal temperature range as associated with host-seeking activity, suggesting that Culicoides may respond to a rapidly decreasing temperature by shifting to an earlier host-seeking time, though this association needs further study.

In the context of climate change, a growing concern is that vector-pathogen or host-parasite interactions may be correlated with climatic factors, especially increasing temperatures. In the present study, we used a mosquito-microsporidian model to determine the impact of environmental factors such as temperature, humidity, wind and rainfall on the occurrence rates of opportunistic obligate microparasites (Microsporidia) in hosts from a family that includes important disease vectors (Culicidae).

In our study, 3000 adult mosquitoes collected from the field over 3 years were analysed. Mosquitoes and microsporidia were identified using PCR and sequencing of the hypervariable V5 region of the small subunit ribosomal RNA gene and a shortened fragment of the cytochrome c oxidase subunit I gene, respectively.

DNA metabarcoding was used to identify nine mosquito species, all of which were hosts of 12 microsporidian species. The prevalence of microsporidian DNA across all mosquito samples was 34.6%. Microsporidian prevalence in mosquitoes was more frequent during warm months (> 19 °C; humidity < 65%), as was the co-occurrence of two or three microsporidian species in a single host individual. During warm months, microsporidian occurrence was noted 1.6-fold more often than during the cold periods. Among the microsporidians found in the mosquitoes, five (representing the genera Enterocytospora, Vairimorpha and Microsporidium) were positively correlated with an increase in temperature, whereas one (Hazardia sp.) was significantly correlated with a decrease in temperature. Threefold more microsporidian co-occurrences were recorded in the warm months than in the cold months.

These results suggest that the susceptibility of mosquitoes to parasite occurrence is primarily determined by environmental conditions, such as, for example, temperatures > 19 °C and humidity not exceeding 62%. Collectively, our data provide a better understanding of the effects of the environment on microsporidian-mosquito interactions.

Arboviruses can emerge rapidly and cause explosive epidemics of severe disease. Some of the most epidemiologically important arboviruses, including dengue virus (DENV), Zika virus (ZIKV), Chikungunya (CHIKV) and yellow fever virus (YFV), are transmitted by Aedes mosquitoes, most notably Aedes aegypti and Aedes albopictus. After a mosquito blood feeds on an infected host, virus enters the midgut and infects the midgut epithelium. The virus must then overcome a series of barriers before reaching the mosquito saliva and being transmitted to a new host. The virus must escape from the midgut (known as the midgut escape barrier; MEB), which is thought to be mediated by transient changes in the permeability of the midgut-surrounding basal lamina layer (BL) following blood feeding. Here, we present a mathematical model of the within-mosquito population dynamics of DENV (as a model system for mosquito-borne viruses more generally) that includes the interaction of the midgut and BL which can account for the MEB. Our results indicate a dose-dependency of midgut establishment of infection as well as rate of escape from the midgut: collectively, these suggest that the extrinsic incubation period (EIP)-the time taken for DENV virus to be transmissible after infection-is shortened when mosquitoes imbibe more virus. Additionally, our experimental data indicate that multiple blood feeding events, which more closely mimic mosquito-feeding behavior in the wild, can hasten the course of infections, and our model predicts that this effect is sensitive to the amount of virus imbibed. Our model indicates that mutations to the virus which impact its replication rate in the midgut could lead to even shorter EIPs when double-feeding occurs. Mechanistic models of within-vector viral infection dynamics provide a quantitative understanding of infection dynamics and could be used to evaluate novel interventions that target the mosquito stages of the infection.