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Extrinsic environmental factors influence the spatiotemporal dynamics of many organisms, including insects that transmit the pathogens responsible for vector-borne diseases (VBDs). Temperature is an especially important constraint on the fitness of a wide variety of ectothermic insects. A mechanistic understanding of how temperature impacts traits of ectotherms, and thus the distribution of ectotherms and vector-borne infections, is key to predicting the consequences of climate change on transmission of VBDs like malaria. However, the response of transmission to temperature and other drivers is complex, as thermal traits of ectotherms are typically nonlinear, and they interact to determine transmission constraints. In this study, we assess and compare the effect of temperature on the transmission of two malaria parasites, Plasmodium falciparum and Plasmodium vivax, by two malaria vector species, Anopheles gambiae and Anopheles stephensi. We model the nonlinear responses of temperature dependent mosquito and parasite traits (mosquito development rate, bite rate, fecundity, proportion of eggs surviving to adulthood, vector competence, mortality rate, and parasite development rate) and incorporate these traits into a suitability metric based on a model for the basic reproductive number across temperatures. Our model predicts that the optimum temperature for transmission suitability is similar for the four mosquito–parasite combinations assessed in this study, but may differ at the thermal limits. More specifically, we found significant differences in the upper thermal limit between parasites spread by the same mosquito (A. stephensi) and between mosquitoes carrying P. falciparum. In contrast, at the lower thermal limit the significant differences were primarily between the mosquito species that both carried the same pathogen (e.g., A. stephensi and A. gambiae both with P. falciparum). Using prevalence data, we show that the transmission suitability metric S(T) calculated from our mechanistic model is consistent with observed P. falciparum prevalence in Africa and Asia but is equivocal for P. vivax prevalence in Asia, and inconsistent with P. vivax prevalence in Africa. We mapped risk to illustrate the number of months various areas in Africa and Asia predicted to be suitable for malaria transmission based on this suitability metric. This mapping provides spatially explicit predictions for suitability and transmission risk.

Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18-34°C with maximal transmission occurring in a range from 26-29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.

Most statistical and mechanistic models used to predict mosquito-borne disease transmission incorporate climate drivers of disease transmission by utilizing environmental data collected at geographic scales that are potentially coarser than what mosquito populations may actually experience. Temperature and relative humidity can vary greatly between indoor and outdoor environments, and can be influenced strongly by variation in landscape features. In the Aedes albopictus system, we conducted a proof-of-concept study in the vicinity of the University of Georgia to explore the effects of fine-scale microclimate variation on mosquito life history and vectorial capacity (VC). We placed Ae. albopictus larvae in artificial pots distributed across three replicate sites within three different land uses-urban, suburban, and rural, which were characterized by high, intermediate, and low proportions of impervious surfaces. Data loggers were placed into each larval environment and in nearby vegetation to record daily variation in water and ambient temperature and relative humidity. The number of adults emerging from each pot and their body size and sex were recorded daily. We found mosquito microclimate to significantly vary across the season as well as with land use. Urban sites were in general warmer and less humid than suburban and rural sites, translating into decreased larval survival, smaller body sizes, and lower per capita growth rates of mosquitoes on urban sites. Dengue transmission potential was predicted to be higher in the summer than the fall. Additionally, the effects of land use on dengue transmission potential varied by season. Warm summers resulted in a higher predicted VC on the cooler, rural sites, while warmer, urban sites had a higher predicted VC during the cooler fall season.

When predicting the response of organisms to global change, models use measures of climate at a coarse resolution from general circulation models or from downscaled regional models. Organisms, however, do not experience climate at such large scales. The climate heterogeneity over a landscape and how much of that landscape an organism can sample will determine ultimately the microclimates experienced by organisms. This past few decades has seen an important increase in the number of studies reporting microclimatic patterns at small scales. This synthesis intends to unify studies reporting microclimatic heterogeneity (mostly temperature) at various spatial scales, to infer any emerging trends, and to discuss the causes and consequences of such heterogeneity for organismal performance and with respect to changing land use patterns and climate. First, we identify the environmental drivers of heterogeneity across the various spatial scales that are pertinent to ectotherms. The thermal heterogeneity at the local and micro-scales is mostly generated by the architecture or the geometrical features of the microhabitat. Then, the thermal heterogeneity experienced by individuals is modulated by behavior. Second, we survey the literature to quantify thermal heterogeneity from the micro-scale up to the scale of a landscape in natural habitats. Despite difficulties in compiling studies that differ much in their design and aims, we found that there is as much thermal heterogeneity across micro-, local and landscape scales, and that the temperature range is large in general (>9°C on average, and up to 26°C). Third, we examine the extent to which urban habitats can be used to infer the microclimatic patterns of the future. Urban areas generate globally drier and warmer microclimatic patterns and recent evidence suggest that thermal traits of ectotherms are adapted to them. Fourth, we explore the interplay between microclimate heterogeneity and the behavioral thermoregulatory abilities of ectotherms in setting their overall performance. We used a random walk framework to show that the thermal heterogeneity allows a more precise behavioral thermoregulation and a narrower temperature distribution of the ectotherm compared to less heterogeneous microhabitats. Finally, we discuss the potential impacts of global change on the fine scale mosaics of microclimates. The amplitude of change may differ between spatial scales. In heterogeneous microhabitats, the amplitude of change at micro-scale, caused by atmospheric warming, can be substantial while it can be limited at the local and landscape scales. We suggest that the warming signal will influence species performance and biotic interactions by modulating the mosaic of microclimates.

Several aspects of mosquito ecology that are important for vectored disease transmission and control have been difficult to measure at epidemiologically important scales in the field. In particular, the ability to describe mosquito population structure and movement rates has been hindered by difficulty in quantifying fine-scale genetic variation among populations. The mosquito virome represents a possible avenue for quantifying population structure and movement rates across multiple spatial scales. Mosquito viromes contain a diversity of viruses, including several insect-specific viruses (ISVs) and “core” viruses that have high prevalence across populations. To date, virome studies have focused on viral discovery and have only recently begun examining viral ecology. While nonpathogenic ISVs may be of little public health relevance themselves, they provide a possible route for quantifying mosquito population structure and dynamics. For example, vertically transmitted viruses could behave as a rapidly evolving extension of the host’s genome. It should be possible to apply established analytical methods to appropriate viral phylogenies and incidence data to generate novel approaches for estimating mosquito population structure and dispersal over epidemiologically relevant timescales. By studying the virome through the lens of spatial and genomic epidemiology, it may be possible to investigate otherwise cryptic aspects of mosquito ecology. A better understanding of mosquito population structure and dynamics are key for understanding mosquito-borne disease ecology and methods based on ISVs could provide a powerful tool for informing mosquito control programs.

The emergence of mosquito-transmitted viruses poses a global threat to human health. Combining mechanistic epidemiological models based on temperature-trait relationships with climatological data is a powerful technique for environmental risk assessment. However, a limitation of this approach is that the local microclimates experienced by mosquitoes can differ substantially from macroclimate measurements, particularly in heterogeneous urban environments. To address this scaling mismatch, we modeled spatial variation in microclimate temperatures and the thermal potential for dengue transmission by Aedes albopictus across an urban-to-rural gradient in Athens-Clarke County GA. Microclimate data were collected across gradients of tree cover and impervious surface cover. We developed statistical models to predict daily minimum and maximum microclimate temperatures using coarse-resolution gridded macroclimate data (4000 m) and high-resolution land cover data (30 m). The resulting high-resolution microclimate maps were integrated with temperature-dependent mosquito abundance and vectorial capacity models to generate monthly predictions for the summer and early fall of 2018. The highest vectorial capacities were predicted for patches of trees in urban areas with high cover of impervious surfaces. Vectorial capacity was most sensitive to tree cover during the summer and became more sensitive to impervious surfaces in the early fall. Predictions from the same models using temperature data from a local meteorological station consistently over-predicted vectorial capacity compared to the microclimate-based estimates. This work demonstrates that it is feasible to model variation in mosquito microenvironments across an urban-to-rural gradient using satellite Earth observations. Epidemiological models applied to the microclimate maps revealed localized patterns of temperature suitability for disease transmission that would not be detectable using macroclimate data. Incorporating microclimate data into disease transmission models has the potential to yield more spatially precise and ecologically interpretable metrics of mosquito-borne disease transmission risk in urban landscapes.

Background Anopheles stephensi is a malaria-transmitting mosquito that has recently expanded from its primary range in Asia and the Middle East, to locations in Africa. This species is a competent vector of both Plasmodium falciparum and Plasmodium vivax malaria. Perhaps most alarming, the characteristics of An . stephensi , such as container breeding and anthropophily, make it particularly adept at exploiting built environments in areas with no prior history of malaria risk. Methods In this paper, global maps of thermal transmission suitability and people at risk (PAR) for malaria transmission by An . stephensi were created, under current and future climate. Temperature-dependent transmission suitability thresholds derived from recently published species-specific thermal curves were used to threshold gridded, monthly mean temperatures under current and future climatic conditions. These temperature driven transmission models were coupled with gridded population data for 2020 and 2050, under climate-matched scenarios for future outcomes, to compare with baseline predictions for 2020 populations. Results Using the Global Burden of Disease regions approach revealed that heterogenous regional increases and decreases in risk did not mask the overall pattern of massive increases of PAR for malaria transmission suitability with An . stephensi presence. General patterns of poleward expansion for thermal suitability were seen for both P . falciparum and P . vivax transmission potential. Conclusions Understanding the potential suitability for An . stephensi transmission in a changing climate provides a key tool for planning, given an ongoing invasion and expansion of the vector. Anticipating the potential impact of onward expansion to transmission suitable areas, and the size of population at risk under future climate scenarios, and where they occur, can serve as a large-scale call for attention, planning, and monitoring.

Over evolutionary time, Wolbachia has been repeatedly transferred between host species contributing to the widespread distribution of the symbiont in arthropods. For novel infections to be maintained, Wolbachia must infect the female germ line after being acquired by horizontal transfer. Although mechanistic examples of horizontal transfer exist, there is a poor understanding of factors that lead to successful vertical maintenance of the acquired infection. Using Anopheles mosquitoes (which are naturally uninfected by Wolbachia) we demonstrate that the native mosquito microbiota is a major barrier to vertical transmission of a horizontally acquired Wolbachia infection. After injection into adult Anopheles gambiae, some strains of Wolbachia invade the germ line, but are poorly transmitted to the next generation. In Anopheles stephensi, Wolbachia infection elicited massive blood meal-induced mortality, preventing development of progeny. Manipulation of the mosquito microbiota by antibiotic treatment resulted in perfect maternal transmission at significantly elevated titers of the wAlbB Wolbachia strain in A. gambiae, and alleviated blood meal-induced mortality in A. stephensi enabling production of Wolbachia-infected offspring. Microbiome analysis using high-throughput sequencing identified that the bacterium Asaia was significantly reduced by antibiotic treatment in both mosquito species. Supplementation of an antibiotic-resistant mutant of Asaia to antibiotic-treated mosquitoes completely inhibited Wolbachia transmission and partly contributed to blood meal-induced mortality. These data suggest that the components of the native mosquito microbiota can impede Wolbachia transmission in Anopheles. Incompatibility between the microbiota and Wolbachia may in part explain why some hosts are uninfected by this endosymbiont in nature.

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. Malaria transmission is sensitive to temperature and models of malaria typically account for daily fluctuations in temperature through a ‘rate summation’ approach. Here, the authors conduct experimental and modeling work to investigate the accuracy of rate summation in predicting thermal suitability of malaria transmission by Anopheles stephensi .

As global temperatures rise due to climate change, urban heat islands have emerged as an important public health concern, significantly exacerbating heat stress in urban populations. Meteorological data is critical for assessing heat stress, and localized microclimate data provide more precise measurements of heat hazards than traditional weather station data. Our study explored microclimate patterns in space and time in tropical cities with rapidly growing urban populations and warming climates. We established a microclimate monitoring network with sensors measuring air temperature and relative humidity throughout two large cities in Gujarat, India. We collected hourly microclimate data on temperature and humidity from April 2023 to May 2024 from paired indoor/outdoor sensors at 48 homes in Ahmedabad and 45 homes in Surat. We summarized dry bulb (T) and wet-bulb (Tw) temperatures at indoor and outdoor locations, compared temporal patterns across seasons and times of the day, and investigated relationships with urban land cover. Indoor and outdoor microclimates had different diurnal variations, with distinctive patterns during the monsoon compared to other seasons. Building volume had warming effects and vegetation had cooling effects on minimum T and Tw, particularly at outdoor locations. In contrast, building volume had cooling effects and vegetation had warming effects on maximum T and Tw, particularly at indoor locations. Temperatures were consistently cooler at locations with higher albedo, and relationships with water were weaker and more variable. A model comparison found significant differences in land cover effects for indoor versus outdoor locations. Given the increasing occurrence of heat waves and climate-related health threats in western India and other tropical areas, it will be essential to account for the different spatial and temporal patterns of indoor and outdoor microclimates to more precisely identify locations and timings of temperature extremes.