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Anopheles stephensiis 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 bothPlasmodium falciparumandPlasmodium vivaxmalaria. Perhaps most alarming, the characteristics ofAn.stephensi, such as container breeding and anthropophily, make it particularly adept at exploiting built environments in areas with no prior history of malaria risk.

In this paper, global maps of thermal transmission suitability and people at risk (PAR) for malaria transmission byAn.stephensiwere 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.

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 withAn.stephensipresence. General patterns of poleward expansion for thermal suitability were seen for bothP.falciparumandP.vivaxtransmission potential.

Understanding the potential suitability forAn.stephensitransmission 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.

 

When a rare pathogen emerges to cause a pandemic, it is critical to understand its dynamics and the impact of mitigation measures. We use experimental data to parametrize a temperature-dependent model of Zika virus (ZIKV) transmission dynamics and analyse the effects of temperature variability and control-related parameters on the basic reproduction number ( R 0 ) and the final epidemic size of ZIKV. Sensitivity analyses show that these two metrics are largely driven by different parameters, with the exception of temperature, which is the dominant driver of epidemic dynamics in the models. Our R 0 estimate has a single optimum temperature (≈30°C), comparable to other published results (≈29°C). However, the final epidemic size is maximized across a wider temperature range, from 24 to 36°C. The models indicate that ZIKV is highly sensitive to seasonal temperature variation. For example, although the model predicts that ZIKV transmission cannot occur at a constant temperature below 23°C (≈ average annual temperature of Rio de Janeiro, Brazil), the model predicts substantial epidemics for areas with a mean temperature of 20°C if there is seasonal variation of 10°C (≈ average annual temperature of Tampa, Florida). This suggests that the geographical range of ZIKV is wider than indicated from static R 0 models, underscoring the importance of climate dynamics and variation in the context of broader climate change on emerging infectious diseases. 

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 falciparumandPlasmodium vivax, by two malaria vector species,Anopheles gambiaeandAnopheles 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 carryingP. 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. stephensiandA. gambiaeboth withP. falciparum). Using prevalence data, we show that the transmission suitability metric calculated from our mechanistic model is consistent with observedP. falciparumprevalence in Africa and Asia but is equivocal forP. vivaxprevalence in Asia, and inconsistent withP. vivaxprevalence 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.

 

Mosquitoes carry several diseases that pose an emerging threat to society. Outbreaks of these diseases are often sudden and can spread to previously unaffected areas. For example, the Zika virus was discovered in 1947, but only received international attention when it spread to the Americas in 2014, where it caused over 100,000 cases in Brazil alone. While we now recognize the threat Zika can pose for public health, our knowledge about the ecology of the disease remains poor. Nine species of mosquitoes are known to be able to carry the Zika virus, but it cannot be ruled out that other mosquitoes may also be able to spread the disease. There are hundreds of species of mosquitoes, and testing all of them is difficult and costly. So far, only a small number of species have been tested to see if they transmit Zika. However, computational tools called decision trees could help by predicting which mosquitoes can transmit a virus based on common traits, such as a mosquito's geographic range, or the symptoms of a virus. Evans et al. used decision trees to create a model that predicts which species of mosquitoes are potential carriers of Zika virus and should therefore be prioritized for testing. The model took into account all known viruses that belong to the same family as Zika virus and the mosquitoes that carry them. Evans et al. predict that 35 species may be able to carry the Zika virus, seven of which are found in the United States. Two of these mosquito species are known to transmit West Nile Virus and are therefore prime examples of species that should be prioritized for testing. Together, the ranges of the seven American species encompass the whole United States, suggesting Zika virus could affect a much larger area than previously anticipated. The next step following on from this work will be to carry out experiments to test if the 35 mosquitoes identified by the model are actually able to transmit the Zika virus. 

Invasive mosquitoes are expanding their ranges into new geographic areas and interacting with resident mosquito species. Understanding how novel interactions can affect mosquito population dynamics is necessary to predict transmission risk at invasion fronts. Mosquito life‐history traits are extremely sensitive to temperature, and this can lead to temperature‐dependent competition between competing invasive mosquito species. We explored temperature‐dependent competition betweenAedes aegyptiandAnopheles stephensi, two invasive mosquito species whose distributions overlap in India, the Middle East, and North Africa, whereAn. stephensiis currently expanding into the endemic range ofAe. aegypti. We followed mosquito cohorts raised at different intraspecific and interspecific densities across five temperatures (16–32°C) to measure traits relevant for population growth and to estimate species’ per capita growth rates. We then used these growth rates to derive each species’ competitive ability at each temperature. We find strong evidence for asymmetric competition at all temperatures, withAe. aegyptiemerging as the dominant competitor. This was primarily because of differences in larval survival and development times across all temperatures that resulted in a higher estimated intrinsic growth rate and competitive tolerance estimate forAe. aegypticompared toAn. stephensi. The spread ofAn. stephensiinto the African continent could lead to urban transmission of malaria, an otherwise rural disease, increasing the human population at risk and complicating malaria elimination efforts. Competition has resulted in habitat segregation of other invasive mosquito species, and our results suggest that it may play a role in determining the distribution ofAn. stephensiacross its invasive range.

 

In the aftermath of the 2015 pandemic of Zika virus (ZIKV), concerns over links between climate change and emerging arboviruses have become more pressing. Given the potential that much of the world might remain at risk from the virus, we used a previously established temperature‐dependent transmission model for ZIKV to project climate change impacts on transmission suitability risk by mid‐century (a generation into the future). Based on these model predictions, in the worst‐case scenario, over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050. The next generation will face substantially increased ZIKV transmission temperature suitability in North America and Europe, where naïve populations might be particularly vulnerable. Mitigating climate change even to moderate emissions scenarios could significantly reduce global expansion of climates suitable for ZIKV transmission, potentially protecting around 200 million people. Given these suitability risk projections, we suggest an increased priority on research establishing the immune history of vulnerable populations, modeling when and where the next ZIKV outbreak might occur, evaluating the efficacy of conventional and novel intervention measures, and increasing surveillance efforts to prevent further expansion of ZIKV.