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

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          Abstract

          The temperature-dependence of many important mosquito-borne diseases has never been quantified. These relationships are critical for understanding current distributions and predicting future shifts from climate change. We used trait-based models to characterize temperature-dependent transmission of 10 vector–pathogen pairs of mosquitoes ( Culex pipiens, Cx. quinquefascsiatus, Cx. tarsalis, and others) and viruses (West Nile, Eastern and Western Equine Encephalitis, St. Louis Encephalitis, Sindbis, and Rift Valley Fever viruses), most with substantial transmission in temperate regions. Transmission is optimized at intermediate temperatures (23–26°C) and often has wider thermal breadths (due to cooler lower thermal limits) compared to pathogens with predominately tropical distributions (in previous studies). The incidence of human West Nile virus cases across US counties responded unimodally to average summer temperature and peaked at 24°C, matching model-predicted optima (24–25°C). Climate warming will likely shift transmission of these diseases, increasing it in cooler locations while decreasing it in warmer locations.

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          Impact of daily temperature fluctuations on dengue virus transmission by Aedes aegypti.

          Most studies on the ability of insect populations to transmit pathogens consider only constant temperatures and do not account for realistic daily temperature fluctuations that can impact vector-pathogen interactions. Here, we show that diurnal temperature range (DTR) affects two important parameters underlying dengue virus (DENV) transmission by Aedes aegypti. In two independent experiments using different DENV serotypes, mosquitoes were less susceptible to virus infection and died faster under larger DTR around the same mean temperature. Large DTR (20 °C) decreased the probability of midgut infection, but not duration of the virus extrinsic incubation period (EIP), compared with moderate DTR (10 °C) or constant temperature. A thermodynamic model predicted that at mean temperatures 18 °C, larger DTR reduces DENV transmission. The negative impact of DTR on Ae. aegypti survival indicates that large temperature fluctuations will reduce the probability of vector survival through EIP and expectation of infectious life. Seasonal variation in the amplitude of daily temperature fluctuations helps to explain seasonal forcing of DENV transmission at locations where average temperature does not vary seasonally and mosquito abundance is not associated with dengue incidence. Mosquitoes lived longer and were more likely to become infected under moderate temperature fluctuations, which is typical of the high DENV transmission season than under large temperature fluctuations, which is typical of the low DENV transmission season. Our findings reveal the importance of considering short-term temperature variations when studying DENV transmission dynamics.
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            Optimal temperature for malaria transmission is dramatically lower than previously predicted.

            The ecology of mosquito vectors and malaria parasites affect the incidence, seasonal transmission and geographical range of malaria. Most malaria models to date assume constant or linear responses of mosquito and parasite life-history traits to temperature, predicting optimal transmission at 31 °C. These models are at odds with field observations of transmission dating back nearly a century. We build a model with more realistic ecological assumptions about the thermal physiology of insects. Our model, which includes empirically derived nonlinear thermal responses, predicts optimal malaria transmission at 25 °C (6 °C lower than previous models). Moreover, the model predicts that transmission decreases dramatically at temperatures > 28 °C, altering predictions about how climate change will affect malaria. A large data set on malaria transmission risk in Africa validates both the 25 °C optimum and the decline above 28 °C. Using these more accurate nonlinear thermal-response models will aid in understanding the effects of current and future temperature regimes on disease transmission. © 2012 Blackwell Publishing Ltd/CNRS.
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              Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models

              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.
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                Author and article information

                Contributors
                Role: Senior Editor
                Role: Reviewing Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                15 September 2020
                2020
                : 9
                : e58511
                Affiliations
                [1 ]Department of Biology, Stanford University StanfordUnited States
                [2 ]Department of Ecology and Evolutionary Biology, University of California Los Angeles Los AngelesUnited States
                [3 ]Department of Statistics, Virginia Polytechnic Institute and State University (Virginia Tech) BlacksburgUnited States
                [4 ]Department of Integrative Biology, University of South Florida TampaUnited States
                [5 ]Department of Forest and Wildlife Ecology, University of Wisconsin MadisonUnited States
                [6 ]Department of Biological Sciences, Virginia Polytechnic Institute and State University (Virginia Tech) BlacksburgUnited States
                [7 ]Department of Biological Sciences, Eck Institute of Global Health, Environmental Change Initiative, University of Notre Dame South BendUnited States
                McGill University Canada
                McGill University Canada
                McGill University Canada
                Author information
                https://orcid.org/0000-0002-8995-4446
                Article
                58511
                10.7554/eLife.58511
                7492091
                32930091
                901a7ba8-a3d6-47d3-83d9-7e898145c6ad
                © 2020, Shocket et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 02 May 2020
                : 18 August 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: DEB-1518681
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: DMS-1750113
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: NIGMS R35 MIRA: 1R35GM133439-01
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Ecology
                Epidemiology and Global Health
                Custom metadata
                Mechanistic, trait-based models for transmission of West Nile virus and observed incidence of human West Nile disease cases in the US both show optimal transmission at 24-25°C.

                Life sciences
                culex pipiens,culex quinquefasciatus,culex tarsalis,temperature,mosquito-borne disease,west nile virus,virus

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