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Temperature impacts the transmission of malaria parasites by Anopheles gambiae and Anopheles stephensi mosquitoes

Oswaldo C. Villena, View ORCID ProfileSadie J. Ryan, Courtney C. Murdock, View ORCID ProfileLeah R. Johnson
doi: https://doi.org/10.1101/2020.07.08.194472
Oswaldo C. Villena
1Department of Statistics, Virginia Tech, VA 24061 USA
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Sadie J. Ryan
2Department of Geography, University of Florida, Gainesville, FL 32611 USA
3Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
4School of Life Sciences, University of KwaZulu-Natal, Durban, South Africa
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Courtney C. Murdock
5Odum School of Ecology, University of Georgia, Athens GA 30602, USA
6Center for the Ecology of Infectious Diseases, University of Georgia, Athens GA 30602, USA
7Center for Vaccines and Immunology, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA
8Riverbasin Center, University of Georgia, Athens GA 30602, USA
9Department of Entomology, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY 14853, USA
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Leah R. Johnson
1Department of Statistics, Virginia Tech, VA 24061 USA
10Computational Modeling and Data Analytics, Virginia Tech, VA 24061 USA
11Department of Biology, Virginia Tech, VA 24061 USA
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  • For correspondence: lrjohnson0@gmail.com
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Abstract

Extrinsic environmental factors influence the spatio-temporal 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 insects, as they are primarily ectotherms. Temperature constrains the distribution of ectotherms and therefore of the infections that they spread in both space and time. More concretely, a mechanistic understanding of how temperature impacts traits of ectotherms to predict 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 non-linear, 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 non-linear responses of temperature dependent mosquito and parasite traits (mosquito development rate, bite rate, fecundity, egg to adult survival, 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. The main differences are found at the thermal limits. More specifically, we found significant differences in the upper thermal limit between parasites spread by the same mosquito (An. 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., An. stephensi and An. gambiae both with P. falciparum). Using prevalence data from Africa and Asia, we show that the transmission suitability metric S(T) calculated from our mechanistic model is an important predictor of malaria prevalence. We mapped risk to illustrate the areas in Africa and Asia that are suitable for malaria transmission year-round based temperature.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Updated figures, shortened main manuscript, and moved some to the supplementary materials.

  • Terms and abbreviations

    BIC
    Bayesian information criterion
    D2
    Squared Deviance, the proportion of deviance explained by the model
    Model pr.
    Model probability based on BIC
    ηi
    linear predictor;
    β0
    Intercept; β1,…βn Regression parameters
    lpop den
    log(population density)
    lGDP
    log(per capita gross domestic product)
    SGTZ
    Probability of S(T)>0
    Pfal
    Plasmodium falciparum
    Pviv
    Plasmodium vivax
    𝟙AFR
    An indicator function that returns 1 if the condition in the subscript is TRUE and zero if FALSE. In our notation, the variable AFR is TRUE (=1) if the location is in Africa and if FALSE (=0) otherwise (i.e., if the location is in Asia).
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    Posted October 14, 2020.
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    Temperature impacts the transmission of malaria parasites by Anopheles gambiae and Anopheles stephensi mosquitoes
    Oswaldo C. Villena, Sadie J. Ryan, Courtney C. Murdock, Leah R. Johnson
    bioRxiv 2020.07.08.194472; doi: https://doi.org/10.1101/2020.07.08.194472
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    Temperature impacts the transmission of malaria parasites by Anopheles gambiae and Anopheles stephensi mosquitoes
    Oswaldo C. Villena, Sadie J. Ryan, Courtney C. Murdock, Leah R. Johnson
    bioRxiv 2020.07.08.194472; doi: https://doi.org/10.1101/2020.07.08.194472

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