Abstract
AbstractExtrinsic 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 falciparumandPlasmodium vivax, by two malaria vector species,Anopheles gambiaeandAnopheles 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 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.,An. stephensiandAn. gambiaeboth withP. falciparum). Using prevalence data from Africa and Asia, we show that the transmission suitability metricS(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.
Publisher
Cold Spring Harbor Laboratory
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