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Additional file 1. Table S1. Top 10 Global Burden of Disease defined regional increase in people at risk (PAR) for year-round transmission suitability of P. falciparum by An. stephensi in 2050, under RCP 4.5 (SSP2 population projection) and RCP 8.5 (SSP5 population projection) future climate scenarios, averaged across four general circulation models (GCMs) as described in the main methods. Global increase is the sum of all gains in PAR increases across all GBD regions. Table S2.Top 10 Global Burden of Disease defined regional increase in people at risk (PAR) for year-round transmission suitability of P. vivax by An. stephensi in 2050, under RCP 4.5 (SSP2 population projection) and RCP 8.5 (SSP5 population projection) future climate scenarios, averaged across four general circulation models (GCMs) as described in the main methods. Global increase is the sum of all gains in PAR increases across all GBD regions. Table S3.Top 10 Global Burden of Disease defined regional increase in people at risk (PAR) for one or months transmission suitability of P. falciparum by An. stephensi in 2050, under RCP 4.5 (SSP2 population projection) and RCP 8.5 (SSP5 population projection) future climate scenarios, averaged across four general circulation models (GCMs) as described in the main methods. Global increase is the sum of all gains in PAR increases across all GBD regions. Table S4.Top 10 Global Burden of Disease defined regional increase in people at risk (PAR) for one or months transmission suitability of P. vivax by An. stephensi in 2050, under RCP 4.5 (SSP2 population projection) and RCP 8.5 (SSP5 population projection) future climate scenarios, averaged across four general circulation models (GCMs) as described in the main methods. Global increase is the sum of all gains in PAR increases across all GBD regions.

Mosquito-borne diseases cause a major burden of disease worldwide. The vital rates of these ectothermic vectors and parasites respond strongly and nonlinearly to temperature and therefore to climate change. Here, we review how trait-based approaches can synthesise and mechanistically predict the temperature dependence of transmission across vectors, pathogens, and environments. We present 11 pathogens transmitted by 15 different mosquito species – including globally important diseases like malaria, dengue, and Zika – synthesised from previously published studies. Transmission varied strongly and unimodally with temperature, peaking at 23–29ºC and declining to zero below 9–23ºC and above 32–38ºC. Different traits restricted transmission at low versus high temperatures, and temperature effects on transmission varied by both mosquito and parasite species. Temperate pathogens exhibit broader thermal ranges and cooler thermal minima and optima than tropical pathogens. Among tropical pathogens, malaria and Ross River virus had lower thermal optima (25–26ºC) while dengue and Zika viruses had the highest (29ºC) thermal optima. We expect warming to increase transmission below thermal optima but decrease transmission above optima. Key directions for future work include linking mechanistic models to field transmission, combining temperature effects with control measures, incorporating trait variation and temperature variation, and investigating climate adaptation and migration. Published version

Additional file 1: Table S1. Hurdle model of hourly biting rates. Model coefficients are presented as incidence rate ratios for the count model (which models hourly bites conditional on being bitten using a negative binomial error distribution and log link), and as odds ratios for the zero model (which models the probability of being bitten using binomial errors and a logit link). Values in parentheses are 95% confidence intervals. Significance levels are * p