Figure Legends:
Figure 1: A Similar to other ectothermic organisms, the life history traits of mosquitoes and the pathogens they transmit typically exhibit non-linear relationships with environmental temperature, where trait performance is constrained by both cool and warm temperatures and optimized at some intermediate temperature. Further, the effect of temperature on these individual traits can vary qualitatively and quantitatively, resulting in different temperature ranges across which trait performance can occur, temperatures that maximize trait performance, and the overall shape of the temperature-trait relationship (e.g., symmetric vs. asymmetric). As a result, predicting the effects of temperature on mosquito fitness, population growth rates, or pathogen transmission is complex. B Mathematical models of vector-borne pathogen transmission that incorporate these temperature-trait relationships generally predict transmission to also follow a non-linear relationship and to peak at some intermediate temperature, as depicted here with the temperature-dependent relative reproductive numberR0 as a conceptual example. This model incorporates the effects of temperature on traits that drive mosquito population dynamics (e.g., per capita mosquito development rate (MDR ), the probability of egg to adult survival (pEA ), and the per capita number of eggs females produce per day (EFD )), host-vector contact rates (the per capita daily biting rate of female mosquitoes (a )), and the number of mosquitoes alive and infectious (transmission (b ) and infection (c ) probabilities, the extrinsic incubation period (1/EIR ), and the per capita mosquito mortality rate (μ )). Where the predicted thermal minimum (Tmin ), maximum (Tmax ), and optimum (Topt ) for transmission occur will be dependent upon the relative effect of each trait, the nature of the temperature-trait relationship, and how these factors combine to shape the transmission process. Adapted from Mordecai et al. 2017.
Figure 2: Monthly malaria case data for Plasmodium falciparum shown (in purple) with a corresponding time series for relative humidity (RH, red) for two cities in India, Ahmedabad (A ) and Surat (B ). Total cases during the transmission season from August to November are shown as a function of mean RH in a critical time window preceding this season and including the monsoons from May to July for Ahmedabad (C ) and March to July for Surat (D ). Figure is taken from Santos-Vega et al. (2022)Nature Communications doi: 10.1038/s41467-022-28145-7. Figure is reproduced under Creative Commons Attribution 4.0 International License.
Figure 3: The total amount of water the air can hold, expressed here as saturation vapor pressure (Es ), increases exponentially with temperature and is estimated as a function of temperature using the Tetens equation. The actual amount of water in the air, expressed here as vapor pressure (Ea ), can be derived from relative humidity (RH ) as Ea = RH /100 * Es . The vapor pressure deficit (VPD ) is the absolute difference between Es andEa and is an important metric of atmospheric moisture because it has a near linear relationship with evaporative potential. Thus, as temperature warms, for a given decrease in RH , there will be a larger increase in VPD and the amount of water stress mosquitoes experience.
Figure 4: A Thermal performance is often measured by placing mosquitoes in different life stages and infection stages across a range of constant temperatures at a set relative humidity (typically between 70-90% RH). However, despite holding relative humidity constant, as temperatures warm there will be a corresponding increase in the vapor pressure deficit (VPD ) and the amount of water stress mosquitoes experience. Overlaying these relationships (from Figure 1) on a given temperature-trait relationship demonstrates that the sensitivity of trait performance to variation in relative humidity should be highest on the descending limb of this relationship. Es = saturation vapor pressure, which increases exponentially with temperature and is estimated as a function of temperature using the Tetens equation.Ea = vapor pressure, meaning the actual amount of water in the air, and can be derived from relative humidity (RH ) as Ea= RH /100 * Es . B-D represent the hypothetical responses of three temperature-trait relationships to variation in relative humidity. These shifts are predicted to both decrease the thermal optimum and maximum for some traits (e.g., B lifespan and D vector competence) or increase them for others (e.g.,C per capita biting rate).
Figure 5: Laboratory work with field derived mosquitoes can be conducted to estimate the effect of multiple environmental variables on mosquito fitness, population dynamics, and pathogen transmission. For example, mosquitoes could be housed across a range of constant temperature (T ) and relative humidity (RH ) conditions that are reflective of monthly field conditions. From these experiments, one can estimate the effects of variation in these environmental variables on key larval traits (A : mosquito development rate (MDR ) and the probability of egg to adult survival (pEA )),adult traits (B : per capita mortality rate (μ ), per capita eggs laid per day (EFD ), and per capita daily biting rate (a )), and parasite / pathogen traits (C : vector competence (bc ) and the extrinsic incubation period (EIP )). D Bayesian hierarchical models can be used to develop T and RH response surfaces for each trait, which can either be incorporated in process-based modeling approaches to infer effects on seasonal and inter-annual variation in vector-borne pathogen transmission dynamics. E Bayesian models can also be used to generate a T and RH dependent, relativeR0 model that can be used to predict environmental suitability for pathogen transmission at various spatial scales. A crucial detail for modeling approaches, based on the evidence presented in Box 2, is that the effects of T and RH will be interactive, not additive. (Inset on temporal dynamics in Dis from Santos-Vega et al. (2022) Nature Communications; doi: 10.1038/s41467-022-28145-7. Figure is reproduced under Creative Commons Attribution 4.0 International License.)