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.)