DOI: 10.5061/dryad.8cz8w9gmd
title: Data from: Age influences the thermal suitability of Plasmodium falciparum transmission in the Asian malaria vector Anopheles stephensi

description: Models predicting disease transmission are vital tools for long-term
 planning of malaria reduction efforts, particularly for mitigating impacts
 of climate change. We compared temperature-dependent malaria transmission
 models when mosquito life history traits were estimated from a truncated
 portion of the lifespan (a common practice) to traits measured across the
 full lifespan. We conducted an experiment on adult female Anopheles
 stephensi, the Asian urban malaria mosquito, to generate daily per capita
 values for mortality, egg production, and biting rate at six constant
 temperatures. Both temperature and age significantly affected trait
 values. Further, we found quantitative and qualitative differences between
 temperature-trait relationships estimated from truncated data versus
 observed lifetime values. Incorporating these temperature-trait
 relationships into an expression governing the thermal suitability of
 transmission, relative R0(T), resulted in minor differences in the breadth
 of suitable temperatures for Plasmodium falciparum transmission between
 the two models constructed from only An. stephensi trait data. However, we
 found a substantial increase in thermal niche breadth compared to a
 previously published model consisting of trait data from multiple
 Anopheles mosquito species. Overall, this work highlights the importance
 of considering how mosquito trait values vary with mosquito age and
 mosquito species when generating temperature-based suitability predictions
 of transmission.
description: <b><i>Life history
 experiment</i></b> We ran a life history
 experiment on the urban type form <em>Anopheles
 stephensi</em>, which was initiated three days after adult emergence
 to permit mating. After they were presented with an initial blood meal for
 15 minutes via a water-jacketed membrane feeder, we randomly distributed
 30 host-seeking females into individual cages (16 oz. paper cup; mesh top)
 to one of six constant temperature treatments (16°C, 20°C, 24°C, 28°C, 32°C, 36°C ± 0.5°C, 80% ± 5 RH, and 12L:12D
 photoperiod). Each individual adult cage contained an oviposition site: a
 petri dish secured to the bottom of the housing containing cotton balls to
 retain liquid, overlaid with filter paper for egg removal and counting.
 Individual mosquitoes were offered a blood meal for 15 min each day. Blood
 meals were scored through visual verification of the abdomen immediately
 after the feeding period. Oviposition sites were rehydrated and checked
 for the presence of eggs daily. We followed populations of individual
 females in each temperature treatment until all mosquitoes had died or
 when less than 7% of the starting population remained. At least two
 biological replicates were performed at each temperature (N=
 390). <b><i>Statistical
 analyses</i></b> We used generalized linear
 mixed models (GLMM) R package &lt;<i>lme4::glmer()</i>
 (29)<i> </i>&gt; to estimate the effects of temperature,
 mosquito age, and their interaction on the proportion of females that
 imbibed blood on a given day (i.e., the number of females that took a
 blood meal on a given day out of the total number of females alive on that
 day for each temperature treatment) and the mean daily egg production
 (i.e., the number of eggs laid on a given day divided by the total number
 of females alive on that day in a given temperature treatment). We used a
 Log-rank test with R package <i>&lt;survival::survdiff()
 </i>(30)<i>&gt;</i> on Kaplan-Meier estimates to
 determine if survivorship differed with temperature. Lastly, to determine
 if the daily survival rate changed across the lifespan of the mosquito, we
 fit a variety of survival distributions, which allow either for a constant
 (exponential) or variable daily mortality rate (log-normal, gamma,
 Gompertz, and Weibull) with R package &lt;<i>flexsurv
 </i>(31)<i>&gt; </i>to the Kaplan-Meier
 estimates. <b><i>Fitting thermal
 responses in a Bayesian framework</i></b> To predict the thermal limits
 (<i>T<sub>min</sub></i>,
 <i>T<sub>max</sub></i>) and optimum
 (<i>T<sub>opt</sub></i>) for each parameter, we
 used Bayesian inference to fit either a symmetric (quadratic;
 -<i>c</i>(<i>T-T<sub>min</sub></i>)(<i>T-T<sub>max</sub></i>)) or an asymmetric (Briere; <i>cT</i>(<i>T-T<sub>min</sub></i>)(<i>T<sub>max</sub></i>-<i>T</i>)<sup>1/2</sup>) unimodal non-linear function to each trait versus temperature (<i>T, in degrees Celsius</i>) as in Johnson et al. 2015 (10). Note the parameter <i>c</i> is a fit parameter that controls the shape of each respective function. These functions were further restricted to be non-negative. That is, all traits are assumed to be zero if <i>T </i>&lt; <i>T<sub>min</sub></i> or <i>T</i> &gt; <i>T<sub>max</sub></i>). We assumed that data are distributed as truncated normal distributions with the means for each block and temperature described by either the quadratic or Briere function as above. We selected the best-fitting functional form for the mean between quadratic or Briere using the Deviance Information Criterion (DIC). We chose to fit thermal responses to the data means across individuals for each replicate as opposed to the raw individual data due to 1) the data exhibiting extreme non-normality for some traits (e.g., lifetime egg production, estimated daily eggs, and lifespan) and thus 2) to ensure compliance with the central limit theorem (CLT) when fitting truncated normal distributions. Developing methodology to account for the non-normal distributions associated with observing individual level data is a key research gap to refine predictions of thermal suitability of transmission events and is an area of future work. For each parameter in the mean function (i.e., <i>c</i>, <i>T<sub>min</sub></i>, <i>T<sub>max</sub></i>) and the variance of the truncated normal distribution, we assumed relatively uninformative uniform priors that restrict the range of parameters to biologically meaningful values.  More specifically, we first fit curves with uninformative priors restricted to biologically informed ranges (<i>T<sub>0</sub></i> ~ uniform (0, 24), <i>T<sub>m</sub></i> ~ uniform (25, 45), <i>c</i> ~ uniform (0, 1)) , followed by informative priors derived from traits estimated in a previous study (assuming a gamma distribution over each component trait). A direct comparison of each temperature-trait response using either uninformative or informative priors is provided to illustrate the influence of informative priors on our trait fits presented in the main text. No fit with informative priors was conducted for lifetime egg production (<i>B</i>) as Johnson et al. 2015 did not fit this trait and thus appropriate priors did not exist. Further, we choose to use the fit using uninformative priors for estimated daily eggs (<i>EFD*</i>) as informative priors altered the thermal response outside the observed data and drastically increased the credible intervals. This is likely associated with the large uncertainty associated with the prior fit observed in Johnson et al. 2015. Models were fitted in R using JAGS/rjag, which implements Markov Chain Monte Carlo (MCMC). For each thermal trait, posterior draws for the parameters were obtained from three concurrent Moarkv chains. In each chain, a 5,000-step burn-in phase was followed by 20,000 samples of the stationary chain, for a total of 60,000 posterior samples. These samples were then thinned by saving every eigth sample, in order to further reduce autocorrelation in the chain and to reduce computation in the following analyses. We also defined temperature-trait responses for mosquito and parasite traits not directly measured in this study to assess the impact incorporating multiple trait thermal responses from a single mosquito species (<i>An. stephensi</i>), rather than aggregated from several different mosquito species, has on relative <i>R<sub>0</sub></i>(<i>T</i>). <i>An. stephensi</i> data in Paaijmans et al. 2013 and Shapiro et al. 2017 were used to construct temperature-trait relationships for mosquito development rate (<i>MDR</i>), probability of egg to adult survival (<i>pEA</i>), <i>P. falciparum</i> development rate (<i>PDR</i>) and vector competence (<i>bc</i>). In contrast, for the Multi-species estimated model we used the thermal relationships defined in Johnson et al. 2015.
description: Description of the data is included in the associated metadata
 file that is uploaded in the Miazgowiczetal_ProcRoySoc_Data zip
 file.