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Changing temperature profiles and the risk of dengue outbreaks [1]

['Imelda Trejo', 'Theoretical Biology', 'Biophysics', 'Los Alamos National Laboratory', 'Los Alamos', 'Nm', 'United States Of America', 'Martha Barnard', 'Information Systems', 'Modeling']

Date: 2023-03

Abstract As temperatures change worldwide, the pattern and competency of disease vectors will change, altering the global distribution of both the burden of infectious disease and the risk of the emergence of those diseases into new regions. To evaluate the risk of potential summer dengue outbreaks triggered by infected travelers under various climate scenarios, we develop an SEIR-type model, run numerical simulations, and conduct sensitivity analyses under a range of temperature profiles. Our model extends existing theoretical frameworks for studying dengue dynamics by introducing temperature dependence of two key parameters: the mosquito extrinsic incubation period and the lifespan of mosquitoes, which empirical data suggests are both highly temperature dependent. We find that changing temperature significantly alters dengue risk in an inverted U-shape, with temperatures in the range 27-31°C producing the highest risk. As temperatures increase beyond 31°C, the determinants of dengue risk begin to shift from mosquito biting rate and carrying capacity to the duration of the human infectious period, suggesting that changing temperatures not only alter dengue risk but also the potential efficacy of control measures. To illustrate the role of spatial and temporal temperature heterogeneity, we select five US cities where the primary dengue vector, the mosquito Aedes aegypti, has been observed, and which have had dengue cases in the past: Los Angeles, Houston, Miami, Brownsville, and Phoenix. Our analysis suggests that an increase of 3°C leads to an approximate doubling of the risk of dengue in Los Angeles and Houston, but a reduction of risk in Miami, Brownsville, and Phoenix due to extreme heat.

Citation: Trejo I, Barnard M, Spencer JA, Keithley J, Martinez KM, Crooker I, et al. (2023) Changing temperature profiles and the risk of dengue outbreaks. PLOS Clim 2(2): e0000115. https://doi.org/10.1371/journal.pclm.0000115 Editor: Samuel Nii Ardey Codjoe, University of Ghana, GHANA Received: January 24, 2022; Accepted: December 21, 2022; Published: February 15, 2023 This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Data Availability: All data used in this analysis are publicly available. Details are provided in S1 Table. Funding: IT and NH were funded by the Laboratory Directed Research and Development Program of Los Alamos National Laboratory under project numbers 20210709ER and 20210043DR. IT, MB, JK, KMM, IC, EOR, and CM were funded by the Laboratory Directed Research and Development Program of Los Alamos National Laboratory under project number 20210062DR. NH benefited from the support and resources of the Center for Non-Linear Studies at LANL. JAS was supported by an appointment to the Intelligence Community Postdoctoral Research Fellowship Program at Los Alamos National Laboratory administered by Oak Ridge Institute for Science and Education (ORISE) through an interagency agreement between the U.S. Department of Energy and the Office of the Director of National Intelligence (ODNI). The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of Los Alamos National Laboratory. Los Alamos National Laboratory, an affirmative action/equal opportunity employer, is managed by Triad National Security, LLC, for the National Nuclear Security Administration of the U.S. Department of Energy under contract 89233218CNA000001. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

Introduction The global reported incidence of Dengue fever, a mosquito-borne disease caused by dengue virus [1], has increased 8-fold in the past two decades. Almost half of the world’s population is now at risk [2], with an estimated 390 million new cases every year [3]. No effective vaccine is broadly available [4], and the primary way to mitigate the disease is through control of or protection from mosquito populations [5–7]. Mosquitoes are a necessary intermediate host for the dengue life-cycle. Mosquitoes are ectothermic, and their life cycle is very sensitive to environmental temperature, which is a key driver of annual dengue case counts [8–13]. The extrinsic incubation period (EIP) is the period from when a mosquito ingests an infectious blood meal to when it becomes infectious (competent to transmit dengue virus). As temperature increases, EIP decreases up to a point, suggesting a proportional relationship between temperature and dengue risk. However, for transmission to take place, the mosquito lifespan, which declines with increasing temperature after a certain point, must exceed the EIP [9, 13–17]. Recent work has quantified the impact of EIP dependence on temperature [14, 18–20]. Considerable modeling work has been done on the effects of temperature dependence of mosquito life traits on arbovirus transmission [21–25]. Mayton et al. established the importance of mosquito age structure on transmission potential, which we include in our model as a temperature dependent lifespan [26]. As temperature changes, the implicit age structure of the mosquito population also changes. Previous models have adopted varied approaches to studying the effects of temperature dependent parameters on disease dynamics. Mordecai et al. integrated multiple temperature dependent parameters to study the relationship of temperature on the epidemic threshold [21], while Kamiya et al. used an explicit epidemic model to examine the effect of temperature dependent EIP while fixing other model parameters [18]. Our study extends these approaches by allowing both lifespan and EIP to vary with temperature in a explicit mechanistic model that both allows us to simulate dynamics and define the epidemic threshold. This approach allows us to characterize temperature-dependent dengue risk more fully by including key drivers of the life-history trade-offs for both dengue and its mosquito hosts. The effects of a changing climate on mosquito-borne disease are not monotonic, and increasing temperatures can have complex effects not only the global distribution of dengue but also on mitigation strategies [13, 18, 21, 27]. Endemic dengue has been historically limited to tropical climates, since A. aegypti cannot survive below 8°C [28]. However, single dengue outbreaks initiated by infected travelers have recently been confirmed in temperate regions [10, 29, 30]. Outbreaks are possible in cities with warm summers and mild winters near the northern borders of A. aegypti ranges. We have chosen to study the potential for outbreaks in two groups of U.S. cities that together represent a range of mean temperatures from 20.6°C to 31.8°C: (1) those where the mosquitoes are found, and limited outbreaks have occurred from imported cases in travelers (Los Angeles, Houston, and Phoenix) [31]; and (2) those where the mosquitoes are found, and autochthonous (locally transmitted) outbreaks have occurred (Miami, Brownsville) [31, 32]. The impact of rising temperatures on the risk of dengue outbreaks in the southern United States is an open question. To explore this question, we adapt the mathematical models developed in [7, 33] to include temperature dependence of the EIP and mosquito lifespan parameters. Our model is composed of ordinary differential equations that describe the time evolution of an outbreak of dengue between humans and adult female mosquitoes. We consider a range of scenarios characterized by different temperatures and initial conditions to understand how temperature affects both dengue risk and mitigation. We compute four quantities of interest (QOIs) to evaluate disease invasion potential, transience and severity of outbreaks: (1) the basic reproduction number; (2) the final epidemic size; (3) the timing of the epidemic peak; and (4) the magnitude of the epidemic peak. We compare and evaluate not only the impact of temperature-dependent mosquito lifespan and EIP, but also how the uncertainty in these values impacts disease dynamics and global parameter sensitivity. It then becomes possible to provide a spectrum of possible disease outcomes under a range of climate change scenarios.

Discussion We analyzed a standard mosquito-born disease model to quantify the impact of key temperature-dependent transmission parameters to dengue epidemic outbreaks in three United States cities. We found that all five cities explored (Los Angeles, Houston, Miami, Brownsville, Phoenix) are at risk of a dengue outbreak at their current average temperatures, and that Houston specifically has the highest risk of a large disease burden. With increasing temperatures due to climate change, Los Angeles and Houston could potentially see larger dengue outbreaks, while risk may decrease in Miami and Brownsville. The temperatures in Phoenix may become incompatible with a dengue outbreak. Furthermore, temperatures between 25°C and 30°C yield A. aegypti EIP and lifespan values that are most conducive to disease spread, while both lower and higher temperatures tend to generate smaller or no outbreaks. Of the explored parameters, changes in biting rate and mosquito carrying capacity have the largest influence on the variation of the number of infected humans. While the sensitivity of the majority of parameters do not vary by temperature, as temperature increases up to 30°C, the sensitivity of the EIP and mosquito lifespan for the epidemic peak and final epidemic size tend to decrease, and the sensitivity of the human infectious period tends to increases. Previous studies have supported the assertion that a shorter EIP can result in increased transmission [9, 17]. While our results generally agree with this conclusion, we also show that there is a trade off between EIP and mosquito lifespan. Between 25–30°C, the EIP is small and mosquito lifespan is relatively large, and therefore larger and more quickly moving outbreaks occur at these temperatures. However, the EIP decreases as temperature increases, while adult mosquito lifespan also starts decreasing at 30°C. Our model shows that at around 35°C there is a high probability that even if dengue is introduced, there would be no outbreak. Our sensitivity results also show that total interaction order sensitivity is larger than single order for the final epidemic size, and to a lesser extent, the peak. This indicates that temperature impacts on several parameters may serve as a multiplier to risk changes, having a larger impact than would be indicated by individual parameter sensitivity alone. Our model also indicates where interventions may have the most relative benefit. Overall, our quantities of interest are most sensitive to the biting rate and mosquito carrying capacity. We should then target interventions at these two parameters (repellent to reduce bites, reducing mosquito density). Interestingly, between 25–30°C, sensitivity of model output to EIP and mosquito lifespan decreases, while sensitivity to the human infectious period increases. This indicates that as temperatures increases within this range (the range of highest disease transmission), human interventions (such as quarantine or preventing onward transmission to mosquitoes) may become more important to limiting disease spread. Also, at higher temperatures, the QOIs are much more sensitive to mosquito lifespan, so reducing the mosquito lifespan can provide more impact and push the model into a zone where outbreaks are unlikely. The final epidemic size is more sensitive to the mosquito lifespan while the epidemic peak is more sensitive to the human infectious period. Based on our model and its assumptions, regions of the southern United States, including Houston and Los Angeles, could be at increased risk of dengue as temperature rises. However, our models also show that some regions, such as Phoenix, may have reduced risk if temperatures become too hot to sustain an outbreak. Of the cities explored, Houston has the largest risk, and generally temperatures between 27–31°C see the largest outbreaks in our analysis. There has already been limited dengue transmission in Houston and Florida [38, 52, 53]. As temperatures increase we can expect most cities in the southern United States to have a higher risk for dengue. However, this is not limitless, and as temperatures increase above 31°C, outbreaks get smaller and at 35°C there are no outbreaks. A caveat to our results is that mosquito population dynamics also depend on water availability for their life cycle, and adult lifespans also depend on humidity. So, for example, desert regions such as Phoenix may have less potential due to low humidity. Additionally, human infrastructure and behavior impacts the size and duration of dengue outbreaks. In regions with screens, air conditioning, good sanitation and water infrastructure, and access to mosquito repellent, the potential for outbreaks is decreased. There are several limitations to this work. First, we only consider temperature dependence and not other environmental characteristics including humidity, precipitation, and vegetation. We also only consider the impacts of temperature on the extrinsic incubation period and mosquito lifespan, but other parameters have been shown to be temperature dependent, including the mosquito to human ratio, biting rate, fecundity, egg viability, larval density, development rate, and survival [54–56]. The relationships among these biological parameters, as well as their dependencies on temperature and impacts on disease transmission, are understood to be nonlinear, and in some cases, contradictory. For example, warmer temperatures (within limits) tend to increase fecundity and decrease development times, while decreasing EIP, which tends to increase mosquito abundance and therefore disease transmission. However, warmer temperatures (within limits) can decrease adult mosquito lifespans, which can reduce or even close transmission windows [10, 21, 23]. The temperature dependence in our model and simulations is based on mean temperatures, and does not take into account diurnal fluctuations, which have been shown to impact dengue transmission [10, 57]. Additional modeling studies are needed to incorporate these complexities, and to increase the accuracy of scenario-based projections. Our sensitivity analysis is dependent on the parameter ranges we select which, while based on values from the literature, could be inaccurate. Similarly, we choose from a uniform range across the parameters, while some parameter combinations may be more or less likely than others. In the future, we plan to incorporate humidity and/or precipitation into the models and expand temperature dependence to other parameters. It may also be important in future iterations of this work to incorporate environmental dependent parameters as distributional forms within the model, and to validate against human case counts and mosquito data across a range of temperature and humidity profiles. Our contribution provides a starting place for better capturing the impacts of temperature on multiple parameters and disease dynamics, in addition to static quantities such as the basic reproduction number.

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[1] Url: https://journals.plos.org/climate/article?id=10.1371/journal.pclm.0000115

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