Modelling vector-borne disease epidemic risks using forward climate projections

在媒介传播疾病领域已经做了大量工作。从这里开始的工作可以用来建立感兴趣的病媒传播疾病(如寨卡病毒或登革热)的模型。这是一个非常频繁的研究领域，因此这些疾病的模型是可靠的，并已被证明可以做出合理的现实世界预测。还对依赖气候的蚊子种群模型进行了研究[3，4]。这些模型的复杂性各不相同，包括温度、湿度和降雨量等参数，以提供蚊子数量的前瞻性预测。这些模型可用于该项目，并嵌入上述流行病学模型，以创建可研究气候变化的流行病风险的系统。这些模型被用来估计疾病的繁殖数量和模拟暴发动态，但不用于估计早期病例产生流行病的风险。IER经常被检查，因为它是流行病学中非常标准的结果，并被广泛应用于许多研究[5]，特别是那些没有考虑气候对流行病风险影响的研究。IER通常是使用嵌入流行病学模型中的人口模型来计算的，如上所述。然而，在CER方面所做的工作很少。CER已经在基本的宿主-媒介模型中进行了检查，但这只考虑了不同的死亡率(而不是不同的蚊子数量)[6]。关于CER的研究不使用气候变化前瞻性预测，而是侧重于一年中当地气候条件的变化。这项研究非常符合该领域的更广泛背景，因为关于CER的工作很少，而且还没有使用真实世界气候预测的工作。本项目旨在回答流行病风险和病媒传播疾病领域的几个问题。在气候变化的情况下，媒介传播的疾病更有可能发生吗？气候变化是否一致地增加了媒介传播疾病大规模暴发的风险，或者是否存在风险可能降低的地理区域？高风险地区和低风险地区的分布情况如何？其他需要回答的问题包括，IER是流行病风险的合适近似值，还是需要计算CER？这两个理论量能否与实际有用的暴发风险指标相关联，例如暴发超过一定病例数量的概率？当气候模拟的初始条件不同时，给定地区的流行病风险有多大变化？是否存在疫情风险持续较高或持续较低的地方？本研究无论在内容上还是在更广泛的目标上都与EPSRC密切相关。内容是数学流行病学领域，其中将使用新的方法来构建预测媒介传播疾病暴发风险的数学框架。该项目还延伸到物理科学(由于气候变化数据)，与环境变化和全球不确定因素共存。将特别重视与外部伙伴和整个科学界交流研究成果。研究领域；全球不确定性、LWEC[与环境变化共存]、数学科学、物理科学外部合作伙伴；科罗拉多州立大学和美国国家大气研究中心

A large amount of work has been done in the field of vector-borne diseases. Work from here can be used to build models for vector-borne diseases of interest (such as Zika virus or Dengue fever). This is a very frequently researched areaand so models of these diseases are robust and have been shown to make sensible real-world predictions. Studies have also been done on climate dependent mosquito population models [3,4]. These models vary in their complexity and include parameters such as temperature, humidity and rainfall to provide forward projections for the population of mosquitoes. Such models can be used in this project and embedded within the aforementioned epidemiological models to create systems where climate varying epidemic risks can be studied. These models have been used to estimate the reproduction number of a disease and to simulate outbreak dynamics but not to estimate the risk that early cases generate an epidemic. The IER is frequently examined because it is a very standard result in epidemiology and is widely used in many studies [5], particularly those in which climate effects on epidemic risks are not accounted for. The IER is oftencomputed using a population model embedded inside an epidemiological model as detailed above. However, there is very little work done on the CER. The CER has been examined in a basic host-vector model but this only allows for varyingdeath rates (and not varying population of mosquitoes) [6]. Studies on the CER do not use climate change forward projections, and instead focus on local change in climatic conditions over the course of a year. This research fits well into thebroader context of the field because very little work has been done on the CER with none having been done using real-world climate projections.This project aims to answer several questions in the field of epidemic risk and vector-borne diseases. Are vector-borne diseases more likely under a changing climate? Is it the case that climate change uniformly increases the risk of largeoutbreaks of vector-borne diseases occurring or are there geographical areas where the risk is likely to decrease? What is the distribution of regions that are high and low risk? Other questions to be answered include, is the IER a suitable approximation for the epidemic risk or does the CER need to be computed? Can these two theoretical quantities be related to practically useful outbreak risk metrics, such as the probability of an outbreak exceeding a certain number of cases? How much variation is there in epidemic risk in a given region when the initial conditions for the climate simulations are varied? Do there exist places where the epidemic risk is consistently high or consistently low?This research closely relates to the EPSRC in both content and wider goals. The content is in the field of mathematical epidemiology where novel methodologies will be used to construct a mathematical framework for predicting the outbreakrisk of vector-borne diseases. This project also extends to the physical sciences (due to climate change data), living with environmental change and global uncertainties. Particular emphasis will be placed on communicating research outcomes with both the external partner and the scientific community as a whole. There is also potential for public outreach and generating awareness of the topic.Research areas; Global uncertainties, LWEC [Living With Environmental Change], Mathematical Sciences, Physical SciencesExternal Partner; Colorado State University, and National Center for Atmospheric Research, USA