Modelling vector-borne disease epidemic risks using forward climate projections

使用前瞻性气候预测对媒介传播疾病流行风险进行建模

• 批准号: 2431727
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2431727
• 关键词: Modelling; vector; borne; disease; epidemic

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

在病媒传染疾病领域已做了大量工作。从这里开始的工作可用于构建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强大的，并已被证明可以做出合理的现实世界预测。还对气候依赖的蚊子种群模型进行了研究[3，4]。这些模型的复杂程度各不相同，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。这些模型可用于本项目，并嵌入上述流行病学模型中，以创建可以研究气候变化流行病风险的系统。这些模型已被用于估计疾病的繁殖数量和模拟爆发动态，但不能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，并被广泛用于许多研究[5]，特别是那些没有考虑气候对流行病风险的影响的研究。IER通常使用嵌入在流行病学模型中的人口模型来计算，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（而不是不同的蚊子种群）[6]。关于CER的研究不使用气候变化前瞻性预测，而是侧重于一年中气候条件的局部变化。这项研究很好地融入了该领域的更广泛的背景，因为很少有工作已经做了CER没有使用现实世界的气候预测。该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，病媒传播的疾病是否更有可能发生？气候变化是否一致地增加了病媒传播疾病大规模爆发的风险，或者是否存在风险可能降低的地理区域？高风险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是否是流行病风险的适当近似值，或者CER是否需要计算？这两个理论量是否与实际有用的疫情风险指标（如疫情超过一定病例数的概率）相关？当气候模拟的初始条件变化时，给定地区的流行病风险有多大变化？是否存在流行病风险一直很高或一直很低的地方？这项研究在内容和更广泛的目标方面与EPSRC密切相关。内容是在数学流行病学领域，新的方法将被用来构建一个数学框架，预测媒介传播疾病的爆发风险。该项目还扩展到物理科学（由于气候变化数据），生活在环境变化和全球不确定性中。将特别强调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;美国科罗拉多州立大学和国家大气研究中心