Predicting seasonal dynamics of UK mosquito vectors across urban and rural gradients

预测英国城市和农村梯度蚊媒的季节性动态

• 批准号: 2108190
• 金额: --
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2108190
• 关键词: Predicting; seasonal; dynamics; UK; mosquito

Understanding how urban and rural gradients alter mosquito temporal abundance in a way that is likely to cause outbreaks of mosquito-borne disease (e.g. West Nile virus) is central to predicting the impact and management of diseases. Environmental drivers (such as rainfall, temperature, evaporation, competition and predation) that vary along urban to rural gradients, affect development, fecundity, survival and therefore abundance of mosquitoes. Spatial variability in environmental drivers also affects abundance and phenology of wildlife and human hosts upon which the mosquitoes feed. Whilst spatial and land use gradients have direct effects on pathogen transmission rates, perhaps the most subtle and profound impacts are on vector species phenology and interactions with susceptible hosts. The temporal pattern of female-blood feeding mosquito abundance in relation to the availability of susceptible hosts is a key determinant of whether a mosquito-borne disease can establish and persist in wildlife, humans and domestic animals. The aim of this project is to investigate the role of urban and rural gradients in driving seasonal and spatial variability in mosquito populations and overlap with hosts. The student will develop and analyse a system of state-dependent delayed differential equations in which environmental drivers affect life-history parameters and development lags focusing on UK mosquito species such as Culex pipiens and Culiseta annulata, which are potential vectors of disease. The model will be analysed by extensive mathematical and numerical simulation techniques using a suitable programming language on high performance computing clusters. In addition, the student will validate the models against new and existing temporal datasets using a broad range of statistical techniques. Finally, the student will derive and analyse a mosquito community model to investigate how host availability shapes the likelihood of disease across urban and rural gradients controlling for competition between mosquito species, predation and abiotic drivers.Overall, the research will demonstrate the value of predictive models that help to understand the dynamics of mosquitoes and mosquito-borne diseases.

了解城市和农村的梯度如何改变蚊子的时间丰度，可能会导致蚊媒疾病（如西尼罗河病毒）的爆发是预测疾病的影响和管理的核心。环境驱动因素（如降雨、温度、蒸发、竞争和捕食）沿着城市到农村的梯度而变化，影响蚊子的发育、繁殖力、生存，从而影响蚊子的数量。环境驱动因素的空间变异性也会影响蚊子赖以为生的野生动物和人类宿主的丰度和物候。虽然空间和土地利用梯度对病原体传播率有直接影响，但最微妙和最深刻的影响可能是对病媒物种物候和与易感宿主的相互作用。与易感宿主的可用性有关的雌性吸血蚊子丰度的时间模式是蚊子传播的疾病是否可以在野生动物，人类和家畜中建立和持续存在的关键决定因素。该项目的目的是调查城市和农村梯度在推动蚊子种群的季节和空间变异以及与宿主重叠方面的作用。学生将开发和分析一个依赖于状态的延迟微分方程系统，其中环境驱动因素影响生活史参数和发展滞后，重点是英国蚊子物种，如库蚊和库利塞塔annulata，这是潜在的疾病载体。将在高性能计算集群上使用适当的编程语言，通过广泛的数学和数值模拟技术对该模型进行分析。此外，学生将使用广泛的统计技术来验证新的和现有的时间数据集的模型。最后，学生将推导和分析蚊子群落模型，以研究宿主可用性如何影响城市和农村梯度中疾病的可能性，控制蚊子物种，捕食和非生物驱动因素之间的竞争。总体而言，该研究将展示预测模型的价值，有助于了解蚊子和蚊媒疾病的动态。