Spatio-temporal dynamics of plague vectors in Madagascar: using population genetics and landscape scale modelling to inform disease reduction strategi

许多新出现的疾病是人畜共患疾病（从动物传染给人），在低收入国家，人的接触程度通常较高。鼠疫是最臭名昭著的人畜共患疾病之一，已经导致了几次大流行。今天，马达加斯加是人类鼠疫病例的热点地区，约占世界每年病例的40%。人畜共患流行病学周期涉及黑鼠、Rattus Rattus和两种跳蚤。在2017年大规模爆发肺鼠疫之后，人们对旨在减少鼠疫发病率的战略的兴趣增加，其中一种选择是控制老鼠。然而，控制老鼠的地点和时间，以及不同的控制选择如何影响跳蚤动力学和疾病传播仍不清楚。目前缺乏关于马达加斯加异质景观中跳蚤时空动态和扩散的详细知识，但这对我们理解鼠疫流行病学和预测疾病风险变化至关重要。遗传和基因组数据可以提供种群连通性的重要信息。大鼠种群表现出随地形起伏而增加的弱遗传结构。然而，寄主和寄生虫的遗传结构并不总是一致的，也没有对马达加斯加跳蚤种群遗传学进行景观尺度的研究。为了帮助管理决策，需要在预测建模框架中将景观特征对鼠和跳蚤种群连通性影响的新信息与当地种群动态信息结合起来。该项目将结合先进的统计分析、种群遗传学和建模，利用现有数据和样本：(1)研究跳蚤丰度如何受到微生境和气候条件的影响，(2)对这两种跳蚤进行景观遗传学研究，(3)使用基于个体的建模方法来了解老鼠和跳蚤的景观动态以及不同控制制度的影响。该模型将在RangeShifter中实现，它集成了种群动态、扩散行为和遗传学，并可用于模拟空间明确景观的场景。本项目适合具有分子生态学或种群生态学背景，对空间生态学、疾病生态学、景观遗传学感兴趣，并具有较强的数字技能的学生。该学生将与马达加斯加巴斯德研究所密切合作。学生将接受全面的多学科培训，将最先进的实验室技能和生态和遗传数据的统计分析与计算建模技能相结合。不同项目组成部分的相对重要性将取决于学生的兴趣。

Many emerging diseases are zoonotic (transmitted from animal to human), with human exposure typically higher in low income countries. Plague is one of the most infamous zoonoses, having been responsible for several pandemics. Today, Madagascar is a hot-spot for human plague cases, with approximately 40% of the world's annual cases. The zoonotic epidemiological cycle involves the black rat, Rattus rattus, and two species of flea. Following a large outbreak of pneumonic plague in 2017, there is increased interest in strategies aimed at reducing plague incidence, with rat control one option. However, where and when to control rats, and how different control options may impact on flea dynamics and disease transmission is still unclear.Detailed knowledge of flea spatio-temporal dynamics and dispersal in the heterogeneous landscapes of Madagascar is lacking, but critical for our understanding of plague epidemiology and predictions of changing disease risk. Genetic and genomic data can give important information on population connectivity. Rat populations show weak genetic structure that increases with topographic relief. However, concordance between host and parasite genetic structure is not always found and no landscape-scale study of flea population genetics in Madagascar has been conducted. To aid management decisions, new information on the impact of landscape features on population connectivity of both rats and fleas needs to be combined with information on local population dynamics in a predictive modelling framework.This project will combine advanced statistical analyses, population genetics and modelling, using existing data and samples to (1) examine how flea abundance is influenced by microhabitat and climatic conditions, (2) conduct a landscape genetic study of the two flea species and (3) use individual based modelling approaches to understand the landscape dynamics of rats and fleas and the impact of different control regimes. The modelling will be implemented in RangeShifter, which integrates population dynamics, dispersal behaviour and genetics, and can be used to simulate scenarios on spatially explicit landscapes.The project will suit a student with a background in molecular ecology or population ecology, who has interests in spatial ecology, disease ecology, landscape genetics, and who has strong numerical skills. The student will be expected to work closely with the Institut Pasteur de Madagascar. The student will be given a thorough multidisciplinary training, integrating state of the art laboratory skills and statistical analysis of ecological and genetic data with computational modelling skills. The relative importance of the different project components will depend on the interests of the student.