Metapopulations and infectious disease dynamics

摘要：背景：元种群是生态学中的一个基本概念，在此基础上，种群的定植和灭绝奠定了种群在景观中的持久性。元种群动力学在保护和控制和消除传染病方面具有重要的应用。来自SARS-CoV-2大流行的遗传和流行病学数据完美地说明了这一理论，病毒谱系的出现以及它们在世界各地相互关联的人群中的频繁引入和灭绝。在一系列环境中观察到的病毒谱系的共循环和频繁的重新引入，假设了元种群动力学是犬狂犬病流行动力学的基础。我们已经展示了狂犬病感染的疫源地是如何从传播和扩散的个体差异中产生的，以及由此产生的谱系是如何具有持久性的特征模式的。来自区域狂犬病消除规划的证据也说明了元种群动态如何促成持久性并对协调管理产生影响。研究目标：利用个体水平的传播和扩散数据和病毒谱系多样性的基因组数据来参数化狂犬病动力学的元种群模型。应用该模型在空间异质性景观中探索病毒循环模式。使用RABV-GLUE（狂犬病病毒序列和元数据管理平台）将模型结果与来自世界各地的基因组数据进行比较。将模型细化为空间显式景观，以便研究在国家和区域尺度上消除控制措施的最佳部署。研究监测偏差如何影响疾病动态推断，特别是应如何加强监测以改进疾病消除规划。培训成果：数学模型的开发和参数化，以及从基于个体的模型到元种群模型的一系列建模框架的应用经验。具备计算机模拟和统计推断的计算和统计能力；了解作为国家和区域狂犬病控制规划一部分的常规监测和加强监测，包括病毒测序；掌握有效的沟通和数据可视化技能，以传达来自数学模型和遗传及流行病学数据的信息，并向其他科学家、决策者、从业人员和公众提供信息

Studentship strategic priority area: Mathematical BiologyKeywords: Transmission, Lineages, Genomics, Inference, StatisticsAbstract: Background: Metapopulations are a fundamental concept in ecology whereby colonization and extinctions underpin the persistence of populations across landscapes. Metapopulation dynamics have important applications in conservation and in the control and elimination of infectious diseases. Genetic and epidemiological data from the SARS-CoV-2 pandemic perfectly illustrate this theory with the emergence of viral lineages and their frequent introductions and extinctions within interconnected populations around the world. Metapopulation dynamics have been hypothesized to underlie the endemic dynamics of canine rabies, with co-circulation of viral lineages and frequent reintroductions observed in a range of settings. We have shown how foci of rabies infection arise from individual variation in transmission and dispersal and how resulting lineages have characteristic patterns of persistence. Evidence from regional rabies elimination programmes also illustrate how metapopulation dynamics contribute to persistence and have implications for coordinated management. Aims of studentship: To parameterize a metapopulation model of rabies dynamics using individual level data on transmission and dispersal and genomic data on viral lineage diversity Apply this model across spatially heterogeneous landscapes to explore patterns of viral circulation. Compare model outcomes with genomic data from around the world using RABV-GLUE, a platform for curation of rabies viral sequences and metadata. Refine model to spatially explicit landscapes so as to investigate the optimal deployment of control efforts for elimination at national and regional scales. Examine how surveillance biases affect inference of disease dynamics and specifically how surveillance should be enhanced to improve disease elimination programmes. Training outcomes: Development and parameterization of mathematical models and experience in application of a range of modelling frameworks from individual-based to metapopulation models. Computational and statistical competence for undertaking computer simulations and statistical inference Understanding of viral sequencing methods and phylodynamics, with skills gained in the integration and synthesis of genomic and epidemiological data Understanding of routine and enhanced surveillance as part of national and regional rabies control programmes including viral sequencing Effective communication and data visualization skills for conveying information from mathematical models and genetic and epidemiological data and to inform other scientists, policy makers, practitioners and the general public