Ecological and epidemiological modelling across multiple spatial scales

跨多个空间尺度的生态和流行病学建模

• 批准号: RGPIN-2017-05466
• 负责人: Arino, Julien
• 金额: $ 2.04万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=711432
• 关键词: Ecological; epidemiological; modelling; across; multiple

I propose to consider the formulation and mathematical and computational analysis of coupled mathematical models operating across distinct spatial scales, with each model describing the movement patterns and resulting range of the different species interacting in competition for resources, prey-predator relationships or the transmission of an infectious pathogen. Indeed, when considering interactions between two or more species, it is common that the species involved occupy and move through space in very different ways. For instance, competition for resources can involve migrating and non-migrating species; the range of many predators far exceeds the range of their prey species; and in vector-borne diseases, hosts are typically highly mobile while vectors have very small ranges. It is therefore important to formulate methodologies to deal with these varying ranges. This will be achieved by considering different model types (ordinary or partial differential equations, discrete or continuous Markov chains, network models), each suitable for the description of the range and movement of a given species, with coupling terms to describe local interactions between species. To understand the different types of couplings that can occur, I will work with three examples for which I have access to data. 1. Annual migration of the purple martin (P. subis) between North America and its overwintering site in Brazil. The data for this problem comes from K. Fraser (University of Manitoba). 2. Utilization of a stock of snow crabs (C. opilio) in Atlantic Canada. The fishing fleet divides itself between cooperative and competitive groups. The data for this problem comes from D. Gillis (University of Manitoba). 3. Spread of malaria in and between the Comoros Islands. Through a collaboration with C. Rogier (Service de Santé des Armées, France), I have data on the spread of several strains of P. falciparum, the causative parasite of malaria, between the five islands in the archipelago. Information is also available about human movement between the islands and about vector densities. These examples will require different combinations of model types: discrete and continuous time deterministic in the case of P. subis, continuous time deterministic and stochastic in the case of C. opilio and a combination of discrete and continuous deterministic and stochastic in the case of P. falciparum. From these different examples, I will derive general principles that govern the use and coupling of models of different types. I will consider the mathematical analysis of such multiscale hybrid models and will devise computer code for their computational analysis. This novel interdisciplinary program will train at least 10 HQP and will help reduce the gap between model- and data-based approaches in spatial ecology and epidemiology, providing a firm theoretic background to consider data driven problems in these fields.

我建议考虑在不同空间尺度上运行的耦合数学模型的制定、数学和计算分析，每个模型描述不同物种在资源竞争、猎物-捕食者关系或信息传播中相互作用的运动模式和结果范围。传染性病原体。 事实上，在考虑两个或多个物种之间的相互作用时，所涉及的物种以截然不同的方式占据和移动空间是很常见的，例如，对资源的竞争可能涉及迁徙和非迁徙物种的范围远远超出许多捕食者的范围。其猎物种类的范围；在媒介传播的疾病中，宿主通常具有高度流动性，而媒介的范围非常小。 因此，制定方法来处理这些变化的范围非常重要，这将通过考虑不同的模型类型（常微分方程或偏微分方程、离散或连续马尔可夫链、网络模型）来实现，每种模型都适合描述范围和运动。给定物种，用耦合项来描述物种之间的局部相互作用。 为了了解可能发生的不同类型的耦合，我将使用我有权访问数据的三个示例。 1. 紫马丁鱼（P. subis）每年在北美与其越冬地巴西之间的迁徙 该问题的数据来自 K. Fraser（马尼托巴大学）。 2. 加拿大大西洋地区雪蟹（C. opilio）资源的利用分为合作群体和竞争群体。该问题的数据来自 D. Gillis（马尼托巴大学）。 3. 疟疾在科摩罗群岛内部和之间的传播 通过与 C. Rogier（法国武装部队服务中心）的合作，我获得了几种恶性疟原虫（疟疾寄生虫）菌株在科摩罗群岛之间传播的数据。群岛中的五个岛屿也有关于岛屿之间的人类活动和媒介密度的信息。 这些示例将需要不同的模型类型组合：在 P. subis 的情况下是离散和连续时间确定性的，在 C. opilio 的情况下是连续时间确定性和随机的，在 P 的情况下是离散和连续确定性和随机的组合从这些不同的例子中，我将得出管理不同类型模型的使用和耦合的一般原则，我将考虑这种多尺度混合模型的数学分析，并为其计算分析设计计算机代码。 这个新颖的跨学科项目将培训至少 10 名 HQP，并将有助于缩小空间生态学和流行病学中基于模型和基于数据的方法之间的差距，为考虑这些领域的数据驱动问题提供坚实的理论背景。