Modelling heterogeneities in disease transmission and predation

模拟疾病传播和捕食的异质性

• 批准号: 238365-2007
• 负责人: Watmough, James
• 金额: $ 1.05万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2011
• 资助国家: 加拿大
• 起止时间: 2011-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=478822
• 关键词: Modelling; heterogeneities; disease; transmission; predation

At the core of every ecological model, whether specified clearly or not, are assumptions about the encounter rates between individuals: between predator and prey, host and parasite, plant and insect or infected and susceptible individuals. Most models assume individuals are identical and interactions are independent. This is clearly not the case; individuals are heterogeneous in almost every aspect: behaviour, physiology, size, age. Despite this, simple models have been very successful: both as theoretical foundations and as applied tools. Heterogeneities, however, are clearly important, and even subtle variations in individuals can lead to interesting and unexpected results. This is especially true in disease control; vaccination models may predict control of the disease in the homogeneous case, but predict bistabilities and hysteresis in the more general case. The objective of this research is to develop and test modelling approaches for specific case studies. The proposed research follows three avenues: development of predictive models for several specific systems, development and analysis of theoretical models for general systems and a study of analytical techniques applicable to disease transmission, spatial spread and predator-prey models.

每一个生态模型的核心，无论是否明确说明，都是关于个体之间相遇率的假设：捕食者和猎物之间，宿主和寄生虫之间，植物和昆虫之间，或者受感染的和易感的个体之间。大多数模型假设个体是相同的，相互作用是独立的。这显然不是事实；个体几乎在每个方面都是异质的：行为、生理、体型、年龄。尽管如此，简单的模型还是非常成功的：无论是作为理论基础还是作为应用工具。然而，异质性显然很重要，即使个体之间的细微差异也可能导致有趣和意想不到的结果。在疾病控制方面尤其如此；疫苗接种模型可以在同质病例中预测疾病的控制，但在更普遍的病例中预测双稳定性和滞后性。本研究的目的是为具体案例研究开发和测试建模方法。提出的研究遵循三个途径：为几个特定系统开发预测模型，为一般系统开发和分析理论模型，以及研究适用于疾病传播、空间传播和捕食者-猎物模型的分析技术。