Multi-scale modeling of infectious diseases in fluctuating environments

波动环境中传染病的多尺度建模

• 批准号: 7901376
• 负责人: Lora Billings
• 金额: $ 26.46万
• 依托单位: MONTCLAIR STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7901376
• 关键词: Communicable Diseases; Computing Methodologies; Data; Disease; Disease model; Environment; Epidemiology; Extinction (Psychology); Health; Immunology; Interdisciplinary Study; Lead; Life; Methods; Modeling; Monitor; Nature; Population; Population Dynamics; Quarantine; Research; Research Proposals; Resources; Schedule; Solutions; System; Systems Biology; Vaccines; Vision; Work; design; disease transmission; disorder control; improved; insight; mathematical model; multi-scale modeling; public health relevance; theories; tool

DESCRIPTION (provided by applicant): The objective of this proposal is to develop new mathematical models of infectious disease transmission that effectively, capture the impact of stochasticity on dynamics and lead to more effective control. The group will study the dynamics of disease spread in fluctuating environments modeled at various population scales. First, the group will develop a new class of stochastic metapopulation models for disease spread, noting the importance of stochastic effects in the dynamics. These models capture new types of solutions that cannot be realized in deterministic models, such as disease extinction. The group proposes to develop new mathematical and computational methods for designing and analyzing this class of models. The group will also model various delivery schedules of vaccines into populations. By assuming limited resources, such as constrained vaccine supply or quarantine-type contact control, the results from these models will lead to practical solutions for experimentalists and poUcy makers. The project will lead to greater insight into the mechanisms that allow a disease to successfully propagate in a population, as well as new mathematical tools to analyze stochastic systems. In our long term vision for this project, the group will contribute new mathematical tools to the field of epidemiology. These tools will be motivated by improved models of real world problems, which lead to better ways to design optimization methods. Our work is driven by real epidemiological threats, is derived from data collected from around the world, and is focused on answering questions that could save lives. There is an excitement about the impact of interdisciplinary research efforts combining mathematical fields, such as nonlinear analysis, stochastic d3Tiamics, and network theory, with systems biology approaches such as population dynamics, epidemiology, and immunology. This proposal describes ways in which modeling can open new research directions in all of these fields. PUBLIC HEALTH RELEVANCE: Noting the collaborative nature of this research proposal, we expect that this project will produce findings that could improve health standards across the world. It may lead to improved methods of disease control and health monitoring.

描述（由申请人提供）：该提案的目的是开发新的传染病传播数学模型，这些模型有效地捕获随机性对动态的影响并导致更有效的控制。该小组将研究以各种种群量表建模的波动环境中疾病传播的动力学。首先，该小组将开发出新的疾病扩散的随机化种群模型，并指出随机效应在动力学中的重要性。这些模型捕获了在确定性模型（例如疾病灭绝）中无法实现的新型解决方案。该小组建议开发新的数学和计算方法，以设计和分析此类模型。该小组还将将疫苗的各种输送时间表建模为种群。通过假设有限的资源，例如受限的疫苗供应或隔离型接触控制，这些模型的结果将为实验者和Poucy制造商提供实用的解决方案。该项目将进一步了解允许疾病在人群中成功传播的机制，以及分析随机系统的新数学工具。在我们对该项目的长期愿景中，该小组将为流行病学领域贡献新的数学工具。这些工具将由改进的现实世界问题模型来激励，这会导致设计优化方法的更好方法。我们的工作是由真正的流行病学威胁驱动的，是从世界各地收集的数据中得出的，并专注于回答可以挽救生命的问题。关于将数学领域的跨学科研究工作的影响（例如非线性分析，随机D3Tiamics和网络理论）与系统生物学方法（例如人群动态，流行病学和免疫学方法）相结合的兴奋。该建议描述了建模可以在所有这些领域打开新的研究方向的方法。公共卫生相关性：注意这项研究建议的协作性质，我们希望该项目将产生可以改善全球健康标准的发现。它可能导致改进的疾病控制和健康监测方法。