Mathematical Modeling and Scientific Computing for Infectious Disease Research

项目摘要/摘要 新出现和再次出现的传染病是巨大的健康和经济负担。 在世界各地。新冠肺炎大流行突显了复杂机制之间的差距 关于疾病传播和传播以及我们目前的知识和干预策略。几个关键问题 问题，如新变种的出现，疫苗迟疑的后果， 环境传播、潜在健康状况和行为的影响以及预测 疾病传播的原理，与新冠肺炎有关，适用于多种传染病， 目前只有部分和不充分的解决方案。数学和计算研究可以 提供对这些挑战的关键见解，并提高我们对疾病传播、传播、 和进步。这项提议的总体目标是建立一个新的数学和 传染病计算建模框架，以新冠肺炎为重点，集成了新的 数学建模、广泛的数值模拟和严格的数据验证。要做到这一点 目标，我们将追求三个具体目标：(1)建立传染病传播动力学模型 疾病；(2)模拟潜在健康状况的影响；以及(3)模拟 传染病。这项拟议的研究意义重大，因为预计它将大大推进 我们目前对新冠肺炎和许多其他传染性疾病相关复杂动力学的理解 这可能会改进我们目前在疾病控制和暴发管理方面的做法。 该方法在开发新的数学模型和高级计算方面具有创新性 解决传染病研究迫切需要的技术，在综合数学、 计算，和流行病学方法，并在本科生参与 通过循序渐进的学习过程进行真实的研究。该项目代表了一种跨学科的 一位应用和计算数学家与一位公共卫生科学家之间的合作 在一起工作了几年。每年5名本科生，总共15名 超过三年，将得到该项目的支持。这个项目的成功将为我们奠定坚实的知识基础 基地复杂的传染病动态，将为公共卫生提供重要的指导方针 在疾病管理和政策制定方面，将创建一个新的平台 聘请本科生科研人员，加强院校研究环境。

Project Summary/Abstract Emerging and reemerging infectious diseases represent a tremendous health and economic burden throughout the world. The COVID-19 pandemic underscores the gap between the complex mechanisms of disease transmission and spread and our current knowledge and intervention strategies. Several critical issues such as the emergence of new variants, the consequence of vaccine hesitancy, the presence of environmental transmission, the impact of underlying health conditions and behaviors, and the prediction of disease spread, which are related to COVID-19 and applicable to a wide variety of infectious diseases, are only partially and inadequately addressed at present. Mathematical and computational studies can provide key insights into these challenges and improve our understanding of disease transmission, spread, and progression. The overall objective of this proposal is to establish a new mathematical and computational modeling framework for infectious diseases, with a focus on COVID-19, that integrates novel mathematical modeling, extensive numerical simulation, and rigorous data validation. To achieve this objective, we will pursue three Specific Aims: (1) Modeling the transmission dynamics of infectious diseases; (2) Modeling the impact of underlying health conditions; and (3) Modeling the spatial spread of infectious diseases. The proposed research is significant because it is expected to substantially advance our current understanding of the complex dynamics associated with COVID-19 and many other infectious diseases, which will potentially improve our current practice in disease control and outbreak management. The approach is innovative in the development of novel mathematical models and advanced computational techniques to address pressing needs for infectious disease research, in the integration of mathematical, computational, and epidemiological methods, and in the involvement of undergraduate students for authentic research through a progressive learning process. The project represents an interdisciplinary collaboration between an applied and computational mathematician and a public health scientist who have worked with each other for several years. A cohort of 5 undergraduate students per year, for a total of 15 over three years, will be supported by the project. The success of this project will build a solid knowledge base for the complex dynamics of infectious diseases, will provide important guidelines for the public health administrations in disease management and policy development, and will create a novel platform for engaging undergraduate researchers and strengthening the institutional research environment.