Mathematical Modeling and Scientific Computing for Infectious Disease Research

传染病研究的数学建模和科学计算

• 批准号: 10793008
• 负责人: Jin Wang
• 金额: $ 33.12万
• 依托单位: UNIVERSITY OF TENNESSEE CHATTANOOGA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-22 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10793008
• 关键词: Address; Algorithms; Behavior; COVID-19; COVID-19 pandemic; Chronic Disease; Clinical; Clinical Research; Collaborations; Communicable Diseases; Complex; Computational Technique; Computer Models; Computing Methodologies; Data; Development; Diffusion; Disease; Disease Management; Disease Outbreaks; Economic Burden; Educational process of instructing; Emerging Communicable Diseases; Environment; Epidemic; Epidemiologic Methods; Epidemiology; Equation; Guidelines; Health; Health Planning; Infectious Diseases Research; Institution; Intervention; Knowledge; Learning; Liquid substance; Long COVID; Mathematics; Methods; Mission; Modeling; Morbidity - disease rate; Outcome; Persons; Policy Developments; Population; Population Dynamics; Prevalence; Process; Public Health; Public Health Administration; Reaction; Research; Research Personnel; Route; SARS-CoV-2 infection; SARS-CoV-2 transmission; Scientist; Solid; System; Techniques; Theoretical Studies; United States National Institutes of Health; Universities; Vaccination; Validation; Variant; Vulnerable Populations; Work; cohort; computer studies; disease transmission; disorder control; experience; experimental study; health management; improved; infectious disease model; innovation; insight; interdisciplinary collaboration; interest; knowledge base; mathematical methods; mathematical model; mortality; novel; outbreak response; prevent pandemics; public health relevance; scaffold; scientific computing; simulation; success; tool; transmission process; undergraduate research experience; undergraduate student; vaccine hesitancy

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.

项目概要/摘要 新出现和重新出现的传染病带来了巨大的健康和经济负担 全世界。 COVID-19 大流行凸显了复杂机制之间的差距 疾病传播和传播以及我们当前的知识和干预策略。几个关键的 诸如新变种的出现、疫苗犹豫的后果、病毒的存在等问题 环境传播、潜在健康状况和行为的影响以及预测 疾病传播，与 COVID-19 相关并适用于多种传染病， 目前仅部分得到充分解决。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、 和进展。该提案的总体目标是建立一个新的数学和 传染病计算建模框架，重点关注 COVID-19，集成了新颖的 数学建模、广泛的数值模拟和严格的数据验证。为了实现这一目标 为了实现这一目标，我们将追求三个具体目标：（1）对传染病的传播动态进行建模 疾病； (2) 对潜在健康状况的影响进行建模； (3) 模拟空间扩散 传染病。拟议的研究意义重大，因为预计它将大大推进 我们目前对与 COVID-19 和许多其他传染病相关的复杂动态的了解 疾病，这将有可能改善我们目前在疾病控制和疫情管理方面的做法。 该方法在开发新颖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求的技术，融合了数学、 计算和流行病学方法，以及本科生的参与 通过渐进的学习过程进行真实的研究。该项目代表了一个跨学科的 应用和计算数学家与公共卫生科学家之间的合作 彼此合作了几年。每年 5 名本科生，总共 15 名 三年内，将得到该项目的支持。该项目的成功将建立扎实的知识 传染病复杂动态的基础，将为公共卫生提供重要指导 疾病管理和政策制定方面的主管部门，并将创建一个新的平台 吸引本科研究人员并加强机构研究环境。