A computational modeling framework for COVID-19 vaccination

COVID-19 疫苗接种的计算模型框架

• 批准号: 10376956
• 负责人: Jin Wang
• 金额: $ 12.26万
• 依托单位: UNIVERSITY OF TENNESSEE CHATTANOOGA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10376956
• 关键词: 2019-nCoV; Address; Advisory Committees; Attention; Businesses; COVID-19; COVID-19 vaccination; Case Study; Centers for Disease Control and Prevention (U.S.); Characteristics; Clinical Research; Collaborations; Communicable Diseases; Complement; Complex; Computer Models; Computer Simulation; Country; County; Coupled; Data; Data Analytics; Data Set; Development; Differential Equation; Economic Factors; Economic Models; Economics; Epidemic; Epidemiologist; Epidemiology; Evolution; Foundations; Future; Goals; Government Agencies; Growth; Guidelines; Health; Immunization Programs; Intervention; Investigation; Joints; Knowledge Discovery; Machine Learning; Mathematics; Mission; Modeling; Persons; Phase; Policy Developments; Public Health; Public Health Administration; Research; Resistance; Route; SARS-CoV-2 transmission; SARS-CoV-2 variant; Scheme; Schools; Science; Solid; Techniques; Tennessee; Theoretical Studies; Unemployment; United States National Institutes of Health; Vaccination; Vaccines; Validation; computer framework; disorder prevention; dynamic system; economic impact; economic indicator; experience; experimental study; health economics; improved; infectious disease model; innovation; interdisciplinary collaboration; interest; knowledge base; mathematical analysis; mathematical learning; mathematical model; member; novel; pandemic disease; professor; simulation; success; transmission process; vaccine efficacy

Project Summary/Abstract Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains a global pandemic at present. Quantitative research is urgently needed to clarify the impacts of the current vaccination campaign on the pandemic evolution and economic growth, and to guide future policy development. The overall objective of this proposal is to establish a new computational modeling framework for an investigation of the COVID-19 vaccination campaign in the US, and to incorporate real data to assess the impacts of COVID-19 vaccination on public health and the economy. To achieve this objective, the team will pursue three specific aims: (1) Modeling the transmission and spread of COVID-19 under the impact of vaccination; (2) Modeling the economic impact of COVID-19 vaccination; (3) Conducting a case study for the Chattanooga region in the state of Tennessee. The proposed research is significant because it will incorporate detailed characteristics and potential limitations of the current vaccination campaign (such as the vaccine efficacy, phased allocation schemes, public resistance to vaccination, and vaccine breakthrough due to new variants of SARS- CoV-2) into a sophisticated modeling framework, which will enable us to make more accurate forecasts on the progression and long-term evolution of the pandemic. As such, the project is expected to advance the current understanding of COVID-19 transmission and to quantify the interaction between epidemic spreading, economic growth, and disease prevention and intervention under the impact of COVID-19 vaccination, all of which are important for the control and management of the pandemic. The approach is innovative in the development of a computational framework that integrates novel mechanistic and machine learning models and that connects the epidemic and economic aspects of COVID-19. The innovation of this project is also reflected by the integration of sophisticated computational modeling, rigorous mathematical analysis, intensive numerical simulation, and detailed data validation. The project represents an interdisciplinary collaboration among an applied and computational mathematician with long-term interest in infectious disease modeling (Wang), an epidemiologist with extensive working experiences at CDC and a current member of the regional COVID-19 task force (Heath), a business and management professor with a background in public heath (Mullen), and a statistician with expertise in machine learning and biomedical data analytics (Ma). The success of this project will not only build a solid knowledge base for the complex transmission dynamics of SARS-CoV-2 and the health and economic impacts of COVID-19 vaccination, but also provide important guidelines for the government agencies and public health administrations in pandemic management and policy development.

项目摘要/摘要 冠状病毒病2019年(新冠肺炎)，由严重急性呼吸综合征冠状病毒2引起 非典冠状病毒(SARS-CoV-2)目前仍是一种全球大流行。迫切需要定量研究来澄清 当前疫苗接种运动对大流行演变和经济增长的影响，以及 引导未来政策发展。这项提议的总体目标是建立一个新的 美国新冠肺炎疫苗接种活动调查的计算模型框架， 并纳入真实数据，以评估新冠肺炎疫苗接种对公众健康和 经济舱。为了实现这一目标，团队将追求三个具体目标：(1)为 疫苗接种影响下新冠肺炎的传播与扩散；(2)经济建模 接种新冠肺炎疫苗的影响；(3)对查塔努加地区进行案例研究 田纳西州。拟议的研究具有重要意义，因为它将纳入详细的特征和 当前疫苗接种活动的潜在限制(如疫苗效力、分阶段分配 方案，公众对疫苗接种的抵抗力，以及由于SARS新变种而实现的疫苗突破- CoV-2)集成到一个复杂的建模框架中，这将使我们能够做出更准确的预测 关于大流行的进展和长期演变。因此，该项目有望取得进展 目前对新冠肺炎传播的认识与量化疫情之间的相互作用 新冠肺炎冲击下的传播、经济增长与疾病预防干预 疫苗接种，所有这些对控制和管理大流行都很重要。方法是 在开发计算框架方面具有创新性，该框架集成了新的机械和 机器学习模型，并将新冠肺炎的流行病和经济方面联系起来。这个 该项目的创新还体现在集成了复杂的计算建模， 严谨的数学分析、密集的数值模拟和详细的数据验证。该项目 表示应用数学家和计算数学家之间的跨学科协作 长期对传染病建模感兴趣(王)，一位工作广泛的流行病学家 在疾病预防控制中心的经验和目前的地区新冠肺炎特别工作组(Heath)成员，一家企业和 管理学教授，有公共卫生背景(马伦)，统计学家，有专业知识 机器学习和生物医学数据分析(MA)。该项目的成功不仅将建立一个 SARS-CoV-2复杂传播动力学与健康和健康的坚实知识基础 新冠肺炎疫苗接种的经济影响，也为政府提供了重要的指导方针 各机构和公共卫生行政部门在大流行管理和政策制定方面的合作。