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 冠状病毒疾病2019年（COVID-19），由严重的急性呼吸综合症冠状病毒2引起 （SARS-COV-2）目前仍然是全球大流行。迫切需要进行定量研究以澄清 当前疫苗接种运动对大流行进化和经济增长的影响，以及 指导未来的政策制定。该提案的总体目的是建立一个新的 调查美国COVID-19疫苗接种活动的计算建模框架， 并合并实际数据以评估COVID-19疫苗接种对公共卫生和公共卫生的影响 经济。为了实现这一目标，团队将追求三个具体目标：（1）建模 在疫苗接种的影响下，Covid-19的传播和传播； （2）对经济建模 COVID-19疫苗接种的影响； （3）为查塔努加地区进行案例研究 田纳西州。拟议的研究很重要，因为它将结合详细的特征和 当前疫苗接种运动的潜在局限性（例如疫苗功效，分阶段分配 由于SARS的新变体，方案，公众对疫苗接种的抵抗以及疫苗突破 COV-2）进入一个复杂的建模框架，这将使我们能够进行更准确的预测 关于大流行的进展和长期演变。因此，该项目有望进步 当前对COVID-19传播的理解并量化流行病之间的相互作用 在Covid-19的影响下，传播，经济增长以及预防疾病和干预措施 疫苗接种，所有这些对于控制和管理大流行都是重要的。方法是 在整合新机械和 机器学习模型，并连接了Covid-19的流行病和经济方面。这 该项目的创新也反映了复杂的计算建模的整合， 严格的数学分析，密集的数值模拟和详细的数据验证。项目 代表应用和计算数学家之间的跨学科合作 对传染病建模（Wang）的长期兴趣，这是一名经常工作的流行病学家 CDC的经验以及区域Covid-19特遣队（Heath）的现任成员，企业和 具有公共荒地背景（Mullen）背景的管理教授，以及具有专业知识的统计学家 机器学习和生物医学数据分析（MA）。该项目的成功不仅会建立一个 SARS-COV-2和健康和健康的复杂传播动力学的可靠知识库和 COVID-19疫苗接种的经济影响，但也为政府提供了重要的指南 大流行管理和政策制定的机构和公共卫生管理部门。