The Health and Economic Impacts of COVID-19 and Policy Responses

COVID-19 的健康和经济影响及政策应对

• 批准号: 10425626
• 负责人: Bruce A Weinberg
• 金额: $ 44.46万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10425626
• 关键词: 2019-nCoV; Accounting; Address; Affect; Age; Area; COVID-19; COVID-19 pandemic; Cell Nucleus; Cities; Communities; Complex; Consumption; Costs and Benefits; Country; County; Data; Developing Countries; Diffusion; Disease Outbreaks; Econometric Models; Economics; Ensure; Environment; Epidemic; Ethnic Origin; Evolution; Future; Gender; Geography; Health; Health Care Costs; Herd Immunity; Incidence; Infection; Literature; Living Arrangement; Location; Masks; Measurement; Measures; Mental Health; Modeling; Nursing Homes; Outcome; Performance; Pilot Projects; Policies; Policy Maker; Policy Making; Prevalence; Proxy; Public Health; Race; Research; Rest; Risk; Running; Structure; Testing; Time; Update; Vaccination; Virus; Work; cost; data modeling; econometrics; economic cost; economic impact; economic outcome; experience; frontier; gender difference; health economics; improved; infection rate; interest; latent infection; mortality; novel; opioid epidemic; pandemic disease; response; simulation

Project Summary This project develops, estimates, and simulates a cutting-edge model of the health and economic impacts of the COVID-19 pandemic and policy responses to it. The model has four original features: First, it allows for two-way interactions between infections and economic outcomes. These are important because even though the COVID-19 pandemic is fundamentally a matter of public health, it is essential to account for how the pandemic and the policy responses to it affect the economy and how, in turn, the economic impacts affect health, including mental health. Second, it builds policies into a model that accounts for geosocial spread because the SARS-CoV-2 virus is spread through contact with others and policy decisions in one area affect the rest of the country. Third, it allows for incidence rates that are measured only through imperfect proxies, which is particularly important for modeling the prevalence of the virus early in the pandemic in the U.S. as well as in many parts of the world for the foreseeable future. Lastly, the model accounts for disparate impacts across demographic groups, which is critical given that the pandemic has had dramatically different effects on different demographic groups (e.g., by age, gender, race, ethnicity, and living arrangements). This work extends earlier pilot projects that develop a model with the first and second features. Once complete, the model will make it possible to identify the best sets of economic and health outcomes, including infections and mortality, that could have been achieved and the policies that would have produced to those best-case scenario outcomes. It will make it possible to identify the ways in which actual policies deviated from the best policies. It will also make it possible to rigorously quantify the health and economic costs of deviating from the optimal policies overall and for specific demographic groups. In addition to understanding the ways in which policies and outcomes could have been improved as lessons for future outbreaks and pandemics, the estimates can quantify the cost of vaccination rates stalling beneath herd immunity levels. The model can be applied to different countries and to cross-country analysis, and its features are intended to apply to public health crises more generally, such as the opioid epidemic. The ability to apply the model to other epidemics will allow policy makers to “compare and contrast” the impacts of different epidemics as well as the same epidemic in different locations using a common approach. Additionally, the project conducts several less structured analyses that document the health and labor market impacts of the COVID-19 pandemic and the policy responses to it. This work will generate results of interest in their own right as policy makers weigh and measure the efficacy of public health responses, will help identify key phenomena to incorporate into our model, and will help us to ensure that the qualitative simulation results are robust to a range of plausible parameter estimates.

项目概要 该项目开发、估计和模拟了一个关于健康和经济影响的尖端模型 COVID-19 大流行及其应对政策。该模型有四个原始特征：首先，它允许 感染与经济结果之间的双向相互作用。这些很重要，因为即使 COVID-19 大流行从根本上来说是一个公共卫生问题，因此必须考虑到 大流行及其应对政策会影响经济，以及经济影响又如何影响 健康，包括心理健康。其次，它将政策构建成一个考虑地理社会传播的模型 因为 SARS-CoV-2 病毒是通过与他人接触传播的，并且某一地区的政策决策会影响 该国其他地区。第三，它允许仅通过不完美的代理来测量发病率， 这对于模拟美国大流行早期病毒的流行情况尤其重要 在可预见的未来，世界许多地方都会如此。最后，该模型考虑了不同的影响 鉴于这一流行病对不同人口群体产生了截然不同的影响，这一点至关重要 不同的人口群体（例如，按年龄、性别、种族、民族和生活安排）。这部作品 扩展了早期的试点项目，开发具有第一个和第二个特征的模型。一旦完成， 模型将能够确定最佳的经济和健康结果，包括感染和 死亡率，本可以实现的目标以及针对最佳情况将产生的政策 情景结果。它将能够确定实际政策偏离最佳政策的方式 政策。它还将使严格量化偏离标准所造成的健康和经济成本成为可能。 总体上和针对特定人口群体的最佳政策。除了了解其中的方法之外 政策和成果本来可以得到改进，作为未来疫情和流行病的教训， 估计可以量化疫苗接种率低于群体免疫水平的成本。模型可以是 适用于不同国家和跨国分析，其功能旨在适用于公众 更普遍的健康危机，例如阿片类药物的流行。将模型应用于其他流行病的能力将 让政策制定者能够“比较和对比”不同流行病以及同一流行病的影响 在不同地点使用通用方法。此外，该项目还进行了一些结构性较差的活动 记录了 COVID-19 大流行和政策对健康和劳动力市场影响的分析 对此的回应。当政策制定者权衡和考虑时，这项工作本身就会产生令人感兴趣的结果。 衡量公共卫生应对措施的有效性，将有助于确定关键现象，并将其纳入我们的研究中 模型，并将帮助我们确保定性模拟结果对于一系列合理的情况是稳健的 参数估计。