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

项目摘要 这个项目开发、评估和模拟了一个尖端的模型，该模型反映了 新冠肺炎大流行及其政策应对。该模型有四个原创功能：第一，它允许 感染和经济结果之间的双向互动。这些都很重要，因为即使 新冠肺炎大流行从根本上说是一个公共卫生问题，必须说明 流行病及其政策对策影响经济，进而影响经济影响。 健康，包括精神健康。其次，它将政策构建成一个解释地缘社会传播的模型 因为SARS-CoV-2病毒是通过与他人的接触传播的，而一个地区的政策决定会影响 这个国家的其他地方。第三，它允许仅通过不完美的代理来衡量发病率， 这对于在美国大流行早期对病毒流行进行建模尤为重要 在可预见的未来，世界上许多地方也是如此。最后，该模型考虑了不同的影响 跨人口群体，这一点至关重要，因为大流行对 不同的人口群体(例如，按年龄、性别、种族、族裔和生活安排)。这部作品 扩展了早期的试点项目，这些项目开发了具有第一和第二功能的模型。一旦完成， 模型将使确定最佳的经济和健康结果成为可能，包括感染和 死亡率，这是本可以实现的，以及对那些最好的情况产生的政策 情景结果。它将使人们有可能找出实际政策偏离最佳政策的方式 政策。它还将使人们有可能严格量化偏离 总体上和针对特定人口群体的最佳政策。除了了解以下方面： 政策和结果本可以改进，作为未来疫情和大流行的教训 估计可以量化疫苗接种率低于群体免疫水平的成本。该模型可以是 适用于不同的国家和跨国分析，其特点是适用于公众 更普遍的健康危机，如阿片类药物的流行。将该模型应用于其他流行病的能力将 允许决策者对不同疫情以及同一疫情的影响进行“比较和对比” 在不同的地点使用共同的方法。此外，该项目还实施了几个结构较差的项目 分析，记录新冠肺炎大流行对健康和劳动力市场的影响以及政策 对它的回应。这项工作将在政策制定者权衡和 衡量公共卫生应对措施的有效性，将有助于确定要纳入我们的 模型，并将帮助我们确保定性模拟结果在一定范围内是稳健的 参数估计。

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.