论文标题
平衡SARS-COV-2缓解测量的财政和死亡率影响
Balancing Fiscal and Mortality Impact of SARS-CoV-2 Mitigation Measurements
论文作者
论文摘要
流行病带来了人类和财政成本。就进口大流行而言，第一最好的解决方案是限制国家边界以识别和隔离感染的人。但是，如果没有完全抓住机会并且没有预防性干预，则必须选择第二好的选择。在本文中，我们开发了一个微分方程系统，该系统模拟与不同缓解测量相关的财政成本和人为成本。在模拟了几种情况之后，我们得出的结论是，就人类和财政成本而言，牛群的免疫力（或释放大流行）是最糟糕的政策。我们发现，第二好的政策将是在大流行后的前20天建立的严格政策（例如，对大规模测试的物理距离），这将感染的可能性降低了80％。就美国而言，与牧群豁免案相比，这项严格的政策将为纳税人节省超过23.9亿美元的生命和近1708亿美元。
An epidemic carries human and fiscal costs. In the case of imported pandemics, the first-best solution is to restrict national borders to identify and isolate infected individuals. However, when that opportunity is not fully seized and there is no preventative intervention available, second-best options must be chosen. In this article we develop a system of differential equations that simulate both the fiscal and human costs associated to different mitigation measurements. After simulating several scenarios, we conclude that herd immunity (or unleashing the pandemic) is the worst policy in terms of both human and fiscal cost. We found that the second-best policy would be a strict policy (e.g. physical distancing with massive testing) established under the first 20 days after the pandemic, that lowers the probability of infection by 80%. In the case of the US, this strict policy would save more than 239 thousands lives and almost $170.8 billion to taxpayers when compared to the herd immunity case.
