Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO, United States of America.
Olin School of Business, Washington University in St. Louis, St. Louis, MO, United States of America.
PLoS One. 2020 Dec 22;15(12):e0244174. doi: 10.1371/journal.pone.0244174. eCollection 2020.
With the COVID-19 pandemic infecting millions of people, large-scale isolation policies have been enacted across the globe. To assess the impact of isolation measures on deaths, hospitalizations, and economic output, we create a mathematical model to simulate the spread of COVID-19, incorporating effects of restrictive measures and segmenting the population based on health risk and economic vulnerability. Policymakers make isolation policy decisions based on current levels of disease spread and economic damage. For 76 weeks in a population of 330 million, we simulate a baseline scenario leaving strong isolation restrictions in place, rapidly reducing isolation restrictions for non-seniors shortly after outbreak containment, and gradually relaxing isolation restrictions for non-seniors. We use 76 weeks as an approximation of the time at which a vaccine will be available. In the baseline scenario, there are 235,724 deaths and the economy shrinks by 34.0%. With a rapid relaxation, a second outbreak takes place, with 525,558 deaths, and the economy shrinks by 32.3%. With a gradual relaxation, there are 262,917 deaths, and the economy shrinks by 29.8%. We also show that hospitalizations, deaths, and economic output are quite sensitive to disease spread by asymptomatic people. Strict restrictions on seniors with very gradual lifting of isolation for non-seniors results in a limited number of deaths and lesser economic damage. Therefore, we recommend this strategy and measures that reduce non-isolated disease spread to control the pandemic while making isolation economically viable.
随着 COVID-19 疫情感染数百万人,全球范围内实施了大规模的隔离政策。为了评估隔离措施对死亡、住院和经济产出的影响,我们创建了一个数学模型来模拟 COVID-19 的传播,将限制措施的影响纳入其中,并根据健康风险和经济脆弱性对人口进行细分。政策制定者根据疾病传播和经济损害的当前水平做出隔离政策决策。在 3.3 亿人口中,我们模拟了 76 周的情景,即保持严格的隔离限制,在疫情得到控制后不久,迅速减少对非老年人的隔离限制,然后逐渐放宽对非老年人的隔离限制。我们使用 76 周作为疫苗可用时间的近似值。在基线情景下,有 235724 人死亡,经济收缩 34.0%。如果迅速放松隔离限制,会出现第二次疫情,有 525558 人死亡,经济收缩 32.3%。如果逐渐放松隔离限制,会有 262917 人死亡,经济收缩 29.8%。我们还表明,住院、死亡和经济产出对无症状人群传播的疾病非常敏感。对老年人实施严格限制,并非常缓慢地放宽对非老年人的隔离限制,可将死亡人数和经济损失限制在较小范围内。因此,我们建议采取这种策略和减少非隔离传播的措施来控制大流行,同时使隔离在经济上可行。