Stay at home to stay safe: Effectiveness of stay-at-home orders in containing the COVID-19 pandemic

• 成果类型: Article
• 署名作者: Wang, Guihua
• 署名单位: University of Texas System; University of Texas Dallas
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.13685
• 发表日期: 2022
• 页码: 2289-2305
• 关键词: Causal Inference; COVID-19 pandemic; health care

摘要

Since the outbreak of the COVID-19 pandemic, the effectiveness of stay-at-home orders implemented in many states in the United States has been the subject of ongoing debate. Whereas proponents believe these orders help reduce person-to-person contact and therefore the spread of the pandemic, opponents argue these orders are unnecessary and ineffective. In this study, we use eight states that did not implement the orders as a control group and six neighboring states that did implement them as a treatment group to estimate the effectiveness of stay-at-home orders. We find that although residents in both groups were staying at home even before the implementation of any order, these orders reduced the number of new COVID-19 cases by 7.6%. To understand the mechanisms behind these results, we compare the mobility of residents in the control and treatment groups over time. We find stay-at-home orders significantly reduced residents' mobility at grocery stores and pharmacies, transit stations, workplaces, and retail and recreation locations. The results of this study are useful to policymakers in conducting cost-benefit analyses of back-to-work plans versus stay-at-home policies and deciding whether to implement, extend, lift, or reimplement stay-at-home orders amid a pandemic such as COVID-19. Our results are also useful to researchers because we highlight the importance of correcting for potential selection issues. As we illustrate in this study, ignoring potential selection issues would lead to the wrong conclusion that stay-at-home orders increase the number of new COVID-19 cases.