Camera Gabriele, Gioffré Alessandro
Economic Science Institute, Chapman University, One University dr., Orange, CA 92866, United States of America.
DSE, University of Bologna, Italy.
J Math Econ. 2021 Dec;97:102552. doi: 10.1016/j.jmateco.2021.102552. Epub 2021 Jul 18.
The sudden appearance of the SARS-CoV-2 virus and the onset of the COVID-19 pandemic triggered extreme and open-ended "lockdowns" to manage the disease. Should these drastic interventions be the blueprint for future epidemics? We construct an analytical framework, based on the theory of random matching, which makes explicit how epidemics spread through economic activity. Imposing lockdowns by assumption not only prevents contagion and reduces healthcare costs, but also disrupts income-generation processes. We characterize how lockdowns impact the contagion process and social welfare. Numerical analysis suggests that protracted, open-ended lockdowns are generally suboptimal, bringing into question the policy responses seen in many countries.
严重急性呼吸综合征冠状病毒2(SARS-CoV-2)病毒的突然出现以及新型冠状病毒肺炎(COVID-19)大流行的爆发引发了极端且无明确期限的“封锁”措施以应对该疾病。这些严厉的干预措施是否应成为未来疫情的蓝本?我们基于随机匹配理论构建了一个分析框架,该框架明确了疫情如何通过经济活动传播。假设实施封锁不仅能预防传染并降低医疗成本,还会扰乱创收过程。我们描述了封锁如何影响传染过程和社会福利。数值分析表明,长期、无明确期限的封锁通常并非最优选择,这使许多国家采取的政策应对措施受到质疑。