识别新冠疫情期间及之后失业趋势的关键指标。
Identifying key indicators of job loss trends during COVID-19 and beyond.
作者信息
Roy Satyaki, Dutta Ronojoy, Ghosh Preetam
机构信息
University of North Carolina, Chapel Hill, USA.
Deep Run High School, Glen Allen, VA, USA.
出版信息
Soc Sci Humanit Open. 2021;4(1):100163. doi: 10.1016/j.ssaho.2021.100163. Epub 2021 May 11.
COVID-19, declared by the World Health Organization as a Public Health Emergency of International Concern, has claimed over 2.7 million lives worldwide. In the absence of vaccinations, social distancing and lockdowns emerged as the means to curb infection spread, with the downside of bringing the world economy to a standstill. In this work, we explore the epidemiological, socioeconomic and demographic factors affecting the unemployment rates of United States that may contribute towards policymaking to contain contagion and mortality while balancing the economy in the future. We identify the ethnic groups and job sectors that are affected by the pandemic and demonstrate that Gross Domestic Product (GDP), race, age group, lockdown severity and infected count are the key indicators of post-COVID job loss trends.
世界卫生组织宣布新冠疫情为国际关注的突发公共卫生事件，它已在全球造成超过270万人死亡。在没有疫苗接种的情况下，社交距离措施和封锁成为遏制感染传播的手段，其负面影响是使世界经济陷入停滞。在这项研究中，我们探讨了影响美国失业率的流行病学、社会经济和人口因素，这些因素可能有助于未来制定政策，在控制疫情传播和死亡率的同时平衡经济。我们确定了受疫情影响的种族群体和就业部门，并证明国内生产总值（GDP）、种族、年龄组、封锁严重程度和感染病例数是新冠疫情后失业趋势的关键指标。
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