Institute for Global Health, University College, London, UK.
Int J Health Policy Manag. 2023;12:7036. doi: 10.34172/ijhpm.2022.7036. Epub 2023 Jan 31.
At the start of the coronavirus disease 2019 (COVID-19) pandemic, in the absence of pharmaceutical interventions, countries resorted to containment measures to stem the spread of the disease. In this paper, we have conducted a global study using a sample of 46 countries to evaluate whether these containment measures resulted in unemployment.
We use a difference-in-differences (DID) specification with a heterogenous intervention to show the varying intensity effect of containment measures on unemployment, on a sample of 46 countries. We explain variations in unemployment from January-June 2020 using stringency of containment measures, controlling for gross domestic product (GDP) growth, inflation rate, exports, cases of COVID-19 per million, COVID-19-specific fiscal spending, time fixed effects, region fixed effects, and region trends. We conduct further subset analyses by COVID-cases quintiles and gross national income (GNI) per capita quintiles.
The median level of containment stringency in our sample was 43.7. Our model found that increasing stringency to this level would result in unemployment increasing by 1.87 percentage points (or 1.67 pp, after controlling for confounding). For countries with below median COVID-19 cases and below median GNI per capita, this effect is larger.
Containment measures have a strong impact on unemployment. This effect is larger in poorer countries and countries with low COVID-19 cases. Given that unemployment has profound effects on mortality and morbidity, this consequence of containment measures may compound the adverse health effects of the pandemic for the most vulnerable groups. It is necessary for governments to consider this in future pandemic management, and to attempt to alleviate the impact of containment measures via effective fiscal spending.
在 2019 年冠状病毒病（COVID-19）大流行开始时，由于缺乏药物干预，各国采取了遏制措施来阻止疾病的传播。在本文中，我们使用来自 46 个国家的样本进行了一项全球研究，以评估这些遏制措施是否导致了失业。
我们使用差异中的差异（DID）规范和异质干预来展示遏制措施对失业的不同强度影响，这是在 46 个国家的样本上进行的。我们使用遏制措施的严格程度来解释 2020 年 1 月至 6 月期间的失业变化，同时控制国内生产总值（GDP）增长、通货膨胀率、出口、每百万例 COVID-19 病例、COVID-19 特定财政支出、时间固定效应、地区固定效应和地区趋势。我们通过 COVID-病例五分位数和人均国民总收入（GNI）五分位数进行进一步的子样本分析。
我们样本中的遏制严格程度中位数为 43.7。我们的模型发现，将严格程度提高到这个水平将导致失业率增加 1.87 个百分点（或在控制了混杂因素后增加 1.67 个百分点）。对于 COVID-19 病例和人均 GNI 低于中位数的国家，这种影响更大。
遏制措施对失业有很大的影响。在较贫穷的国家和 COVID-19 病例较少的国家，这种影响更大。由于失业对死亡率和发病率有深远的影响，遏制措施的这种后果可能会使最脆弱群体的大流行的不利健康影响更加复杂。政府在未来的大流行管理中需要考虑到这一点，并通过有效的财政支出来努力减轻遏制措施的影响。
