Qu Qiubai School of Government, Changzhou University, Changzhou 213159, China.
Institute of Public Agency Administration, Changzhou University, Changzhou 213159, China.
Int J Environ Res Public Health. 2023 Feb 27;20(5):4252. doi: 10.3390/ijerph20054252.
Against the unprecedented outbreaks of the COVID-19 variants, countries have introduced restrictive measures with discretion, ranging from lifting the closure thoroughly to implementing stringent policies, but all together guarding the global public health. Under the changing circumstances, we firstly apply the panel data vector autoregression (PVAR) model, using a sample of 176 countries/territories from 15 June 2021 to 15 April 2022, to estimate the potential associations among the policy responses, the progression of COVID-19 in deaths and vaccination, and medical resources possessed. Furthermore, we use the random effect method and the fixed effect speculation, to examine the determinants of policy variances across regions and over time. Our work has four main findings. Firstly, it showed the existence of a bidirectional relationship between the policy stringency and variables of interest including new daily deaths, the fully vaccinated percentage and health capacity. Secondly, conditional on the availability of vaccines, the sensitivity of policy responses to the death numbers tends to decline. Thirdly, the role of health capacity matters in coexisting with the virus mutation. Fourthly, regarding the variance in policy responses over time, the impact of new deaths tends to be seasonal. As to geographical differences in policy responses, we present the analysis for Asia, Europe, and Africa, and they show different levels of dependencies on the determinants. These findings suggest that bidirectional correlations exist in the complex context of wrestling with the COVID-19, as government interventions exert influence on the virus spread, the policy responses also progress alongside multiple factors evolving in the pandemic. This study will help policymakers, practitioners, and academia to formulate a comprehensive understanding of the interactions between policy responses and the contextualized implementation factors.
面对前所未有的 COVID-19 变种爆发，各国谨慎地采取了限制措施，从彻底解除封锁到实施严格政策不等，但都是为了保护全球公共卫生。在不断变化的情况下，我们首先应用面板数据向量自回归（PVAR）模型，使用 2021 年 6 月 15 日至 2022 年 4 月 15 日期间 176 个国家/地区的样本，来估计政策反应、COVID-19 死亡和疫苗接种进展以及医疗资源之间的潜在关联。此外，我们使用随机效应法和固定效应推断，来检验跨地区和随时间的政策差异的决定因素。我们的工作有四个主要发现。首先，它表明政策严格性与包括新的每日死亡人数、完全接种疫苗的比例和医疗能力在内的相关变量之间存在双向关系。其次，在疫苗供应的前提下，政策反应对死亡人数的敏感性趋于下降。第三，医疗能力的作用在与病毒突变共存中很重要。第四，关于政策反应随时间的变化，新死亡人数的影响具有季节性。至于政策反应的时间差异，新死亡人数的影响往往与季节有关。至于政策反应的地理差异，我们对亚洲、欧洲和非洲进行了分析，它们显示出对决定因素的不同依赖程度。这些发现表明，在应对 COVID-19 的复杂背景下存在双向相关性，因为政府干预对病毒传播产生影响，政策反应也随着大流行中不断演变的多种因素而发展。这项研究将帮助政策制定者、从业者和学术界全面了解政策反应与背景化实施因素之间的相互作用。
