, Austin, Texas, USA.
School of Nursing, The University of Texas at Austin, 1710 Red River St., Austin, TX, 78712, USA.
Health Res Policy Syst. 2021 Oct 30;19(1):134. doi: 10.1186/s12961-021-00783-1.
A variety of policies have been implemented around the world in response to the COVID-19 pandemic. This study originally aimed to identify and compare policy responses of different countries and their effects on the pandemic. It quickly evolved into an identification of the heterogeneity among existing policies and the challenges in making meaningful comparisons of the impact of these policies.
The process of collecting and comparing data from different sources was analysed through inductive thematic analysis to understand the obstacles that impede research designed to compare COVID-19 data and related policies.
We identified the following obstacles: (1) no single reputable source of information and too much noise; (2) a lack of standards for how to measure and report data across countries; (3) variations in the content, implementation and enforcement of policies; and (4) politics, instead of science, leading the efforts in pandemic management.
Heterogeneity in existing policies makes it challenging to compare the effects of various policies worldwide on the COVID-19 pandemic. Our findings call for an automatically updated informatics infrastructure across the globe for collecting and maintaining standardized data from multiple sources. There is a strong need for steadfast utilization of scientific and technical experts to inform and influence health policy. Increased investment in public health and emergency planning is essential to overcome the current pandemic, as well as future public health emergencies. Focused leadership and collaboration from world leaders in a unified mission to decrease the mortality and morbidity of the COVID-19 pandemic is imperative.
为应对 COVID-19 大流行,全球各国实施了多种政策。本研究最初旨在确定和比较不同国家的政策反应及其对大流行的影响。但很快演变成了对现有政策异质性的识别,以及对这些政策影响进行有意义比较的挑战。
通过归纳主题分析对从不同来源收集和比较数据的过程进行分析,以了解阻碍旨在比较 COVID-19 数据和相关政策的研究的障碍。
我们确定了以下障碍:(1) 没有可靠的单一信息来源,噪音太大;(2) 缺乏衡量和报告各国数据的标准;(3) 政策的内容、实施和执行存在差异;(4) 政治而非科学主导着大流行管理工作。
现有政策的异质性使得难以比较全球范围内各种政策对 COVID-19 大流行的影响。我们的研究结果呼吁在全球范围内建立一个自动更新的信息学基础设施,用于从多个来源收集和维护标准化数据。坚定地利用科学和技术专家来为卫生政策提供信息和影响至关重要。增加对公共卫生和应急规划的投资对于克服当前的大流行以及未来的公共卫生紧急情况至关重要。需要来自世界各国领导人的集中领导和合作,以降低 COVID-19 大流行的死亡率和发病率。