新冠病毒检测和病例数据在循证卫生政策和实践方面的局限性。
Limitations of COVID-19 testing and case data for evidence-informed health policy and practice.
机构信息
Department of Health Research Methods, Evidence and Impact, McMaster University, CRL 2nd Floor, 1280 Main Street West, Hamilton, ON, L8S4K1, Canada.
Department of Anthropology, University of Colorado Boulder, Boulder, CO, USA.
出版信息
Health Res Policy Syst. 2023 Jan 25;21(1):11. doi: 10.1186/s12961-023-00963-1.
BACKGROUND
Coronavirus disease 2019 (COVID-19) became a pandemic within a matter of months. Analysing the first year of the pandemic, data and surveillance gaps have subsequently surfaced. Yet, policy decisions and public trust in their country's strategies in combating COVID-19 rely on case numbers, death numbers and other unfamiliar metrics. There are many limitations on COVID-19 case counts internationally, which make cross-country comparisons of raw data and policy responses difficult.
PURPOSE AND CONCLUSIONS
This paper presents and describes steps in the testing and reporting process, with examples from a number of countries of barriers encountered in each step, all of which create an undercount of COVID-19 cases. This work raises factors to consider in COVID-19 data and provides recommendations to inform the current situation with COVID-19 as well as issues to be aware of in future pandemics.
背景
新冠肺炎（COVID-19）在数月内成为全球大流行。对大流行第一年进行分析后，随后出现了数据和监测方面的差距。然而，政策决策和公众对本国抗击 COVID-19 战略的信任取决于病例数量、死亡人数和其他不熟悉的指标。国际上对 COVID-19 病例的统计存在诸多限制，这使得对原始数据和政策应对措施进行跨国比较变得困难。
目的和结论
本文提出并描述了检测和报告流程中的步骤，并以一些国家为例说明了在每个步骤中遇到的障碍，所有这些都导致了 COVID-19 病例的漏报。这项工作提出了在 COVID-19 数据中需要考虑的因素，并为当前的 COVID-19 情况提供了建议，以及在未来的大流行中需要注意的问题。
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