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COVID-19 病例和死亡定义中的偏差:潜在原因和后果。

Biases in COVID-19 Case and Death Definitions: Potential Causes and Consequences.

机构信息

School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada.

出版信息

Disaster Med Public Health Prep. 2022 Dec 12;17:e313. doi: 10.1017/dmp.2022.281.

Abstract

This paper investigates three controversies involving potential causes and consequences of information bias in case and death definitions during the coronavirus disease (COVID-19) pandemic. First, evidence suggests China's surveillance data were biased and misinterpreted by the World Health Organization (WHO), prompting the WHO to advise nations to copy China's lockdowns. China appeared to use narrow diagnostic definitions that undercounted cases and deaths. Second, novel genomic data disseminated during the pandemic without adequate guidance from rigorous epidemiologic studies biased infection control policies in many countries. A novel genomic sequence of a virus is insufficient to declare new cases of a novel disease. Third, media reports of COVID-19 surveillance data in many nations appeared to be biased. Broadened surveillance definitions captured additional information, but unadjusted surveillance data disseminated to the public are not true cases and deaths. Recommendations include clarification of the proper use of diagnostic and surveillance case and death definitions to avoid information bias.

摘要

本文研究了与冠状病毒病(COVID-19)大流行期间病例和死亡定义中信息偏倚的潜在原因和后果相关的三个争议。首先,有证据表明中国的监测数据被世界卫生组织(WHO)误读和曲解,促使 WHO 建议各国效仿中国的封锁措施。中国似乎采用了狭隘的诊断定义,从而少报了病例和死亡人数。其次,大流行期间传播的新型基因组数据在没有严格的流行病学研究提供充分指导的情况下,影响了许多国家的感染控制政策。病毒的新型基因组序列不足以宣布新型疾病的新病例。第三,许多国家对 COVID-19 监测数据的媒体报道似乎存在偏差。扩大监测定义可以捕捉到更多信息,但向公众传播的未经调整的监测数据并非真实的病例和死亡人数。建议包括明确诊断和监测病例和死亡定义的正确使用方法,以避免信息偏倚。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c5f/9947039/8531da603fc2/S1935789322002816_fig1.jpg

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