论文标题
评论：关于COVID-19的感染率的已发表研究数据的系统评价和荟萃分析
Comment on: A systematic review and meta-analysis of published research data on COVID-19 infection-fatality rates
论文作者
论文摘要
COVID-19的感染死亡率（IFR）是对政策制定至关重要的疾病影响的措施之一。在这里我们表明，这些估计值的许多研究在科学上是有缺陷的，其原因包括：荒谬的方程，不合理的假设，小样本大小，非代表性的样本（系统偏见）（系统的偏见），不正确的症状定义和不正确的情况（完全不明显的情况）（典型的假设）是典型的，这些情况是典型的，典型的情况是，既有症状，均为易于症状，并且是典型的疾病。有症状的情况。此外，一项被广泛引用的荟萃分析歪曲了原始研究中的某些IFR值，并使研究或研究的信息不当，因此平均结果并非彼此独立。鉴于它们对影响生活和福祉的政策，在面对全球大流行的政策上，这些研究论文缺乏有效性尤其重要。
The infection fatality rate (IFR) of COVID-19 is one of the measures of disease impact that can be of importance for policy making. Here we show that many of the studies on which these estimates are based are scientifically flawed for reasons which include: nonsensical equations, unjustified assumptions, small sample sizes, non-representative sampling (systematic biases), incorrect definitions of symptomatic and asymptomatic cases (identified and unidentified cases), typically assuming that cases which are asymptomatic at the time of testing are the same as completely asymptomatic (never symptomatic) cases. Moreover, a widely cited meta-analysis misrepresents some of the IFR values in the original studies, and makes inappropriate duplicate use of studies, or the information from studies, so that the results that are averaged are not independent from each other. The lack of validity of these research papers is of particular importance in view of their influence on policies that affect lives and well-being in confronting a worldwide pandemic.
