论文标题
案件死亡比率为什么会引起误导：基于个人和人口的死亡率估计以及影响它们的因素
Why case fatality ratios can be misleading: individual- and population-based mortality estimates and factors influencing them
论文作者
论文摘要
在流行期间计算死亡率的不同方式产生了截然不同的结果，尤其是在当前的Covid-19大流行期间。我们既制定生存概率模型，也是相关的感染持续时间依赖的SIR模型，以定义动态死亡率的个体和基于人群的估计。影响不同死亡率估计的动态的关键参数是孵育期和个人在确认感染之前被感染的时间。我们强调，这些比率均未通过经常被误解的病例死亡比率（CFR）准确地表示，迄今为止，死亡人数除以迄今为止已确认的感染病例的总数。使用有关最近的SARS-COV-2爆发的数据，我们估计并比较不同的动态死亡率比例并突出其差异。通过我们的建模，我们提出了更多系统的方法，以确定流行病爆发期间的死亡率比率，并讨论对数据中的混淆效果和不确定性的敏感性。
Different ways of calculating mortality ratios during epidemics have yielded very different results, particularly during the current COVID-19 pandemic. We formulate both a survival probability model and an associated infection duration-dependent SIR model to define individual- and population-based estimates of dynamic mortality ratios. The key parameters that affect the dynamics of the different mortality estimates are the incubation period and the time individuals were infected before confirmation of infection. We stress that none of these ratios are accurately represented by the often misinterpreted case fatality ratio (CFR), the number of deaths to date divided by the total number of confirmed infected cases to date. Using data on the recent SARS-CoV-2 outbreaks, we estimate and compare the different dynamic mortality ratios and highlight their differences. Informed by our modeling, we propose more systematic methods to determine mortality ratios during epidemic outbreaks and discuss sensitivity to confounding effects and uncertainties in the data.
