Department of Epidemiology of Microbial Diseases, Yale University School of Public Health, New Haven, CT, United States of America.
Center for Neurosciences, Institute of Molecular Medicine, Northwell Health, Manhasset, New York, United States of America.
PLoS One. 2021 Aug 18;16(8):e0253843. doi: 10.1371/journal.pone.0253843. eCollection 2021.
Knowing the true infected and symptomatic case fatality ratios (IFR and CFR) for COVID-19 is of high importance for epidemiological model projections. Early in the pandemic many locations had limited testing and reporting, so that standard methods for determining IFR and CFR required large adjustments for missed cases. We present an alternate approach, based on results from the countries at the time that had a high test to positive case ratio to estimate symptomatic CFR.
We calculated age specific (0-69, 70-79, 80+ years old) time corrected crude symptomatic CFR values from 7 countries using two independent time to fatality correction methods. Data was obtained through May 7, 2020. We applied linear regression to determine whether the mean of these coefficients had converged to the true symptomatic CFR values. We then tested these coefficients against values derived in later studies as well as a large random serological study in NYC at that time.
The age dependent symptomatic CFR values accurately predicted the percentage of the population infected as reported by two random testing studies in NYC. They also were in good agreement with later studies that estimated age specific IFR and CFR values from serological studies and more extensive data sets available later in the pandemic.
We found that for regions with extensive testing it is possible to get early accurate symptomatic CFR coefficients. These values, in combination with an estimate of the age dependence of infection, allows symptomatic CFR values and percentage of the population that is infected to be determined in similar regions with limited testing.
了解 COVID-19 的真实感染和有症状病例病死率（IFR 和 CFR）对于流行病学模型预测非常重要。在大流行早期，许多地方的检测和报告都有限，因此，确定 IFR 和 CFR 的标准方法需要对漏诊病例进行大量调整。我们提出了一种替代方法，该方法基于当时具有高检测阳性病例比的国家的结果来估计有症状的 CFR。
我们使用两种独立的死亡时间校正方法，从 7 个国家计算了特定年龄（0-69、70-79、80+ 岁）的时间校正粗有症状 CFR 值。数据获取时间截至 2020 年 5 月 7 日。我们应用线性回归来确定这些系数的平均值是否已收敛到真实的有症状 CFR 值。然后，我们将这些系数与当时在纽约市进行的后来的研究以及一项大型随机血清学研究得出的值进行了比较。
年龄相关的有症状 CFR 值准确地预测了纽约市两项随机检测研究报告的感染人群比例。它们也与后来的研究非常吻合，这些研究通过血清学研究和大流行后期更广泛的数据集中估计了年龄特异性 IFR 和 CFR 值。
我们发现，对于广泛进行检测的地区，有可能获得早期准确的有症状 CFR 系数。这些值与感染的年龄依赖性估计值结合使用，可以在检测有限的类似地区确定有症状的 CFR 值和感染人群的比例。
