Am J Epidemiol. 2021 Sep 1;190(9):1908-1917. doi: 10.1093/aje/kwab089.
Estimates of the reproductive number for novel pathogens, such as severe acute respiratory syndrome coronavirus 2, are essential for understanding the potential trajectory of epidemics and the levels of intervention that are needed to bring the epidemics under control. However, most methods for estimating the basic reproductive number (R0) and time-varying effective reproductive number (Rt) assume that the fraction of cases detected and reported is constant through time. We explored the impact of secular changes in diagnostic testing and reporting on estimates of R0 and Rt using simulated data. We then compared these patterns to data on reported cases of coronavirus disease 2019 and testing practices from different states in the United States from March 4, 2020, to August 30, 2020. We found that changes in testing practices and delays in reporting can result in biased estimates of R0 and Rt. Examination of changes in the daily numbers of tests conducted and the percentages of patients who tested positive might be helpful for identifying the potential direction of bias. Changes in diagnostic testing and reporting processes should be monitored and taken into consideration when interpreting estimates of the reproductive number of coronavirus disease.
估算新型病原体(如严重急性呼吸系统综合征冠状病毒 2)的繁殖数对于了解传染病的潜在趋势以及控制传染病所需的干预水平至关重要。然而,大多数估计基本繁殖数(R0)和时变有效繁殖数(Rt)的方法都假设检测和报告的病例比例在整个时间段内保持不变。我们使用模拟数据探讨了诊断检测和报告的长期变化对 R0 和 Rt 估计的影响。然后,我们将这些模式与 2020 年 3 月 4 日至 2020 年 8 月 30 日期间美国不同州的新冠肺炎报告病例和检测实践数据进行了比较。我们发现,检测实践的变化和报告的延迟会导致 R0 和 Rt 的估计值出现偏差。对每日进行的检测数量和检测呈阳性的患者比例的变化进行检查,可能有助于确定潜在的偏差方向。在解释新冠肺炎繁殖数的估计值时,应监测和考虑诊断检测和报告过程的变化。