Background Estimates of excess deaths provide critical intelligence on the impact of population health threats including seasonal respiratory infections, pandemics and environmental hazards. Timely estimates of excess deaths can inform the response to COVID-19. However, access to timely mortality data is challenging due to the time interval between the death occurring and the date the death is registered and available for analysis (‘registration interval’). Development Using data from the New South Wales, Australia, Births Deaths and Marriages Registry, we developed a Poisson regression model that estimated near-complete weekly counts, for a given week of death, from partially-complete death registration counts. A 10-weeks lag was considered, and a 2-year baseline of historical registration intervals was used to correct lag weeks. Application Validation of estimated counts found that the root-mean-square error (as a percentage of mean observed near-complete registrations) was less than 7% for lag week 3, and <5% for lag weeks 4–9. We incorporated this method utilizing an existing rapid weekly mortality surveillance system. Counts corrected for registration interval replaced observed values for the most recent weeks. Excess death estimates, based on corrected counts, were within 1.2% of near-complete counts available 9 weeks from the end of the analysis period. Conclusions This study demonstrates a method for estimating recent death counts to correct for registration intervals. Estimates obtained at a 3-week lag were acceptable, while those at greater than 3 weeks were optimal.

中文翻译：

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开发登记间隔校正模型，以加强 COVID-19 大流行期间的超额全因死亡率监测


背景 超额死亡人数的估计提供了有关人口健康威胁影响的关键情报，包括季节性呼吸道感染、大流行病和环境危害。及时估计超额死亡人数可以为应对 COVID-19 提供信息。然而，由于死亡发生与死亡登记并可用于分析的日期（“登记间隔”）之间的时间间隔，因此难以及时获取死亡率数据。开发 使用来自澳大利亚新南威尔士州出生死亡和婚姻登记处的数据，我们开发了一个泊松回归模型，该模型从部分完成的死亡登记计数中估计给定一周死亡人数的近乎完整的每周计数。考虑了 10 周的滞后，并使用历史注册间隔的 2 年基线来纠正滞后周。应用程序对估计计数的验证发现，滞后第 3 周的均方根误差（作为观察到的平均接近完成注册的百分比）小于 7%，滞后第 4-9 周的均方根误差（占观察到的平均接近完成注册的百分比）小于 <5%。我们利用现有的每周快速死亡率监测系统整合了这种方法。针对配准间隔校正的计数替换了最近几周的观测值。基于校正计数的超额死亡估计值在分析期结束后 1.2 周可用的接近完整计数的 9% 以内。结论 本研究展示了一种估计近期死亡人数以校正登记间隔的方法。在 3 周滞后获得的估计值是可以接受的，而在 3 周以上的估计值是最佳的。