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从日本哨兵监测数据重建 COVID-19 的年龄结构病例数:一项建模研究。

Reconstructing the age-structured case count of COVID-19 from sentinel surveillance data in Japan: A modeling study.

机构信息

Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Graduate School of Medicine, Kyoto University, Kyoto, Japan.

出版信息

Int J Infect Dis. 2024 Nov;148:107223. doi: 10.1016/j.ijid.2024.107223. Epub 2024 Aug 30.

Abstract

OBJECTIVES

To reconstruct age-structured case counts of COVID-19 using sentinel reporting, which replaced universal reporting of COVID-19 from May 2023 in Japan.

METHODS

Using COVID-19 sentinel data stratified by discrete age groups in selected prefectures and referring to universal case count data up to May 8, 2023, we fitted a statistical model to handle weekly growth rates as a function of age and time so as to convert sentinel data to case counts after cessation of universal reporting.

RESULTS

The age distribution of cases in sentinel reporting was significantly biased toward younger age groups compared to universal reporting. When comparing the epidemic size of the 9th wave (May 8 to September 18, 2023) to the 8th wave (October 3, 2022 to April 10, 2023), using the wave-on-wave ratio of total cumulative sentinel cases led to a significant underestimation of the wave-on-wave in Tokyo (0.975, vs 1.461 by universal reporting) and Okinawa (1.299, vs 1.472). The estimates of growth rates, scaling factors between universal and sentinel cases, and expected universal case count showed robustness to changes in the ending week of the data period.

CONCLUSION

Our model quantified COVID-19 dynamics, comparably to universal reporting that ended in May 2023, enabling detailed and up-to-date health burden analysis using sentinel reports. The cumulative incidence was greater than that suggested from sentinel data in Tokyo, Nara, and Okinawa. Per-population burdens among children were particularly high in Osaka and Nara, indicating a strong bias in sentinel reporting toward pediatric cases.

摘要

目的

利用哨点报告重建 COVID-19 的年龄结构病例数,哨点报告自 2023 年 5 月起取代 COVID-19 的全人群报告。

方法

利用选定县的离散年龄组的 COVID-19 哨点数据,并参考截至 2023 年 5 月 8 日的全人群病例数,我们拟合了一个统计模型,将每周增长率作为年龄和时间的函数进行处理,以便在全人群报告停止后将哨点数据转换为病例数。

结果

与全人群报告相比,哨点报告的病例年龄分布明显偏向于年轻年龄组。当比较第 9 波(2023 年 5 月 8 日至 9 月 18 日)和第 8 波(2022 年 10 月 3 日至 2023 年 4 月 10 日)的流行规模时,使用全人群累计哨点病例的波峰比会导致东京(0.975,vs 1.461 为全人群报告)和冲绳(1.299,vs 1.472)的波峰比显著低估。增长率的估计值、全人群和哨点病例之间的缩放因子以及预期的全人群病例数在数据期结束周发生变化时表现出稳健性。

结论

我们的模型定量描述了 COVID-19 的动态,与 2023 年 5 月结束的全人群报告相当,使使用哨点报告能够进行详细和最新的健康负担分析。累积发病率高于东京、奈良和冲绳的哨点数据所显示的水平。大阪和奈良的儿童每人口负担尤其高,表明哨点报告对儿科病例存在强烈偏向。

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