在混合监测研究中比较现有和新方法来估计病因特异性腹疾病发病率
Maria Garcia Quesada1,2, Alexander Breskin3, James A Platts-Mills4
1Department of Epidemiology, Emory Rollins School of Public Health, Atlanta, GA.
medRxiv : the preprint server for health sciences
|November 26, 2025
概括
准确的传染病发病率估计对于疫苗研究至关重要. 使用个人倾向得分的混合监测对寻求调整的医疗保健减少了偏见,为公共卫生研究提供了一种可靠的方法.
科学领域:
- 流行病学 流行病学
- 生物统计学 生物统计学
- 公共卫生 公共卫生
背景情况:
- 准确的传染病发病率估计对于公共卫生干预,特别是疫苗试验至关重要.
- 混合监控研究将医疗机构数据与社区分母结合起来,需要对寻求医疗保健的行为进行调整,以最大限度地减少偏见.
- 全球健康的肠道 (EFGH) 研究寻求儿童*Shigella*腹的最新发病率估计,以告知疫苗开发.
研究的目的:
- 评估调整寻求医疗保健行为的方法和估计混合监测研究中的不确定性.
- 为了比较不同的统计方法来减少偏差和信任区间覆盖.
- 将这些验证的方法应用于EFGH研究数据.
主要方法:
- 进行了一项模拟研究,以评估各种寻求医疗保健的调整策略.
- 对寻求医疗保健的个人水平倾向得分与边际概率调整进行了比较.
- 用M估计和引导方法来估计不确定性,并与蒙特卡洛区间进行比较.
主要成果:
- 使用个人水平倾向得分的逆值进行调整,与边际概率调整相比,显著减少了偏差.
- 无论是M估计还是启动过程中的95%置信区间,都显示了对模拟场景的充分覆盖.
- 尽管计算成本更高,但M估计在EFGH研究中与启动相比,对调整后的发病率估计产生了更窄的置信区间.
结论:
- 个人水平的倾向得分调整是减少混合监测研究偏差的一种优秀方法.
- 引导式置信区间为混合研究中的不确定性量化提供了M估计的计算效率高的替代方案.
- 这些发现为准备疫苗试验和公共卫生决策提供了可靠的发病率估计方法.
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