将基因组数据集成到测试负面设计中,以估计特定系谱的COVID-19疫苗有效性
Kevin C Ma1, Diya Surie1, Natalie Dean2
1National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA.
概括
使用基于时期的血统分配的COVID-19疫苗有效性 (VE) 研究可能会因为错误分类而低估VE差异. 调整值可以减少偏差,但可能会影响精度,需要进行灵敏度分析以获得可靠的结果.
科学领域:
- 病毒学 病毒学
- 流行病学 流行病学
- 免疫学 免疫学 免疫学
背景情况:
- 由于SARS-CoV-2的演变,因此需要持续评估COVID-19疫苗对严重疾病的有效性.
- 测试负面设计 (TND) 研究中的血统分配方法包括基于序列的,基于代理的和基于时间段的方法.
研究的目的:
- 总结不同谱系分配方法的好处,挑战和方法考虑,以估计SARS-CoV-2谱系特定的VE.
- 为了建模出血统错误分类错误对TND研究中VE估计的影响,使用基于周期的与基于序列的分配.
主要方法:
- 在VE TND研究中对血统分配的好处,挑战和方法考虑的审查.
- 确定性建模用于评估血统错误分类对 VE 估计在各种变体出现场景下的影响.
主要成果:
- 基于周期的谱系分配可能低估了由于错误分类而导致的谱系之间的 VE 差异,特别是在长期的共同流通或早期变种接管期间.
- 在基于周期的分析中增加主导性值可以减少偏差,但可能会降低精度或阻止估计.
- 对于基于周期的 VE 研究,建议进行敏感性分析,以评估对不同主导值的稳定性.
结论:
- 使用各种血统分配方法进行的测试负设计研究已经对SARS-CoV-2变种介导的疫苗逃生有了更深入的了解.
- 每个研究设计中固有的偏见各不相同,强调需要仔细的分析考虑,以进行可靠的 VE 估计.
- 确定了可靠估计的原则可能适用于其他具有持续抗原漂移的病原体.
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