five

Acellular pertussis vaccines effectiveness over time: A systematic review, meta-analysis and modeling study

收藏
NIAID Data Ecosystem2026-03-10 收录
下载链接:
https://figshare.com/articles/dataset/Acellular_pertussis_vaccines_effectiveness_over_time_A_systematic_review_meta-analysis_and_modeling_study/6589154
下载链接
链接失效反馈
官方服务:
资源简介:
Background Acellular pertussis vaccine studies postulate that waning protection, particularly after the adolescent booster, is a major contributor to the increasing US pertussis incidence. However, these studies reported relative (ie, vs a population given prior doses of pertussis vaccine), not absolute (ie, vs a pertussis vaccine naïve population) efficacy following the adolescent booster. We aim to estimate the absolute protection offered by acellular pertussis vaccines. Methods We conducted a systematic review of acellular pertussis vaccine effectiveness (VE) publications. Studies had to comply with the US schedule, evaluate clinical outcomes, and report VE over discrete time points. VE after the 5-dose childhood series and after the adolescent sixth-dose booster were extracted separately and pooled. All relative VE estimates were transformed to absolute estimates. VE waning was estimated using meta-regression modeling. Findings Three studies reported VE after the childhood series and four after the adolescent booster. All booster studies reported relative VE (vs acellular pertussis vaccine-primed population). We estimate initial childhood series absolute VE is 91% (95% CI: 87% to 95%) and declines at 9.6% annually. Initial relative VE after adolescent boosting is 70% (95% CI: 54% to 86%) and declines at 45.3% annually. Initial absolute VE after adolescent boosting is 85% (95% CI: 84% to 86%) and declines at 11.7% (95% CI: 11.1% to 12.3%) annually. Interpretation Acellular pertussis vaccine efficacy is initially high and wanes over time. Observational VE studies of boosting failed to recognize that they were measuring relative, not absolute, VE and the absolute VE in the boosted population is better than appreciated.
创建时间:
2018-06-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作