Rozenbaum Mark H, Tort Maria J, Capitano Blair, Chapman Ruth, Dillon-Murphy Desmond, Althouse Benjamin M, Cane Alejandro
Pfizer Inc., Collegeville, PA 19426, USA.
PPD™ Evidera™ Health Economics & Market Access, Thermo Fisher Scientific, London W6 8BJ, UK.
Vaccines (Basel). 2025 Jul 29;13(8):805. doi: 10.3390/vaccines13080805.
The number needed to vaccinate (NNV) is a metric commonly used to evaluate the public health impact of a vaccine as it represents the number of individuals that must be vaccinated to prevent one case of disease. Traditional calculations may underestimate vaccine benefits by neglecting indirect effects and duration of protection (DOP), resulting in NNV overestimation. This study evaluated the NNV for the pediatric 20-valent pneumococcal conjugate (PCV20) US immunization program, as compared to PCV13, with a unique approach to NNV. A multi-cohort, population-based Markov model accounting for indirect effects was employed to calculate the NNV of PCV20 to avert a case of pneumococcal disease, invasive pneumococcal disease (IPD), hospitalized non-bacteremic pneumonia (NBP), ambulatory NBP, and otitis media (OM), as well as to prevent antibiotic-resistant cases and antibiotic prescriptions. The mean NNV over a 25-year time horizon to prevent one case of pneumococcal disease was 6, with NNVs of 854 for IPD, 106 for hospitalized NBP, 25 for outpatient NBP, and 9 for OM, 11 for a course of antibiotic, and 4 for resistant disease. The mean NNV per year decreased over time, reflecting the DOP and increasing indirect effects over time. This study presents a novel approach to NNVs and shows that relatively few vaccinations are required to prevent disease. The decrease in NNV over time highlights the necessity of including DOP and indirect effects in NNV calculations, ensuring a more realistic assessment of a vaccine's impact.
需接种疫苗人数(NNV)是一种常用于评估疫苗对公共卫生影响的指标,因为它代表了为预防一例疾病必须接种疫苗的个体数量。传统计算可能会因忽视间接效应和保护持续时间(DOP)而低估疫苗的益处,从而导致NNV被高估。本研究采用独特的NNV计算方法,评估了美国儿科20价肺炎球菌结合疫苗(PCV20)免疫计划相对于PCV13的NNV。采用了一个基于人群的多队列马尔可夫模型,该模型考虑了间接效应,以计算PCV20预防一例肺炎球菌疾病、侵袭性肺炎球菌疾病(IPD)、住院非菌血症性肺炎(NBP)、门诊NBP和中耳炎(OM)的NNV,以及预防抗生素耐药病例和抗生素处方的NNV。在25年的时间范围内,预防一例肺炎球菌疾病的平均NNV为6,IPD的NNV为854,住院NBP的NNV为106,门诊NBP的NNV为25,OM的NNV为9,一个疗程抗生素的NNV为11,耐药疾病的NNV为4。每年的平均NNV随时间下降,反映了DOP以及随着时间推移间接效应的增加。本研究提出了一种计算NNV的新方法,并表明预防疾病所需的疫苗接种相对较少。NNV随时间的下降凸显了在NNV计算中纳入DOP和间接效应的必要性,以确保对疫苗影响进行更现实的评估。