Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Campinas, SP, Brazil.
Center for Infectious Disease Modeling and Analysis, School of Public Health, Yale University, New Haven, CT, United States of America.
PLoS One. 2020 Nov 3;15(11):e0241549. doi: 10.1371/journal.pone.0241549. eCollection 2020.
The impact of influenza vaccination is largely measured by estimating vaccine effectiveness (VE), which vary in different seasons. Strain mutations and waning immunity present two key mechanisms affecting VE. We sought to quantify the relative effect of these mechanisms by projecting VE and the reduction of illness due to vaccination. We developed a stochastic age-structured agent-based simulation model of influenza transmission dynamics to encapsulate intraseason waning of immunity post-vaccination, and mutation-induced antigenic distance between circulating strains and vaccine strains. Parameterizing the model with published estimates, we projected the temporal and overall VE during an epidemic season, and estimated the reduction of infection for high (70%) and low (30%) vaccine efficacies to reflect the levels of vaccine-induced protection in randomized control trials. Both temporal and overall VE decreased as the attack rate increased, with lower median values for epidemics starting with strains that were antigenically more distant from vaccine strains. We observed a higher rate of temporal decline with considerably lower median values of the overall VE in the presence of intraseason waning of immunity compared with only the antigenic distance effect. The highest benefit of vaccination in preventing influenza infection was achieved at moderate attack rates in the range of 6%-15%. The results show that even when VE is relatively low in the population and almost negligible for older age groups (i.e., 50+ years), vaccination can still prevent significant illness in high-risk individuals; thereby reducing healthcare resource utilization and economic burden. Our study indicates that early vaccination remains an important strategy for alleviating the burden of seasonal influenza. Policy discussions on optimal timing of vaccination to reduce the effect of intraseason waning of immunity should be considered in the context of strain mutations within the epidemic course.
流感疫苗的效果主要通过估计疫苗效力 (VE) 来衡量，而 VE 在不同季节有所差异。毒株突变和免疫衰减是影响 VE 的两个关键机制。我们试图通过预测 VE 和疫苗接种减少发病来量化这些机制的相对影响。我们开发了一个随机的、基于年龄结构的流感传播动力学代理模拟模型，以包含接种后季节性免疫衰减和循环毒株与疫苗毒株之间抗原差异引起的突变。通过使用已发表的估计值对模型进行参数化，我们预测了流行季节期间的时间和总体 VE，并估计了高（70%）和低（30%）疫苗效力的感染减少量，以反映随机对照试验中疫苗诱导的保护水平。随着发病率的增加，时间和总体 VE 都降低了，而与疫苗株抗原差异较大的毒株引起的流行，其中位值更低。我们观察到，与仅考虑抗原距离效应相比，在存在季节性免疫衰减的情况下，时间衰减率更高，总体 VE 的中位值明显更低。在发病率为 6%-15%的中等水平下，疫苗接种在预防流感感染方面的获益最大。结果表明，即使在人群中的 VE 相对较低，并且对年龄较大的人群（即 50 岁以上）几乎可以忽略不计的情况下，疫苗接种仍然可以预防高危人群的严重疾病，从而减少医疗资源的利用和经济负担。我们的研究表明，早期接种仍然是减轻季节性流感负担的重要策略。在流行过程中考虑到毒株突变，应在考虑到季节性免疫衰减的情况下，讨论接种的最佳时机以降低其影响的政策。
