Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom.
PLoS Biol. 2024 Nov 7;22(11):e3002864. doi: 10.1371/journal.pbio.3002864. eCollection 2024 Nov.
Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology in humans remains unclear. Here, we used a multilevel mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015. These estimated infection histories allowed us to reconstruct historical seasonal influenza patterns in humans and to investigate how influenza incidence varies over time, space, and age in this population. We estimated median annual influenza infection rates to be approximately 19% from 1968 to 2015, but with substantial variation between years; 88% of individuals were estimated to have been infected at least once during the study period (2009 to 2015), and 20% were estimated to have 3 or more infections in that time. We inferred decreasing infection rates with increasing age, and found that annual attack rates were highly correlated across all locations, regardless of their distance, suggesting that age has a stronger impact than fine-scale spatial effects in determining an individual's antibody profile. Finally, we reconstructed each individual's expected antibody profile over their lifetime and inferred an age-stratified relationship between probability of infection and HI titre. Our analyses show how multi-strain serological panels provide rich information on long-term epidemiological trends, within-host processes, and immunity when analysed using appropriate inference methods, and adds to our understanding of the life course epidemiology of influenza A/H3N2.
人类在其一生中会经历多次流感感染，从而产生复杂多样的免疫史。尽管实验和定量分析已经提高了我们对定义个体抗体库的免疫过程的理解，但这些宿主内过程如何与人类群体水平的流感流行病学相关联仍不清楚。在这里，我们使用一个多层次的数学模型，对来自 2009 年至 2015 年重复血清样本的 67683 次血凝抑制（HI）测定值，对来自中国广州的 1130 个人的抗体动力学和个体终身流感 A/H3N2 感染史进行联合推断。这些估计的感染史使我们能够重建人类历史季节性流感模式，并研究在该人群中流感发病率如何随时间、空间和年龄而变化。我们估计，1968 年至 2015 年期间，每年的流感感染率约为 19%，但各年之间存在很大差异；估计有 88%的人在研究期间（2009 年至 2015 年）至少感染过一次，有 20%的人在这段时间内估计感染了 3 次或更多次。我们推断感染率随年龄的增长而降低，并且发现无论其距离如何，所有地点的年攻击率都高度相关，这表明年龄对确定个体的抗体特征的影响比细粒度的空间效应更强。最后，我们重建了每个人在其一生中的预期抗体特征，并推断了感染概率和 HI 滴度之间的年龄分层关系。我们的分析表明，当使用适当的推断方法对多株血清学面板进行分析时，它们如何提供有关长期流行病学趋势、宿主内过程和免疫的丰富信息，并增加了我们对流感 A/H3N2 生命历程流行病学的理解。
