Directly measuring evidence of influenza infections is difficult, especially in low surveillance settings such as sub-Saharan Africa. Using a Bayesian model, we estimated unobserved infection times and underlying antibody responses to influenza A/H3N2 using cross-sectional serum antibody responses to four strains in children aged 24-60 months. Among the 242 individuals, we estimated a variable seasonal attack rate and found that most children had at least one infection before two years of age. Our results are consistent with previously published high attack rates in children. The modelling approach highlights how cross-sectional serological data can be used to estimate epidemiological dynamics.

中文翻译：

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使用横断面血清学数据估计儿童季节性流感发病率和抗体动力学。

直接衡量流感感染的证据很困难，尤其是在撒哈拉以南非洲等监测不力的环境中。使用贝叶斯模型，我们使用横断面血清抗体对 24-60 个月大的儿童的四种毒株的反应来估计未观察到的感染时间和对甲型 H3N2 流感的潜在抗体反应。在 242 人中，我们估计了可变的季节性发病率，发现大多数儿童在两岁之前至少感染过一次。我们的结果与之前发表的儿童高发病率一致。建模方法强调了如何使用横截面血清学数据来估计流行病学动态。