The presence of serum antibodies is a biomarker of past infection. Instead of seroclassification aimed at measuring seroprevalence a population sample of serum antibody levels may be used to estimate the incidence of seroconversion. This article expands an earlier study into seroincidence estimation, employing models of the seroresponse that include probability of escaping infection, as well as nonexponential decay kinetics and different sources of noise. As previously, a constant force of infection is assumed. When the seroconversion rate is low, a substantial fraction of the population may not be old enough to have experienced any seroconversions, causing underestimation of seroconversion rates that may be substantial at young ages. A correction is given that can be shown to remove such age dependent bias. Simulation studies show that the updated models provide accurate estimates of seroconversion rates, but also that the presence of noise, when unaccounted for, may introduce considerable bias, especially at low (< 0.1/yr) seroconversion rates and young ages. The revised serocalculator scripts can be used to update the R package “seroincidence.”

中文翻译：

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传染病血清转化率的估算：年龄和噪音的影响。

血清抗体的存在是过去感染的生物标志。代替旨在测量血清阳性率的血清分类，可以使用血清抗体水平的总体样本来估计血清转化的发生率。本文使用血清反应模型扩展了对血清事件估计的早期研究，该模型包括逃逸感染的可能性，非指数衰减动力学和不同噪声源。如前所述，假定感染力恒定。当血清转化率较低时，很大一部分人口可能还不够老而没有经历过任何血清转化，导致低估了可能在年轻时就大量发生的血清转化率。给出了可以消除这种与年龄有关的偏见的校正。仿真研究表明，更新后的模型可以准确估算出血清转化率，但是，如果无法说明噪声的存在，则可能会引入相当大的偏差，尤其是在血清转化率（<0.1 / yr）和低龄的年轻人中。修订后的serocalculator脚本可用于更新R包“ seroincidence”。