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社会接触和原始抗原性错误在塑造季节性流感免疫的年龄模式中的作用。

The role of social contacts and original antigenic sin in shaping the age pattern of immunity to seasonal influenza.

机构信息

Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom.

出版信息

PLoS Comput Biol. 2012;8(10):e1002741. doi: 10.1371/journal.pcbi.1002741. Epub 2012 Oct 25.

Abstract

Recent serological studies of seasonal influenza A in humans suggest a striking characteristic profile of immunity against age, which holds across different countries and against different subtypes of influenza. For both H1N1 and H3N2, the proportion of the population seropositive to recently circulated strains peaks in school-age children, reaches a minimum between ages 35-65, then rises again in the older ages. This pattern is little understood. Variable mixing between different age classes can have a profound effect on disease dynamics, and is hence the obvious candidate explanation for the profile, but using a mathematical model of multiple influenza strains, we see that age dependent transmission based on mixing data from social contact surveys cannot on its own explain the observed pattern. Instead, the number of seropositive individuals in a population may be a consequence of 'original antigenic sin'; if the first infection of a lifetime dominates subsequent immune responses, we demonstrate that it is possible to reproduce the observed relationship between age and seroprevalence. We propose a candidate mechanism for this relationship, by which original antigenic sin, along with antigenic drift and vaccination, results in the age profile of immunity seen in empirical studies.

摘要

最近对人类季节性流感 A 的血清学研究表明,针对年龄的免疫具有显著特征,这在不同国家和不同流感亚型中都成立。对于 H1N1 和 H3N2,对最近流行株呈血清阳性的人群比例在学龄儿童中达到峰值,在 35-65 岁之间达到最低,然后在老年再次上升。这种模式还不太清楚。不同年龄组之间的可变混合会对疾病动态产生深远影响,因此是该模式的明显候选解释,但使用多种流感株的数学模型,我们发现基于社交接触调查混合数据的年龄相关传播本身并不能解释观察到的模式。相反,人群中血清阳性个体的数量可能是“原始抗原性失误”的结果;如果一生中的第一次感染主导了随后的免疫反应,我们证明可以重现观察到的年龄与血清阳性率之间的关系。我们提出了一种解释这种关系的候选机制,即原始抗原性失误,以及抗原漂移和疫苗接种,导致了经验研究中观察到的免疫年龄特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/3486889/a7cc2765a1eb/pcbi.1002741.g001.jpg

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