School of Chemical Sciences, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
Sci Rep. 2022 Jun 7;12(1):9379. doi: 10.1038/s41598-022-13748-3.
The increase of COVID-19 breakthrough infection risk with time since vaccination has a clear relationship to the decrease of antibody concentration with time. The empirically-observed dependence on blood IgG anti-receptor binding domain antibody concentration of SARS-CoV-2 vaccine efficacy against infection has a rational explanation in the statistics of binding of antibody to spike proteins on the virus surface, leading to blocking of binding to the receptor: namely that the probability of infection is the probability that a critical number of the spike proteins protruding from the virus are unblocked. The model is consistent with the observed antibody concentrations required to induce immunity and with the observed dependence of vaccine efficacy on antibody concentration and thus is a useful tool in the development of models to relate, for an individual person, risk of infection given measured antibody concentration. It can be used to relate population breakthrough infection risk to the distribution across the population of antibody concentration, and its variation with time.
随着时间的推移，COVID-19 突破性感染风险的增加与抗体浓度的下降有明显的关系。从统计学角度来看，SARS-CoV-2 疫苗对感染的功效与血液 IgG 抗受体结合域抗体浓度有关，这一观察结果有合理的解释，即抗体与病毒表面刺突蛋白的结合会导致阻断与受体的结合：即感染的概率是病毒表面突出的刺突蛋白数量达到临界值的概率。该模型与观察到的诱导免疫所需的抗体浓度以及观察到的疫苗功效与抗体浓度的依赖性一致，因此是开发个体感染风险与测量抗体浓度相关的模型的有用工具。它可以用来将人群突破性感染风险与人群中抗体浓度的分布及其随时间的变化联系起来。
