Nikas Ariel, Ahmed Hasan, Zarnitsyna Veronika I
Emory University School of Medicine, Department of Microbiology and Immunology, Atlanta, Georgia, United States of America.
Emory University, Department of Biology, Atlanta, Georgia, United States of America.
ArXiv. 2023 May 12:arXiv:2305.01737v2.
Understanding waning of vaccine-induced protection is important for both immunology and public health. Population heterogeneities in underlying (pre-vaccination) susceptibility and vaccine response can cause measured vaccine effectiveness (mVE) to change over time even in the absence of pathogen evolution and any actual waning of immune responses. We use a multi-scale agent-based models parameterized using epidemiological and immunological data, to investigate the effect of these heterogeneities on mVE as measured by the hazard ratio. Based on our previous work, we consider waning of antibodies according to a power law and link it to protection in two ways: 1) motivated by correlates of risk data and 2) using a within-host model of stochastic viral extinction. The effect of the heterogeneities is given by concise and understandable formulas, one of which is essentially a generalization of Fisher's fundamental theorem of natural selection to include higher derivatives. Heterogeneity in underlying susceptibility accelerates apparent waning, whereas heterogeneity in vaccine response slows down apparent waning. Our models suggest that heterogeneity in underlying susceptibility is likely to dominate. However, heterogeneity in vaccine response offsets <10% to >100% (median of 29%) of this effect in our simulations. Our methodology and results may be helpful in understanding competing heterogeneities and waning of immunity and vaccine-induced protection. Our study suggests heterogeneity is more likely to 'bias' mVE downwards towards faster waning of immunity but a subtle bias in the opposite direction is also plausible.
了解疫苗诱导的保护作用的减弱对于免疫学和公共卫生都很重要。潜在（接种疫苗前）易感性和疫苗反应中的人群异质性可能导致即使在病原体没有进化且免疫反应没有实际减弱的情况下，实测疫苗效力（mVE）也会随时间变化。我们使用基于多尺度主体的模型，通过流行病学和免疫学数据进行参数化，以研究这些异质性对通过风险比衡量的mVE的影响。基于我们之前的工作，我们根据幂律考虑抗体的减弱，并通过两种方式将其与保护作用联系起来：1）受风险数据相关性的推动；2）使用宿主内随机病毒灭绝模型。异质性的影响由简洁易懂的公式给出，其中一个公式本质上是对费希尔自然选择基本定理的推广，以纳入高阶导数。潜在易感性的异质性加速了明显的减弱，而疫苗反应的异质性减缓了明显的减弱。我们的模型表明，潜在易感性的异质性可能占主导。然而，在我们的模拟中，疫苗反应的异质性抵消了这种影响的10%以下至100%以上（中位数为29%）。我们的方法和结果可能有助于理解相互竞争的异质性以及免疫和疫苗诱导保护作用的减弱。我们的研究表明，异质性更有可能使mVE“偏向”免疫力更快减弱的方向，但相反方向的细微偏差也有可能。
