Mathematics Institute, University of Warwick, Coventry, United Kingdom.
Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom.
Front Immunol. 2023 Jan 11;13:1049458. doi: 10.3389/fimmu.2022.1049458. eCollection 2022.
A key feature of the COVID-19 pandemic has been the emergence of SARS-CoV-2 variants with different transmission characteristics. However, when a novel variant arrives in a host population, it will not necessarily lead to many cases. Instead, it may fade out, due to stochastic effects and the level of immunity in the population. Immunity against novel SARS-CoV-2 variants may be influenced by prior exposures to related viruses, such as other SARS-CoV-2 variants and seasonal coronaviruses, and the level of cross-reactive immunity conferred by those exposures.
Here, we investigate the impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants in a simplified scenario in which a novel SARS-CoV-2 variant is introduced after an antigenically related virus has spread in the population. We use mathematical modelling to explore the risk that the novel variant invades the population and causes a large number of cases, as opposed to fading out with few cases.
We find that, if cross-reactive immunity is complete (i.e. someone infected by the previously circulating virus is not susceptible to the novel variant), the novel variant must be more transmissible than the previous virus to invade the population. However, in a more realistic scenario in which cross-reactive immunity is partial, we show that it is possible for novel variants to invade, even if they are less transmissible than previously circulating viruses. This is because partial cross-reactive immunity effectively increases the pool of susceptible hosts that are available to the novel variant compared to complete cross-reactive immunity. Furthermore, if previous infection with the antigenically related virus assists the establishment of infection with the novel variant, as has been proposed following some experimental studies, then even variants with very limited transmissibility are able to invade the host population.
Our results highlight that fast assessment of the level of cross-reactive immunity conferred by related viruses against novel SARS-CoV-2 variants is an essential component of novel variant risk assessments.
COVID-19 大流行的一个重要特征是出现了具有不同传播特征的 SARS-CoV-2 变体。然而，当一种新型变体进入宿主人群时，它不一定会导致很多病例。相反，由于随机效应和人群中的免疫水平，它可能会逐渐消失。对新型 SARS-CoV-2 变体的免疫力可能会受到先前接触相关病毒的影响，例如其他 SARS-CoV-2 变体和季节性冠状病毒，以及这些接触所带来的交叉反应性免疫水平的影响。
在这里，我们在一个简化的情景中研究了交叉反应性免疫对 SARS-CoV-2 变体出现的影响，在这种情景中，一种新型 SARS-CoV-2 变体在人群中传播相关病毒后被引入。我们使用数学模型来探索新型变体入侵人群并导致大量病例的风险，而不是出现少量病例而逐渐消失的风险。
我们发现，如果交叉反应性免疫是完全的（即感染先前流行病毒的人对新型变体没有易感性），那么新型变体必须比先前流行的病毒更具传染性才能入侵人群。然而，在一个更现实的情况下，即交叉反应性免疫是部分的，我们表明即使新型变体的传染性比以前流行的病毒低，也有可能入侵。这是因为部分交叉反应性免疫实际上增加了可被新型变体利用的易感宿主的数量，而不是完全的交叉反应性免疫。此外，如果先前感染相关病毒有助于新型变体的建立感染，就像一些实验研究提出的那样，那么即使是具有非常有限传染性的变体也能够入侵宿主人群。
我们的研究结果强调，快速评估相关病毒对新型 SARS-CoV-2 变体产生的交叉反应性免疫水平是新型变体风险评估的一个重要组成部分。
