Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA.
Lancet Microbe. 2021 Dec;2(12):e666-e675. doi: 10.1016/S2666-5247(21)00219-6. Epub 2021 Oct 1.
Among the most consequential unknowns of the devastating COVID-19 pandemic are the durability of immunity and time to likely reinfection. There are limited direct data on SARS-CoV-2 long-term immune responses and reinfection. The aim of this study is to use data on the durability of immunity among evolutionarily close coronavirus relatives of SARS-CoV-2 to estimate times to reinfection by a comparative evolutionary analysis of related viruses SARS-CoV, MERS-CoV, human coronavirus (HCoV)-229E, HCoV-OC43, and HCoV-NL63.
We conducted phylogenetic analyses of the , M, and genes to reconstruct a maximum-likelihood molecular phylogeny of human-infecting coronaviruses. This phylogeny enabled comparative analyses of peak-normalised nucleocapsid protein, spike protein, and whole-virus lysate IgG antibody optical density levels, in conjunction with reinfection data on endemic human-infecting coronaviruses. We performed ancestral and descendent states analyses to estimate the expected declines in antibody levels over time, the probabilities of reinfection based on antibody level, and the anticipated times to reinfection after recovery under conditions of endemic transmission for SARS-CoV-2, as well as the other human-infecting coronaviruses.
We obtained antibody optical density data for six human-infecting coronaviruses, extending from 128 days to 28 years after infection between 1984 and 2020. These data provided a means to estimate profiles of the typical antibody decline and probabilities of reinfection over time under endemic conditions. Reinfection by SARS-CoV-2 under endemic conditions would likely occur between 3 months and 5·1 years after peak antibody response, with a median of 16 months. This protection is less than half the duration revealed for the endemic coronaviruses circulating among humans (5-95% quantiles 15 months to 10 years for HCoV-OC43, 31 months to 12 years for HCoV-NL63, and 16 months to 12 years for HCoV-229E). For SARS-CoV, the 5-95% quantiles were 4 months to 6 years, whereas the 95% quantiles for MERS-CoV were inconsistent by dataset.
The timeframe for reinfection is fundamental to numerous aspects of public health decision making. As the COVID-19 pandemic continues, reinfection is likely to become increasingly common. Maintaining public health measures that curb transmission-including among individuals who were previously infected with SARS-CoV-2-coupled with persistent efforts to accelerate vaccination worldwide is critical to the prevention of COVID-19 morbidity and mortality.
US National Science Foundation.
在毁灭性的 COVID-19 大流行中，最具深远影响的未知因素之一是免疫的持久性和可能再次感染的时间。目前关于 SARS-CoV-2 的长期免疫反应和再感染的直接数据有限。本研究旨在通过对 SARS-CoV、MERS-CoV、人类冠状病毒（HCoV）-229E、HCoV-OC43 和 HCoV-NL63 等 SARS-CoV-2 亲缘冠状病毒的免疫持久性进行比较进化分析，利用相关病毒的直接数据来估计再感染时间。
我们对 、M 和 基因进行了系统发育分析，构建了人类感染冠状病毒的最大似然分子系统发育树。该系统发育树使我们能够结合对地方性人类感染冠状病毒的再感染数据，对峰值归一化核衣壳蛋白、刺突蛋白和全病毒裂解 IgG 抗体光密度水平进行比较分析。我们进行了祖先和后代状态分析，以估计抗体水平随时间的预期下降、基于抗体水平的再感染概率以及在地方性传播条件下 SARS-CoV-2 以及其他人类感染冠状病毒康复后的再感染预期时间。
我们获得了 1984 年至 2020 年期间 6 种人类感染冠状病毒的抗体光密度数据，感染后时间从 128 天延长至 28 年。这些数据提供了一种手段，可以估计在地方性条件下典型的抗体下降和再感染随时间变化的情况。在地方性条件下，SARS-CoV-2 的再感染可能发生在峰值抗体反应后 3 个月至 5.1 年之间，中位数为 16 个月。与人类中循环的地方性冠状病毒（HCoV-OC43 的 5-95%分位数为 15 个月至 10 年，HCoV-NL63 为 31 个月至 12 年，HCoV-229E 为 16 个月至 12 年）相比，这种保护作用不到一半。对于 SARS-CoV，5-95%分位数为 4 个月至 6 年，而 MERS-CoV 的 95%分位数因数据集而异。
再感染时间框架是公共卫生决策的众多方面的基础。随着 COVID-19 大流行的继续，再感染可能会越来越普遍。遏制传播的公共卫生措施（包括先前感染 SARS-CoV-2 的个体）与全球加速疫苗接种的持续努力对于预防 COVID-19 的发病率和死亡率至关重要。
美国国家科学基金会。
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