Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
The Queen's College, and, University of Oxford, Oxford, UK.
Philos Trans A Math Phys Eng Sci. 2022 Oct 3;380(2233):20210304. doi: 10.1098/rsta.2021.0304. Epub 2022 Aug 15.
The SARS-CoV-2 epidemic has been extended by the evolution of more transmissible viral variants. In autumn 2020, the B.1.177 lineage became the dominant variant in England, before being replaced by the B.1.1.7 (Alpha) lineage in late 2020, with the sweep occurring at different times in each region. This period coincided with a large number of non-pharmaceutical interventions (e.g. lockdowns) to control the epidemic, making it difficult to estimate the relative transmissibility of variants. In this paper, we model the spatial spread of these variants in England using a meta-population agent-based model which correctly characterizes the regional variation in cases and distribution of variants. As a test of robustness, we additionally estimated the relative transmissibility of multiple variants using a statistical model based on the renewal equation, which simultaneously estimates the effective reproduction number . Relative to earlier variants, the transmissibility of B.1.177 is estimated to have increased by 1.14 (1.12-1.16) and that of Alpha by 1.71 (1.65-1.77). The vaccination programme starting in December 2020 is also modelled. Counterfactual simulations demonstrate that the vaccination programme was essential for reopening in March 2021, and that if the January lockdown had started one month earlier, up to 30 k (24 k-38 k) deaths could have been prevented. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.
SARS-CoV-2 疫情的传播因更具传染性的病毒变体的进化而延长。2020 年秋季,B.1.177 谱系成为英国的主要变体,随后在 2020 年末被 B.1.1.7(Alpha)谱系取代,每个地区的取代时间不同。这一时期恰逢大量非药物干预(如封锁)来控制疫情,使得评估变体的相对传染性变得困难。在本文中,我们使用基于元种群的代理模型来模拟这些变体在英国的空间传播,该模型正确地描述了病例的区域变化和变体的分布。作为稳健性的检验,我们还使用基于更新方程的统计模型来估计多个变体的相对传染性,该模型同时估计有效繁殖数 。与早期变体相比,B.1.177 的传染性估计增加了 1.14(1.12-1.16),Alpha 的传染性增加了 1.71(1.65-1.77)。该模型还模拟了 2020 年 12 月开始的疫苗接种计划。反事实模拟表明,疫苗接种计划对于 2021 年 3 月的重新开放至关重要,如果 1 月的封锁提前一个月开始,最多可以预防 30 万人(24 万至 38 万)死亡。本文是“建模现实生活中的传染病的技术挑战及克服这些挑战的实例”主题特刊的一部分。