Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China.
Guangzhou Liwan District Center for Disease Prevention and Control, Guangzhou, China.
Front Public Health. 2024 Feb 21;12:1343950. doi: 10.3389/fpubh.2024.1343950. eCollection 2024.
Although the global COVID-19 emergency ended, the real-world effects of multiple non-pharmaceutical interventions (NPIs) and the relative contribution of individual NPIs over time were poorly understood, limiting the mitigation of future potential epidemics.
Based on four large-scale datasets including epidemic parameters, virus variants, vaccines, and meteorological factors across 51 states in the United States from August 2020 to July 2022, we established a Bayesian hierarchical model with a spike-and-slab prior to assessing the time-varying effect of NPIs and vaccination on mitigating COVID-19 transmission and identifying important NPIs in the context of different variants pandemic.
We found that (i) the empirical reduction in reproduction number attributable to integrated NPIs was 52.0% (95%CI: 44.4, 58.5%) by August and September 2020, whereas the reduction continuously decreased due to the relaxation of NPIs in following months; (ii) international travel restrictions, stay-at-home requirements, and restrictions on gathering size were important NPIs with the relative contribution higher than 12.5%; (iii) vaccination alone could not mitigate transmission when the fully vaccination coverage was less than 60%, but it could effectively synergize with NPIs; (iv) even with fully vaccination coverage >60%, combined use of NPIs and vaccination failed to reduce the reproduction number below 1 in many states by February 2022 because of elimination of above NPIs, following with a resurgence of COVID-19 after March 2022.
Our results suggest that NPIs and vaccination had a high synergy effect and eliminating NPIs should consider their relative effectiveness, vaccination coverage, and emerging variants.
尽管全球 COVID-19 紧急情况已经结束，但多种非药物干预措施（NPIs）的实际效果以及随着时间的推移，每种干预措施的相对贡献程度了解甚少，这限制了未来潜在疫情的缓解。
我们基于包括 2020 年 8 月至 2022 年 7 月美国 51 个州的传染病参数、病毒变体、疫苗和气象因素在内的四个大型数据集，建立了一个具有尖峰-哑板先验的贝叶斯分层模型，以评估 NPIs 和疫苗接种随时间变化对减轻 COVID-19 传播的影响，并在不同变体大流行的背景下确定重要的 NPIs。
我们发现：（i）到 2020 年 8 月和 9 月，综合 NPI 归因于减少的繁殖数为 52.0%（95%CI：44.4，58.5%），而随着后续月份 NPIs 的放宽，这种减少持续下降；（ii）国际旅行限制、居家要求和集会规模限制是重要的 NPIs，其相对贡献高于 12.5%；（iii）在完全疫苗接种覆盖率低于 60%时，单独接种疫苗无法减轻传播，但它可以与 NPIs 有效协同；（iv）即使完全疫苗接种覆盖率>60%，由于消除了上述 NPIs，2022 年 2 月许多州的 NPIs 和疫苗联合使用仍未能将繁殖数降低到 1 以下，随后 COVID-19 在 2022 年 3 月后再次爆发。
我们的研究结果表明，NPIs 和疫苗接种具有很高的协同效应，消除 NPIs 时应考虑其相对有效性、疫苗接种覆盖率和新兴变体。
