Laboratory of Multiscale Studies in Building Physics, Empa, Dübendorf, Switzerland.
Laboratory of Multiscale Studies in Building Physics, Empa, Dübendorf, Switzerland.
Epidemics. 2023 Jun;43:100680. doi: 10.1016/j.epidem.2023.100680. Epub 2023 Mar 14.
In January 2022, after the implementation of broad vaccination programs, the Omicron wave was propagating across Europe. There was an urgent need to understand how population immunity affects the dynamics of the COVID-19 pandemic when the loss of vaccine protection was concurrent with the emergence of a new variant of concern. In particular, assessing the risk of saturation of the healthcare systems was crucial to manage the pandemic and allow a transition towards the endemic course of SARS-CoV-2 by implementing more refined mitigation strategies that shield the most vulnerable groups and protect the healthcare systems. We investigated the epidemic dynamics by means of compartmental models that describe the age-stratified social-mixing and consider vaccination status, type, and waning of the efficacy. In response to the acute situation, our model aimed at (i) providing insight into the plausible scenarios that were likely to occur in Switzerland and Germany in the midst of the Omicron wave, (ii) informing public health authorities, and (iii) helping take informed decisions to minimize negative consequences of the pandemic. Despite the unprecedented numbers of new positive cases, our results suggested that, in all plausible scenarios, the wave was unlikely to create an overwhelming healthcare demand; due to the lower hospitalization rate and the effectiveness of the vaccines in preventing a severe course of the disease. This prediction came true and the healthcare systems in Switzerland and Germany were not pushed to the limit, despite the unprecedentedly large number of infections. By retrospective comparison of the model predictions with the official reported data of the epidemic dynamic, we demonstrate the ability of the model to capture the main features of the epidemic dynamic and the corresponding healthcare demand. In a broader context, our framework can be applied also to endemic scenarios, offering quantitative support for refined public health interventions in response to recurring waves of COVID-19 or other infectious diseases.
2022 年 1 月，在广泛疫苗接种计划实施后，Omicron 浪潮在欧洲蔓延。当疫苗保护作用减弱的同时出现了一种新的令人关注的变异株，迫切需要了解人群免疫力如何影响 COVID-19 大流行的动态。特别是，评估医疗保健系统饱和的风险对于管理大流行并通过实施更精细的缓解策略来过渡到 SARS-CoV-2 的地方病过程至关重要，这些策略可以保护最脆弱的群体并保护医疗保健系统。我们通过描述按年龄分层的社交混合并考虑疫苗接种状况、类型和效力衰减的房室模型来研究疫情动态。为了应对紧急情况，我们的模型旨在：(i) 深入了解在 Omicron 浪潮中瑞士和德国可能发生的情况；(ii) 为公共卫生当局提供信息；(iii) 帮助做出明智的决策，以尽量减少大流行的负面影响。尽管新阳性病例数量空前，但我们的结果表明，在所有可能的情况下，由于住院率较低和疫苗在预防疾病严重程度方面的有效性，这波浪潮不太可能导致医疗保健需求过大。这一预测成为现实，瑞士和德国的医疗保健系统尽管感染人数空前，但并未达到极限。通过对模型预测与疫情动态官方报告数据的回顾性比较，我们证明了模型能够捕捉疫情动态和相应医疗保健需求的主要特征。从更广泛的角度来看，我们的框架也可以应用于地方病情景，为应对 COVID-19 或其他传染病的反复浪潮提供量化支持，以进行精细的公共卫生干预。
