Græsbøll Kaare, Eriksen Rasmus Skytte, Kirkeby Carsten, Christiansen Lasse Engbo
Department of Epidemiology Research, Statens Serum Institut, Artillerivej 5, Copenhagen S, 2300, Denmark.
Dynamical Systems, Compute, Technical University of Denmark, Anker Engelunds Vej 101, Kongens Lyngby, 2800, Denmark.
Commun Med (Lond). 2024 Oct 4;4(1):192. doi: 10.1038/s43856-024-00621-9.
Following the COVID-19 pandemic, it is important to evaluate different mitigation strategies for future preparedness. Mass testing and local lockdowns were employed during the Alpha wave in Denmark, which led to ten times more tests than the typical European member state and incidence-based restrictions at the parish level. This study aims to quantify the effects of these interventions in terms of hospital admissions and societal freedom.
This study assesses the effectiveness of these strategies via counterfactual scenarios using a detailed, individual-based simulation model that replicates the entire Danish population. The model considers multiple factors, including evolving societal restrictions, vaccination roll-out, seasonal influences, and varying intensities of PCR and antigen testing across different age groups and degree of completed vaccination. It also integrates adaptive human behavior in response to changes in incidences at the municipality and parish levels.
The simulations show, that without mass testing in Denmark, there would have been a 150% increase in hospital admissions, and additional local lockdowns equivalent to 21 days of strict national lockdown. Without the policy of local lockdowns, hospitalizations would have increased by 50%.
In conclusion, the combination of mass testing and local lockdowns likely prevented a large increase in hospitalizations while increasing overall societal freedom during the Alpha wave in Denmark. In future epidemics, mass testing and local lockdowns can likely prevent overwhelming healthcare systems in phases of high transmission and hospitalization risks.
在新冠疫情之后，评估不同的缓解策略以备未来之需十分重要。丹麦在阿尔法波疫情期间采用了大规模检测和局部封锁措施，这使得检测次数比典型的欧洲成员国多了十倍，并在教区层面实施了基于发病率的限制措施。本研究旨在量化这些干预措施在住院人数和社会自由度方面的影响。
本研究通过使用一个详细的、基于个体的模拟模型来评估这些策略的有效性，该模型复制了整个丹麦人口。该模型考虑了多个因素，包括不断变化的社会限制、疫苗接种推广、季节性影响，以及不同年龄组和疫苗接种完成程度下PCR检测和抗原检测的不同强度。它还整合了人类针对市镇和教区层面发病率变化的适应性行为。
模拟结果显示，在丹麦若没有大规模检测，住院人数将增加150%，且会出现相当于全国严格封锁21天的额外局部封锁。若没有局部封锁政策，住院人数将增加50%。
总之，大规模检测和局部封锁相结合可能在丹麦阿尔法波疫情期间防止了住院人数大幅增加，同时提高了总体社会自由度。在未来的疫情中，大规模检测和局部封锁可能在高传播和高住院风险阶段防止医疗系统不堪重负。
