Digital twin simulation modelling shows that mass testing and local lockdowns effectively controlled COVID-19 in Denmark

数字孪生仿真模型显示,丹麦通过大规模检测和局部封锁有效控制了新冠疫情。

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Abstract

BACKGROUND: 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. METHODS: 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. RESULTS: 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%. CONCLUSIONS: 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.

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