Department of Mathematics and Systems Analysis, Aalto University, Espoo, Finland.
Oslo Center for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway.
PLoS Comput Biol. 2024 Jun 12;20(6):e1012182. doi: 10.1371/journal.pcbi.1012182. eCollection 2024 Jun.
Restrictions of cross-border mobility are typically used to prevent an emerging disease from entering a country in order to slow down its spread. However, such interventions can come with a significant societal cost and should thus be based on careful analysis and quantitative understanding on their effects. To this end, we model the influence of cross-border mobility on the spread of COVID-19 during 2020 in the neighbouring Nordic countries of Denmark, Finland, Norway and Sweden. We investigate the immediate impact of cross-border travel on disease spread and employ counterfactual scenarios to explore the cumulative effects of introducing additional infected individuals into a population during the ongoing epidemic. Our results indicate that the effect of inter-country mobility on epidemic growth is non-negligible essentially when there is sizeable mobility from a high prevalence country or countries to a low prevalence one. Our findings underscore the critical importance of accurate data and models on both epidemic progression and travel patterns in informing decisions related to inter-country mobility restrictions.
跨境流动限制通常用于防止新发疾病进入一个国家,以减缓其传播。然而,这种干预措施可能会带来重大的社会成本,因此应该基于对其影响的仔细分析和定量理解。为此,我们对 2020 年期间丹麦、芬兰、挪威和瑞典这四个北欧邻国的 COVID-19 跨境流动传播进行建模。我们研究了跨境旅行对疾病传播的即时影响,并采用反事实情景来探索在疫情持续期间将额外的感染者引入人群中所产生的累积效应。结果表明,当从高流行国家或国家向低流行国家有大量的人口流动时,国家间的移动对疫情的增长有着不可忽视的影响。我们的研究结果强调了准确的数据和模型对于了解与国家间流动限制相关的决策至关重要,这些模型需要同时考虑到疾病的传播进程和旅行模式。