Researchers have been focusing on analyzing the impact of travel restrictions during the COVID-19 pandemic, with internal restrictions being studied more extensively than cross-border travel due to data accessibility challenges. In a significant collaboration involving experts from various fields across Finland, Sweden, Norway, and Denmark, researchers, including mathematicians, physicists, and computer scientists, have conducted a groundbreaking study on the spread of infections across Nordic borders from spring to the end of 2020. The report provides valuable insights into the effectiveness of cross-border travel restrictions, helping us better understand which measures are truly effective.
As the COVID-19 pandemic spread globally in 2020, many countries swiftly closed their borders to prevent the disease from spreading. However, there was limited scientific evidence supporting the effectiveness of such measures.
The researchers developed a sophisticated mathematical model by collecting travel data from the four neighboring countries, focusing on the short-term spread of the disease during a stage of the pandemic when infections had already started to spread within each country.
The study revealed that cross-border closures were only impactful in specific scenarios where there was a significant difference in disease prevalence between countries coupled with high volumes of cross-border traffic. Despite Sweden having looser restrictions leading to higher case numbers than in Finland, the overall effect of cross-border travel on the Finnish disease situation was relatively low.
The research suggests that closing borders may not always be well-justified and should be carefully considered due to its adverse effects. Different pandemic stages may require various approaches, with restrictions on cross-border travelers potentially proving more effective in certain situations.
The study also highlighted differences in the impact of various types of travel, indicating that commuters played a smaller role in spreading infections compared to vacationers spending longer periods in a country.
The researchers emphasized the importance of their predictive model in providing insights for decision-makers during uncertain times like the beginning of the pandemic, offering guidance on appropriate border control interventions.
Although the study focused on the Nordic countries, its findings can be applied to other nations with a focus on obtaining reliable and comparable data for analysis. Data sources such as mobile phone data were utilized to validate findings, emphasizing the need for various datasets and meticulous modeling approaches.
The research is part of the NordicMathCovid project, which involves collaboration among teams from different Nordic countries and has received support from NordForsk. The project aims to provide research on pandemic flows and vaccination strategies from diverse perspectives.
