Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China.
Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, People's Republic of China.
J R Soc Interface. 2022 Feb;19(187):20210662. doi: 10.1098/rsif.2021.0662. Epub 2022 Feb 16.
The ongoing coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc worldwide with millions of lives claimed, human travel restricted and economic development halted. Leveraging city-level mobility and case data, our analysis shows that the spatial dissemination of COVID-19 can be well explained by a local diffusion process in the mobility network rather than a global diffusion process, indicating the effectiveness of the implemented disease prevention and control measures. Based on the constructed case prediction model, it is estimated that there could be distinct social consequences if the COVID-19 outbreak happened in different areas. During the epidemic control period, human mobility experienced substantial reductions and the mobility network underwent remarkable local and global structural changes toward containing the spread of COVID-19. Our work has important implications for the mitigation of disease and the evaluation of the socio-economic consequences of COVID-19 on society.
正在持续的 2019 年冠状病毒病（COVID-19）大流行在全球范围内造成了严重破坏，数百万人因此失去生命，人类旅行受到限制，经济发展停滞不前。利用城市层面的移动性和病例数据，我们的分析表明，COVID-19 的空间传播可以很好地用移动性网络中的局部扩散过程来解释，而不是用全球扩散过程来解释，这表明所实施的疾病预防和控制措施是有效的。基于构建的病例预测模型，如果 COVID-19 在不同地区爆发，可能会产生明显的社会后果。在疫情防控期间，人类流动性大幅减少，移动性网络发生了显著的局部和全球结构变化，以遏制 COVID-19 的传播。我们的工作对于减轻疾病以及评估 COVID-19 对社会的社会经济影响具有重要意义。
