Tan Suoyi, Lai Shengjie, Fang Fan, Cao Ziqiang, Sai Bin, Song Bing, Dai Bitao, Guo Shuhui, Liu Chuchu, Cai Mengsi, Wang Tong, Wang Mengning, Li Jiaxu, Chen Saran, Qin Shuo, Floyd Jessica R, Cao Zhidong, Tan Jing, Sun Xin, Zhou Tao, Zhang Wei, Tatem Andrew J, Holme Petter, Chen Xiaohong, Lu Xin
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China.
WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK.
Natl Sci Rev. 2021 Aug 16;8(11):nwab148. doi: 10.1093/nsr/nwab148. eCollection 2021 Nov.
2020 was an unprecedented year, with rapid and drastic changes in human mobility due to the COVID-19 pandemic. To understand the variation in commuting patterns among the Chinese population across stable and unstable periods, we used nationwide mobility data from 318 million mobile phone users in China to examine the extreme fluctuations of population movements in 2020, ranging from the Lunar New Year travel season (), to the exceptional calm of COVID-19 lockdown, and then to the recovery period. We observed that cross-city movements, which increased substantially in and then dropped sharply during the lockdown, are primarily dependent on travel distance and the socio-economic development of cities. Following the Lunar New Year holiday, national mobility remained low until mid-February, and COVID-19 interventions delayed more than 72.89 million people returning to large cities. Mobility network analysis revealed clusters of highly connected cities, conforming to the social-economic division of urban agglomerations in China. While the mass migration back to large cities was delayed, smaller cities connected more densely to form new clusters. During the recovery period after travel restrictions were lifted, the netflows of over 55% city pairs reversed in direction compared to before the lockdown. These findings offer the most comprehensive picture of Chinese mobility at fine resolution across various scenarios in China and are of critical importance for decision making regarding future public-health-emergency response, transportation planning and regional economic development, among others.
2020年是史无前例的一年，由于新冠疫情，人类流动性发生了迅速而剧烈的变化。为了解中国人口在稳定期和不稳定期通勤模式的差异，我们使用了来自中国3.18亿手机用户的全国性移动数据，来研究2020年人口流动的极端波动情况，范围从春运期间，到新冠疫情封锁期间的异常平静，再到恢复期。我们观察到，跨城流动在春运期间大幅增加，在封锁期间急剧下降，主要取决于出行距离和城市的社会经济发展。春节假期过后，全国流动性一直较低，直到2月中旬，新冠疫情防控措施使超过7289万人推迟返回大城市。流动网络分析揭示了高度连通城市的集群，符合中国城市群的社会经济划分。虽然大规模返城被推迟，但小城市之间的联系更加密集，形成了新的集群。在解除出行限制后的恢复期，超过55%的城市对的净流动方向与封锁前相比发生了逆转。这些发现提供了中国在各种情景下精细分辨率的最全面的人口流动图景，对于未来公共卫生应急响应、交通规划和区域经济发展等决策至关重要。
