| 1 | Mobility in China,2020:a tale of four phases显示文摘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(chunyun),to the exceptional calm of COVID-19 lockdown,and then to the recovery period.We observed that cross-city movements;which increased substantially in chunyun 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. | Suoyi Tan Shengjie Lai Fan Fang Ziqiang Cao Bin Sai Bing Song Bitao Dai Shuhui Guo Chuchu Liu Mengsi Cai Tong Wang Mengning Wang Jiaxu Li Saran Chen Shuo Qin Jessica R.Floyd Zhidong Cao Jing Tan Xin Sun Tao Zhou Wei Zhang Andrew J.Tatem Petter Holme Xiaohong Chen Xin Lu | 2021 | National Science Review2021，8，11： | 3 |
| 2 | Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures(Cities)-China,2022显示文摘Introduction:Minimizing the importation and exportation risks of coronavirus disease 2019(COVID-19)is a primary concern for sustaining the“Dynamic COVID-zero”strategy in China.Risk estimation is essential for cities to conduct before relaxing border control measures.Methods:Informed by the daily number of passengers traveling between 367 prefectures(cities)in China,this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks.Results:Under the transmission scenario(R0=5.49),this study estimated the cumulative case incidence of Changchun City,Jilin Province as 3,233(95%confidence interval:1,480,4,986)before a lockdown on March 14,2022,which is close to the 3,168 cases reported in real life by March 16,2022.In a total of 367 prefectures(cities),127(35%)had high exportation risks according to the simulation and could transmit the disease to 50%of all other regions within a period from 17 to 94 days.The average time until a new infection arrives in a location in 1 of the 367 prefectures(cities)ranged from 26 to 101 days.Conclusions:Estimating COVID-19 importation and exportation risks is necessary for preparedness,prevention,and control measures of COVID-19—especially when new variants emerge. | Yuan Bai Mingda Xu Caifen Liu Mingwang Shen Lin Wang Linwei Tian Suoyi Tan Lei Zhang Petter Holme Xin Lu Eric H.Y.Lau Benjamin J.Cowling Zhanwei Du | 2022 | China CDC weekly2022，4，40： | 0 |
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