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1000 Titel
  • An analysis of the domestic resumption of social production and life under the COVID-19 epidemic
1000 Autor/in
  1. Xu, Xinliang |
  2. Wang, Shihao |
  3. Dong, Jinhui |
  4. Shen, Zhicheng |
  5. Xu, Shuwan |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-07-22
1000 Erschienen in
1000 Quellenangabe
  • 15(7):e0236387
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1371/journal.pone.0236387 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Population migration and urban traffic are two important aspects of the socioeconomic system. We analyze the trends of social production and resumption of life after the coronavirus disease 2019 (COVID-19)-influenced Spring Festival in 2020 with statistics on reported cases of COVID-19 from China’s National Health Commission and big data from Baidu Migration (a platform collecting population migration data). We find that (1) the distribution of COVID-19 cases throughout mainland China has a specific spatial pattern. Provinces in eastern China have more reported cases than those in western China, and provinces adjacent to Hubei have more confirmed COVID-19 cases than nonadjacent provinces. Densely populated regions with well-developed economies and transportation are more likely to have cluster infection incidents. (2) The COVID-19 epidemic severely impacts the return of the migrant population in the Spring Festival travel rush, as demonstrated by the significant reduction in the return scale, along with the extended timespan and uncertainty regarding the end of the travel rush. Among 33 provinces, special administrative regions, autonomous regions and municipalities, 23 of them (approximately 70%) have a return rate below 60%. Hubei, Hong Kong, Xinjiang, and Inner Mongolia have the lowest return rates (below 5%), whereas the return rates in Hainan and Shandong, 272.72% and 97.35%, respectively, indicate the best trend of resumption. Due to government regulations, the population return in densely populated and well-developed regions shows a positive trend. (3) The resumption of urban traffic is slow and varies greatly in different regions. The urban traffic conditions in 22 provinces and municipalities have a more than 60% level of resumption. Guizhou and Yunnan have the highest level of resumption of urban traffic, whereas Xinjiang, Hubei, and Heilongjiang have the lowest (29.37%, 35.76%, and 37.90%, respectively). However, provinces and municipalities with well-developed intercity traffic have a lower level of resumption, mainly because of regulatory methods such as lockdowns and traffic restrictions. The increased public awareness of epidemic prevention and the decreased frequency of outdoor activities are also two positive factors slowing the spread of the epidemic. (4) Time will be necessary to fully resume social production and life throughout China. Xining and Jinan have the highest levels of resumption, 82.14% and 71.51%, respectively. Urumqi and Wuhan are the cities with the lowest levels of resumption, only 0.11% and 0.61%, respectively. Currently, 12 of 33 provinces and municipalities have levels of resumption of more than 80%; among them, Guizhou, Yunnan, and Gansu have with the highest levels of resumption and have nearly resumed the 2019 levels of work and life, whereas Xinjiang and Hubei have the lowest resumption rates, only 0.09% and 7.57%, respectively. Thus, relevant government departments should focus more on densely populated and well-developed provinces and cities when applying epidemic prevention and work resumption methods. We reveal the general conditions of the epidemic and the population return scale across China, along with urban traffic conditions and the resumption of social production and life under COVID-19, providing a scientific basis for local governments to make further decisions on work resumption.
1000 Sacherschließung
gnd 1206347392 COVID-19
lokal Epidemiological statistics
lokal China
lokal Social epidemiology
lokal Transportation
lokal Socioeconomic aspects of health
lokal Cities
lokal Economic development
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/WHUsIFhpbmxpYW5n|https://orcid.org/0000-0001-8091-4926|https://frl.publisso.de/adhoc/uri/RG9uZywgSmluaHVp|https://frl.publisso.de/adhoc/uri/U2hlbiwgWmhpY2hlbmc=|https://frl.publisso.de/adhoc/uri/WHUsIFNodXdhbg==
1000 Label
1000 Förderer
  1. Chinese Academy of Sciences |
1000 Fördernummer
  1. XDA20010302
1000 Förderprogramm
  1. Strategic Priority Research
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Chinese Academy of Sciences |
    1000 Förderprogramm Strategic Priority Research
    1000 Fördernummer XDA20010302
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6422103.rdf
1000 Erstellt am 2020-07-23T11:41:52.596+0200
1000 Erstellt von 122
1000 beschreibt frl:6422103
1000 Bearbeitet von 122
1000 Zuletzt bearbeitet Thu Jul 23 11:49:53 CEST 2020
1000 Objekt bearb. Thu Jul 23 11:49:32 CEST 2020
1000 Vgl. frl:6422103
1000 Oai Id
  1. oai:frl.publisso.de:frl:6422103 |
1000 Sichtbarkeit Metadaten public
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