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A data-driven assessment of early travel restrictions related to the spreading of the novel COVID-19 within mainland China.
Aleta, Alberto; Hu, Qitong; Ye, Jiachen; Ji, Peng; Moreno, Yamir.
  • Aleta A; ISI Foundation, Via Chisola 5, 10126 Torino, Italy.
  • Hu Q; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
  • Ye J; Research Institute of Intelligent and Complex Systems, Fudan University, Shanghai 200433, China.
  • Ji P; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
  • Moreno Y; Research Institute of Intelligent and Complex Systems, Fudan University, Shanghai 200433, China.
Chaos Solitons Fractals ; 139: 110068, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-623809
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ABSTRACT
Two months after it was firstly reported, the novel coronavirus disease COVID-19 spread worldwide. However, the vast majority of reported infections until February occurred in China. To assess the effect of early travel restrictions adopted by the health authorities in China, we have implemented an epidemic metapopulation model that is fed with mobility data corresponding to 2019 and 2020. This allows to compare two radically different scenarios, one with no travel restrictions and another in which mobility is reduced by a travel ban. Our findings indicate that i) travel restrictions might be an effective measure in the short term, however, ii) they are ineffective when it comes to completely eliminate the disease. The latter is due to the impossibility of removing the risk of seeding the disease to other regions. Furthermore, our study highlights the importance of developing more realistic models of behavioral changes when a disease outbreak is unfolding.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Chaos Solitons Fractals Year: 2020 Document Type: Article Affiliation country: J.chaos.2020.110068

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Chaos Solitons Fractals Year: 2020 Document Type: Article Affiliation country: J.chaos.2020.110068