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Country distancing reveals the effectiveness of travel restrictions during COVID-19
Lu Zhong; Mamadou Diagne; Weiping Wang; Jianxi Gao.
Afiliação
  • Lu Zhong; Rensselaer Polytechnic Institute
  • Mamadou Diagne; Rensselaer Polytechnic Institute
  • Weiping Wang; Beijing Jiaotong University
  • Jianxi Gao; Rensselaer Polytechnic Institute
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20160994
ABSTRACT
Travel restrictions are the current central strategy to globally stop the transmission of the novel coronavirus disease (COVID-19). Despite remarkably successful approaches in predicting the spatiotemporal patterns of the ongoing pandemic, we lack an intrinsic understanding of the travel restrictions effectiveness. We fill this gap by developing a surprisingly simple measure, country distancing, that is analogical to the effective resistance in series and parallel circuits and captures the propagation backbone tree from the outbreak locations globally. This approach enables us to map the effectiveness of travel restrictions to arrival time delay (ATD) or infected case reduction (ICR) systematically. Our method estimates that 50.8% of travel restrictions as of Apr-4 are ineffective, resulting in zero ATD or ICR worldwide. Instead, by imposing Hubeis lockdown on Jan-23 and national lockdown on Feb-8, mainland China alone leads to 11.66 [95% credible interval (CI), 9.71 to 13.92] days of ATD per geographic area and 1,012,233 (95% CI, 208,210 -4,959,094) ICR in total as of Apr-4. Our result unveils the trade-off between the country distancing increase and economic loss, offering practical guidance for strategic actsion about when and where to implement travel restrictions, tailed to the real-time national context.
Licença
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Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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