Risk assessment of COVID-19 infection for subway commuters integrating dynamic changes in passenger numbers.

Li, Peikun; Chen, Xumei; Ma, Chaoqun; Zhu, Caihua; Lu, Wenbo

Li, Peikun; Chen, Xumei; Ma, Chaoqun; Zhu, Caihua; Lu, Wenbo.

Afiliação

Li P; Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, 100044, China.
Chen X; Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Ministry of Transport, Beijing Jiaotong University, Beijing, 100044, China. xmchen@bjtu.edu.cn.
Ma C; College of Transportation Engineering, Chang'an University, Xi'an, 710064, Shaanxi, China.
Zhu C; College of Transportation Engineering, Chang'an University, Xi'an, 710064, Shaanxi, China.
Lu W; School of Transportation, Southeast University, Nanjing, 214135, Jiangsu, China.

Environ Sci Pollut Res Int ; 29(49): 74715-74724, 2022 Oct.

Article em En | MEDLINE | ID: mdl-35639325

Assuntos

Poluentes Atmosféricos; COVID-19; Ferrovias; Poluentes Atmosféricos/análise; Monitoramento Ambiental/métodos; Humanos; Medição de Risco

Palavras-chave

COVID-19; Infection risk; Journey time; SEIR model; Subway carriage; Ventilation

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ferrovias / Poluentes Atmosféricos / COVID-19 Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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