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Author:

Liu, X. (Liu, X..) | Dou, Z. (Dou, Z..) | Wang, L. (Wang, L..) | Su, B. (Su, B..) | Jin, T. (Jin, T..) | Guo, Y. (Guo, Y..) | Wei, J. (Wei, J..) | Zhang, N. (Zhang, N..) (Scholars:张楠)

Indexed by:

EI Scopus SCIE

Abstract:

During COVID-19 pandemic, analysis on virus exposure and intervention efficiency in public transports based on real passenger's close contact behaviors is critical to curb infectious disease transmission. A monitoring device was developed to gather a total of 145,821 close contact data in subways based on semi-supervision learning. A virus transmission model considering both short- and long-range inhalation and deposition was established to calculate the virus exposure. During rush-hour, short-range inhalation exposure is 3.2 times higher than deposition exposure and 7.5 times higher than long-range inhalation exposure of all passengers in the subway. The close contact rate was 56.1 % and the average interpersonal distance was 0.8 m. Face-to-back was the main pattern during close contact. Comparing with random distribution, if all passengers stand facing in the same direction, personal virus exposure through inhalation (deposition) can be reduced by 74.1 % (98.5 %). If the talk rate was decreased from 20 % to 5 %, the inhalation (deposition) exposure can be reduced by 69.3 % (73.8 %). In addition, we found that virus exposure could be reduced by 82.0 % if all passengers wear surgical masks. This study provides scientific support for COVID-19 prevention and control in subways based on real human close contact behaviors. © 2022 Elsevier B.V.

Keyword:

Close contact behavior; COVID-19; Deposition; Depth sensor; Inhalation; Subway; Virus exposure

Author Community:

  • [ 1 ] [Liu, X.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Dou, Z.]Department of Computer Science, The University of Hong Kong, Hong Kong, Hong Kong
  • [ 3 ] [Wang, L.]Institute of Refrigeration and Cryogenics/Key Laboratory of Refrigeration and Cryogenic Technology of Zhejiang Province, Zhejiang University, Hangzhou, China
  • [ 4 ] [Su, B.]China Electric Power Planning & Engineering Institute, Beijing, China
  • [ 5 ] [Jin, T.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, China
  • [ 6 ] [Guo, Y.]Department of Building Science, Tsinghua University, Beijing, China
  • [ 7 ] [Wei, J.]Institute of Refrigeration and Cryogenics/Key Laboratory of Refrigeration and Cryogenic Technology of Zhejiang Province, Zhejiang University, Hangzhou, China
  • [ 8 ] [Zhang, N.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, China

Reprint Author's Address:

  • 张楠

    [Zhang, N.]Key Laboratory of Green Built Environment and Energy Efficient Technology, Room 204, Pingleyuan 100, Chaoyang District, China

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Source :

Journal of Hazardous Materials

ISSN: 0304-3894

Year: 2022

Volume: 436

1 3 . 6

JCR@2022

1 3 . 6 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:49

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 33

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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