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Author:

Zhang, H. (Zhang, H..) | Zhao, P. (Zhao, P..) | Dou, Z. (Dou, Z..) | Su, B. (Su, B..) | Li, Y. (Li, Y..) | Zhang, N. (Zhang, N..)

Indexed by:

EI Scopus SCIE

Abstract:

Outbreaks of respiratory infectious diseases have often been reported in fitness centers, likely attributed to high population density, extensive shared surfaces, and elevated metabolic equivalent (MET) levels. This study analyzed the behaviors of 30 gym attendees to establish a connection between exercise intensity and virus exposure. Close interactions among participants were tracked using self-developed wearable devices that utilized computer vision technologies, while surface-contact behaviors were recorded using video cameras. A multi-route transmission model for respiratory infectious diseases was subsequently created, integrating the observed behaviors. The Omicron variant of COVID-19 served as a case study to evaluate infection risk via various transmission routes and to assess the efficacy of interventions. The METs during physical activity were about 3.5 times higher than those recorded at rest. The average interpersonal distance during close interactions in the gym was measured at 0.82 m, with 36.7 % of interactions occurring face-to-face. On average, the participants made contact with surfaces 770.3 times per hour, with 517.5 of these contacts involving public surfaces. The hourly infection rate was calculated at 18.5 %, with long-range airborne transmission and close contact accounting for 70.1 % and 28.5 % of the cases, respectively. To mitigate transmission risk, several intervention scenarios were modeled. These included (1) 100 % mask-wearing with N95 masks and occupancy reduced to 62 % (25 m2/person); (2) 100 % mask-wearing with surgical masks and occupancy reduced to 26 % (59.6 m2/person); (3) no mask-wearing, with occupancy reduced to 18 % (86.1 m2/person). All scenarios fulfilled the criteria for achieving an Rt below 1, indicating that under these conditions, gyms could be reopened safely. © 2024 Elsevier Ltd

Keyword:

Human behavior Metabolic equivalent (MET) COVID-19 Gym Epidemic prevention and control

Author Community:

  • [ 1 ] [Zhang H.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Zhao P.]School of Energy and Environment, Southeast University, Jiangsu, Nanjing, 210096, China
  • [ 3 ] [Dou Z.]Department of Computer Science, The University of Hong Kong, Hong Kong
  • [ 4 ] [Su B.]China Electric Power Planning & Engineering Institute, Beijing, China
  • [ 5 ] [Li Y.]Department of Mechanical Engineering, The University of Hong Kong, Pokfulam, Hong Kong
  • [ 6 ] [Zhang N.]Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, Beijing University of Technology, Beijing, 100124, China

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Source :

Building and Environment

ISSN: 0360-1323

Year: 2025

Volume: 267

7 . 4 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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