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  3. Bioenvironmental Systems Engineering / 生物環境系統工程學系
  4. Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects
 
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Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects

Journal
Environmental Science and Pollution Research
Journal Volume
30
Journal Issue
13
Pages
36228 - 36243
Date Issued
2023
Author(s)
Yang, Ying Fei
Lin, Yi Jun
You, Shu Han
Lu, Tien Hsuan
Chen, Chi Yun
Wang, Wei Min
CHUNG-MIN LIAO  
DOI
10.1007/s11356-022-24815-7
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/629822
Abstract
The Wells-Riley model invokes human physiological and engineering parameters to successfully treat airborne transmission of infectious diseases. Applications of this model would have high potentiality on evaluating policy actions and interventions intended to improve public safety efforts on preventing the spread of COVID-19 in an enclosed space. Here, we constructed the interaction relationships among basic reproduction number (R0) − exposure time − indoor population number by using the Wells-Riley model to provide a robust means to assist in planning containment efforts. We quantified SARS-CoV-2 changes in a case study of two Wuhan (Fangcang and Renmin) hospitals. We conducted similar approach to develop control measures in various hospital functional units by taking all accountable factors. We showed that inhalation rates of individuals proved crucial for influencing the transmissibility of SARS-CoV-2, followed by air supply rate and exposure time. We suggest a minimum air change per hour (ACH) of 7 h−1 would be at least appropriate with current room volume requirements in healthcare buildings when indoor population number is < 10 and exposure time is < 1 h with one infector and low activity levels being considered. However, higher ACH (> 16 h−1) with optimal arranged-exposure time/people and high-efficiency air filters would be suggested if more infectors or higher activity levels are presented. Our models lay out a practical metric for evaluating the efficacy of control measures on COVID-19 infection in built environments. Our case studies further indicate that the Wells-Riley model provides a predictive and mechanistic basis for empirical COVID-19 impact reduction planning and gives a framework to treat highly transmissible but mechanically heterogeneous airborne SARS-CoV-2.
Subjects
Airborne infection transmission
COVID-19
Healthcare facility
Indoor air quality
SARS-CoV-2
Wells-Riley model
Publisher
SPRINGER HEIDELBERG
Type
journal article

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