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A spatiotemporal assessment of occupants’ infection risks in a multi-occupants space using modified Wells–Riley model
Abstract Escalating demands of assessing airborne disease infection risks had been awakened from ongoing pandemics. An inhalation index linked to biomedical characteristics of pathogens (e.g. for coronavirus delta variant) was proposed to quantify human uptake dose. A modified Wells–Riley risk-assessment framework was then developed with enhanced capability of integrating biological and spatiotemporal features of infectious pathogens into assessment. The instantaneous transport characteristics of pathogens were traced by Eulerian–Lagrangian method. Droplets released via speaking and coughing in a conference room with three ventilation strategies were studied to assess occupants’ infection risks using this framework. Outcomes revealed that speaking droplets could travel with less distance (0.5 m) than coughing droplets (1 m) due to the frequent interaction between speaking flow and thermal plume. Quantified analysis of inhalation index revealed a higher inhalation possibility of droplets with nuclei size smaller than , and this cut-off size was found sensitive to ventilation. With only 60-second exposure, occupants in the near-field of host started to have considerable infection risks (approximately 20%). This risk was found minimising over distance exponentially. This modified framework demonstrated the systematic analysis of airborne transmission, from quantifying particle inhalation possibility, targeting specific disease’s , to ultimate evaluation of infection risks.
Graphical abstract Display Omitted
Highlights An novel inhalation index (ID) was proposed based on droplet inhalability. The biological attributes of airborne pathogen were integrated into modelling. A modified Wells–Riley model integrating ID and Tissue Culture Infectious Dose. Exposure over 60 s within 2 m of host could have considerable infection risk. 5 m is cut-off size of sensitive ID and could increase with enabled ventilation.
A spatiotemporal assessment of occupants’ infection risks in a multi-occupants space using modified Wells–Riley model
Abstract Escalating demands of assessing airborne disease infection risks had been awakened from ongoing pandemics. An inhalation index linked to biomedical characteristics of pathogens (e.g. for coronavirus delta variant) was proposed to quantify human uptake dose. A modified Wells–Riley risk-assessment framework was then developed with enhanced capability of integrating biological and spatiotemporal features of infectious pathogens into assessment. The instantaneous transport characteristics of pathogens were traced by Eulerian–Lagrangian method. Droplets released via speaking and coughing in a conference room with three ventilation strategies were studied to assess occupants’ infection risks using this framework. Outcomes revealed that speaking droplets could travel with less distance (0.5 m) than coughing droplets (1 m) due to the frequent interaction between speaking flow and thermal plume. Quantified analysis of inhalation index revealed a higher inhalation possibility of droplets with nuclei size smaller than , and this cut-off size was found sensitive to ventilation. With only 60-second exposure, occupants in the near-field of host started to have considerable infection risks (approximately 20%). This risk was found minimising over distance exponentially. This modified framework demonstrated the systematic analysis of airborne transmission, from quantifying particle inhalation possibility, targeting specific disease’s , to ultimate evaluation of infection risks.
Graphical abstract Display Omitted
Highlights An novel inhalation index (ID) was proposed based on droplet inhalability. The biological attributes of airborne pathogen were integrated into modelling. A modified Wells–Riley model integrating ID and Tissue Culture Infectious Dose. Exposure over 60 s within 2 m of host could have considerable infection risk. 5 m is cut-off size of sensitive ID and could increase with enabled ventilation.
A spatiotemporal assessment of occupants’ infection risks in a multi-occupants space using modified Wells–Riley model
Yan, Yihuan (author) / Li, Xueren (author) / Fang, Xiang (author) / Tao, Yao (author) / Tu, Jiyuan (author)
Building and Environment ; 230
2023-01-10
Article (Journal)
Electronic Resource
English
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