Dilution-based evaluation of airborne infection risk - Thorough expansion of Wells-Riley model

• Published in: Building and environment Vol. 194; p. 107674
• Main Authors: Zhang, Sheng, Lin, Zhang
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.05.2021; Elsevier BV
• Subjects: Airborne infection; Airborne infection risk; Built environment; COVID-19; Dilution; Health risks; Infections; Infectious respiratory disease; Respiratory diseases; Risk; Spatial and temporal; Urban environments; Wells; Wells-riley model; Dilution; Spatial and temporal; Wells-riley model; Infectious respiratory disease; Airborne infection risk
• ISSN: 0360-1323; 1873-684X
• DOI: 10.1016/j.buildenv.2021.107674

Evaluation of airborne infection risk with spatial and temporal resolutions is indispensable for the design of proper interventions fighting infectious respiratory diseases (e.g., COVID-19), because the distribution of aerosol contagions is both spatially and temporally non-uniform. However, the well-recognized Wells-Riley model and modified Wells-Riley model (i.e., the rebreathed-fraction model) are limited to the well-mixed condition and unable to evaluate airborne infection risk spatially and temporally, which could result in overestimation or underestimation of airborne infection risk. This study proposes a dilution-based evaluation method for airborne infection risk. The method proposed is benchmarked by the Wells-Riley model and modified Wells-Riley model, which indicates that the method proposed is a thorough expansion of the Wells-Riley model for evaluation of airborne infection risk with both spatial and temporal resolutions. Experiments in a mock hospital ward also demonstrate that the method proposed effectively evaluates the airborne infection risk both spatially and temporally. The proposed method is convenient to implement for the development of healthy built environments. •Dilution-based evaluation of airborne infection risk is proposed.•It is benchmarked with Wells-Riley model for well-mixed and steady condition.•It is benchmarked with rebreathed-fraction model for well-mixed and dynamic condition.•It has spatial and temporal resolutions.•It is a thorough expansion of Wells-Riley model.