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Risk assessment of infectious respiratory disease transmission in indoor environments

Authors Sze To, Gin Nam
Issue Date 2010
Summary Pathogens of infectious respiratory diseases can be transmitted via aerosols. These pathogen-laden aerosols are responsible for several modes of transmission of infectious diseases. Multidisciplinary knowledge is required to understand the mechanics and mechanism of transmission of infectious disease via aerosols. Step-by-step procedures are necessary to realistically assess the infection risk associated with these infectious particles. This research integrates knowledge and techniques of mechanical engineering and health sciences to further study the transmission of infectious respiratory diseases in a multidisciplinary perspective and to assess their risk in realistic indoor environments. Multiphase fluid dynamics modeling was employed to estimate the transport of the infectious particles in air and their deposition onto indoor environmental surfaces. Knowing the distribution and the fate of these aerosols, together with respiratory physiological and microbiological data, exposure level and intake dose of the pathogens were estimated. Epidemiological and/or experimental biological models were then used to correlate the intake dose of pathogen to the infection risk of the receptor. Ensemble averaging and Poisson probability were used to express the uncertainties in the infection risk assessment process. Exposure and risk assessment models for different exposure pathways and a retrospective model used to analyze past outbreak cases were developed in this research. Using these models, infection risk assessments were performed in a number of indoor environments, including a general hospital ward, an isolation ward and an aircraft cabin. A Varicella outbreak was analyzed using the retrospective model. The infectious source strength of the index case was predicted by the model. It is found that the infection risks were highly related to the aerosol and airflow dynamics in all these cases. The models developed in this research can be used to predict the spread of infectious respiratory diseases and to evaluate the effectiveness of infection control strategy.
Note Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2010
Language English
Format Thesis
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