Surface interactions of aerosols and their impact on infectious disease transmission
Infection transmission has been a major health concern indoors. Exposure analysis and risk analysis are the fundamentals of effectively controlling and managing infection transmission, which requires a clear understanding of transmission mode. A significant fraction of airborne pathogens deposits on...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Theses and Dissertations |
Language: | English |
Published: |
2014
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/61765 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Summary: | Infection transmission has been a major health concern indoors. Exposure analysis and risk analysis are the fundamentals of effectively controlling and managing infection transmission, which requires a clear understanding of transmission mode. A significant fraction of airborne pathogens deposits onto surfaces. Some of these deposited pathogens could be resuspended by airflow or mechanical disturbances and become airborne again, leading to prolonged exposure risk via the airborne mode. Hence, pathogen resuspension can contribute significantly in indoor infection transmission. Understanding the impact of resuspension on infection transmission is crucial for a complete risk assessment scheme. This work intends to improve the current capability of modelling resuspension processes and explore the impact of the resuspension processes on infection transmission by developing a new risk assessment scheme. Two common types of particle resuspension process relevant to indoor environments were studied, i.e., airflow-induced particle resuspension (AIPR) and walking-induced particle resuspension (WIPR). In the case of AIPR, the particle resuspension in the ventilation duct such as that during a bioterrorist attack was considered. A corresponding model of particle concentration dynamics in the ventilation duct was developed based on the existing empirical resuspension models and was validated against the data of wind tunnel experiments. In the case of WIPR, a scaled resuspension chamber with a pair of model feet installed inside was fabricated to investigate the influence of various factors (e.g., flooring material, particle size, walking rate, relative humidity and mechanism) towards WIPR. The resuspension rates for WIPR were calculated based on the mass balance model, and the power law was applied to fit the resuspension rate data. The developed model of particle concentration dynamics in the ventilation duct with AIPR and the power law resuspension rate for WIPR were subsequently substituted into the mass balance models of indoor particle dynamics to develop a set of airborne and surface particle concentration models. Based on the concentration models, a set of inhalational exposure analysis models was developed. Then, a risk assessment scheme was proposed by plugging the exposure analysis into the dose response model. The influence of pathogen resuspension towards infection transmission was examined through two case studies using the developed risk assessment scheme, which generated meaningful insights towards the control and management of infection transmission indoors. Further effort was put to advance the theoretical AIPR model which has the potential to be used in exposure modelling in the future. A set of mean adhesion force (van der Waals force and capillary force) models was firstly developed. Then, an adhesion force distribution model was developed by integrating the RMS roughness distribution into the mean adhesion force models. Finally, a theoretical AIPR model considering the essential characteristics underlying the process (e.g., turbulent burst, adhesion force distribution, depletion of resuspendable particles and relative humidity) was developed based on the proposed adhesion force distribution model. The new theoretical model is able to predict the effect of humidity on AIPR, which greatly enhances the current capability of modelling AIPR. |
---|