Airborne disease infection risk modeling
A mathematical model which estimates spatial infection risk as a function of pulmonary rate and deposition region has been developed based on the does-response model. It is specifically designed for enclosed space with consideration of pathogen bio-properties, such as viability and infectivity. Firs...
Main Author: | |
---|---|
Language: | English |
Published: |
University of British Columbia
2012
|
Online Access: | http://hdl.handle.net/2429/43206 |
id |
ndltd-UBC-oai-circle.library.ubc.ca-2429-43206 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-UBC-oai-circle.library.ubc.ca-2429-432062018-01-05T17:26:06Z Airborne disease infection risk modeling Lin, Chu A mathematical model which estimates spatial infection risk as a function of pulmonary rate and deposition region has been developed based on the does-response model. It is specifically designed for enclosed space with consideration of pathogen bio-properties, such as viability and infectivity. Firstly, eleven cases of Tuberculosis (TB) outbreaks in aircraft are studied to develop the optimal parameters set. It is then used to perform model validation and investigation of sample inpatient room spatial infection risk. Secondly, infection risk for eleven TB outbreaks are compared with modeling and Wells-Riley estimations. As a result, modeling results are within the calculated range of Wells-Riley prediction. To determine the importance of viability and ventilation rate regarding HVAC system design for health facilities, infection risks are calculated at different viability and ventilation rates. Based on the observation, ventilation rate or particle concentration in the space dominate the infection risk distribution, except when viability decays extreme rapidly. Thirdly, the spatial infection risk is investigated for TB in a typical 60 m³ inpatient room with displacement and well-mixed ventilation systems. Two room settings, a nurse standing close to the patient’s bed versus a visitor standing far away from the bed, and two coughing directions, horizontal versus vertical, are studied. The results show that for coughing horizontally, when the nurse stands beside the patient's bed, his/her breathing zone is the highest risk zone for displacement ventilation. Under displacement ventilation, the infection risk is lower when visitor stands away from the bed compared to stand close to the bed if the visitor is the only person present in the room besides the patient. The infection risk of the breathing zones in the two cases with horizontal coughing are both higher than 25%. However, when a patient coughs vertically, the displacement ventilation significantly reduces the infection risk. With 24 hours exposure, the infection risk for the nurse and the visitor are both less than 5%. Applied Science, Faculty of Mechanical Engineering, Department of Graduate 2012-09-14T17:03:55Z 2012-09-14T17:03:55Z 2012 2012-11 Text Thesis/Dissertation http://hdl.handle.net/2429/43206 eng Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ University of British Columbia |
collection |
NDLTD |
language |
English |
sources |
NDLTD |
description |
A mathematical model which estimates spatial infection risk as a function of pulmonary rate and deposition region has been developed based on the does-response model. It is specifically designed for enclosed space with consideration of pathogen bio-properties, such as viability and infectivity.
Firstly, eleven cases of Tuberculosis (TB) outbreaks in aircraft are studied to develop the optimal parameters set. It is then used to perform model validation and investigation of sample inpatient room spatial infection risk.
Secondly, infection risk for eleven TB outbreaks are compared with modeling and Wells-Riley estimations. As a result, modeling results are within the calculated range of Wells-Riley prediction. To determine the importance of viability and ventilation rate regarding HVAC system design for health facilities, infection risks are calculated at different viability and ventilation rates. Based on the observation, ventilation rate or particle concentration in the space dominate the infection risk distribution, except when viability decays extreme rapidly.
Thirdly, the spatial infection risk is investigated for TB in a typical 60 m³ inpatient room with displacement and well-mixed ventilation systems. Two room settings, a nurse standing close to the patient’s bed versus a visitor standing far away from the bed, and two coughing directions, horizontal versus vertical, are studied. The results show that for coughing horizontally, when the nurse stands beside the patient's bed, his/her breathing zone is the highest risk zone for displacement ventilation. Under displacement ventilation, the infection risk is lower when visitor stands away from the bed compared to stand close to the bed if the visitor is the only person present in the room besides the patient. The infection risk of the breathing zones in the two cases with horizontal coughing are both higher than 25%. However, when a patient coughs vertically, the displacement ventilation significantly reduces the infection risk. With 24 hours exposure, the infection risk for the nurse and the visitor are both less than 5%. === Applied Science, Faculty of === Mechanical Engineering, Department of === Graduate |
author |
Lin, Chu |
spellingShingle |
Lin, Chu Airborne disease infection risk modeling |
author_facet |
Lin, Chu |
author_sort |
Lin, Chu |
title |
Airborne disease infection risk modeling |
title_short |
Airborne disease infection risk modeling |
title_full |
Airborne disease infection risk modeling |
title_fullStr |
Airborne disease infection risk modeling |
title_full_unstemmed |
Airborne disease infection risk modeling |
title_sort |
airborne disease infection risk modeling |
publisher |
University of British Columbia |
publishDate |
2012 |
url |
http://hdl.handle.net/2429/43206 |
work_keys_str_mv |
AT linchu airbornediseaseinfectionriskmodeling |
_version_ |
1718583503397847040 |