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dc.contributor.advisor | Craig, Ian K. | |
dc.contributor.postgraduate | Küsel, Ralf Ronald | |
dc.date.accessioned | 2021-04-22T10:33:13Z | |
dc.date.available | 2021-04-22T10:33:13Z | |
dc.date.created | 2020/04/10 | |
dc.date.issued | 2020 | |
dc.description | Dissertation (MEng)--University of Pretoria, 2020. | |
dc.description.abstract | A detailed mathematical modelling framework for the risk of airborne infectious disease transmission in indoor spaces was developed. This modelling framework enables the mathematical analysis of experiments conducted at the Airborne Infections Research (AIR) facility of eMalahleni, South Africa. A model was built using this framework to explore possible causes of why an experiment at the AIR facility, from 31 August 2015 to 4 December 2015, did not produce expected results. In this experiment the efficacy of upper room germicidal ultraviolet (GUV) irradiation as an environmental control was tested. However, the experiment did not produce the expected outcome of having fewer infections in the test animal room than in the control room. The simulation results indicate that dynamic effects, caused by switching the GUV lights, power outages, or introduction of new patients, did not result in the unexpected outcomes. However, a sensitivity analysis highlights that significant uncertainty exists with risk of transmission predictions based on current measurement practices, due to the reliance on large viable literature ranges for parameters. This work builds on the commonly used Wells-Riley equation for the circumstance of the research facility by including additional mechanisms and dynamics. The model framework is given modularly, to assist in the manipulation of the model for different research questions that are wished to be explored using such a facility. The developed mathematical model is found useful in improving understanding of the risk of infection of airborne infectious diseases in indoor spaces, and in the theoretical exploration of the experiment. Especially the dynamics of the model helped to investigate whether the switching rate of the upper room GUV lights was adequately slow so that one room did indeed get more infectious particles than another. | |
dc.description.availability | Unrestricted | |
dc.description.degree | MEng | |
dc.description.department | Electrical, Electronic and Computer Engineering | |
dc.identifier.citation | Küsel, RR 2020, Modelling of tuberculosis transmission risk for a research Facility in eMalahleni, South Africa, MEng Dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/79595> | |
dc.identifier.other | S2020 | |
dc.identifier.uri | http://hdl.handle.net/2263/79595 | |
dc.language.iso | en | |
dc.publisher | University of Pretoria | |
dc.rights | © 2020 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. | |
dc.subject | UCTD | |
dc.title | Modelling of tuberculosis transmission risk for a research Facility in eMalahleni, South Africa | |
dc.type | Dissertation |