Resource constraints in an epidemic: a goal programming and mathematical modelling framework for optimal resource shifting in South Africa
| dc.contributor.advisor | Silal, Sheetal | |
| dc.contributor.advisor | Durbach, Ian | |
| dc.contributor.author | Mayet, Saadiyah | |
| dc.date.accessioned | 2022-03-01T16:11:18Z | |
| dc.date.available | 2022-03-01T16:11:18Z | |
| dc.date.issued | 2021 | |
| dc.date.updated | 2022-03-01T16:09:04Z | |
| dc.description.abstract | The COVID-19 pandemic has had devastating consequences across the globe, and has led many governments into completely new decision making territory. Developing models which are capable of producing realistic projections of disease spread under extreme uncertainty has been paramount for supporting decision making by many levels of government. In South Africa, this role has been fulfilled by the South African COVID-19 Modelling Consortium's generalised Susceptible-ExposedInfectious-Removed compartmental model, known as the National COVID-19 Epi Model. This thesis adapted and contributed to the Model; its primary contribution has been to incorporate the feature that resources available to the health system are limited. Building capacity constraints into the Model allowed it to be used in the resource-scarce context of a pandemic. This thesis further designed and implemented a goal programming framework to shift ICU beds between districts intra-provincially in a way that aimed to minimise deaths caused by the non-availability of ICU beds. The results showed a 15% to 99% decrease in lives lost when ICU beds were shifted, depending on the scenario considered. Although there are limitations to the scope and assumptions of this thesis, it demonstrates that it is possible to combine mathematical modelling with optimisation in a way that may save lives through optimal resource allocation. | |
| dc.identifier.apacitation | Mayet, S. (2021). <i>Resource constraints in an epidemic: a goal programming and mathematical modelling framework for optimal resource shifting in South Africa</i>. (). ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/35867 | en_ZA |
| dc.identifier.chicagocitation | Mayet, Saadiyah. <i>"Resource constraints in an epidemic: a goal programming and mathematical modelling framework for optimal resource shifting in South Africa."</i> ., ,Faculty of Science ,Department of Statistical Sciences, 2021. http://hdl.handle.net/11427/35867 | en_ZA |
| dc.identifier.citation | Mayet, S. 2021. Resource constraints in an epidemic: a goal programming and mathematical modelling framework for optimal resource shifting in South Africa. . ,Faculty of Science ,Department of Statistical Sciences. http://hdl.handle.net/11427/35867 | en_ZA |
| dc.identifier.ris | TY - Master Thesis AU - Mayet, Saadiyah AB - The COVID-19 pandemic has had devastating consequences across the globe, and has led many governments into completely new decision making territory. Developing models which are capable of producing realistic projections of disease spread under extreme uncertainty has been paramount for supporting decision making by many levels of government. In South Africa, this role has been fulfilled by the South African COVID-19 Modelling Consortium's generalised Susceptible-ExposedInfectious-Removed compartmental model, known as the National COVID-19 Epi Model. This thesis adapted and contributed to the Model; its primary contribution has been to incorporate the feature that resources available to the health system are limited. Building capacity constraints into the Model allowed it to be used in the resource-scarce context of a pandemic. This thesis further designed and implemented a goal programming framework to shift ICU beds between districts intra-provincially in a way that aimed to minimise deaths caused by the non-availability of ICU beds. The results showed a 15% to 99% decrease in lives lost when ICU beds were shifted, depending on the scenario considered. Although there are limitations to the scope and assumptions of this thesis, it demonstrates that it is possible to combine mathematical modelling with optimisation in a way that may save lives through optimal resource allocation. DA - 2021 DB - OpenUCT DP - University of Cape Town KW - statistical science LK - https://open.uct.ac.za PY - 2021 T1 - Resource constraints in an epidemic: a goal programming and mathematical modelling framework for optimal resource shifting in South Africa TI - Resource constraints in an epidemic: a goal programming and mathematical modelling framework for optimal resource shifting in South Africa UR - http://hdl.handle.net/11427/35867 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/35867 | |
| dc.identifier.vancouvercitation | Mayet S. Resource constraints in an epidemic: a goal programming and mathematical modelling framework for optimal resource shifting in South Africa. []. ,Faculty of Science ,Department of Statistical Sciences, 2021 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/35867 | en_ZA |
| dc.language.rfc3066 | eng | |
| dc.publisher.department | Department of Statistical Sciences | |
| dc.publisher.faculty | Faculty of Science | |
| dc.subject | statistical science | |
| dc.title | Resource constraints in an epidemic: a goal programming and mathematical modelling framework for optimal resource shifting in South Africa | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationlevel | MSc |