Population-level considerations for the treatment of lethal diseases in resource-limited settings

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dc.contributor.advisorPulliam, Juliet RCen_ZA
dc.contributor.authorSereo, Tumelo Donalden_ZA
dc.contributor.otherStellenbosch University. Faculty of Science. Dept. of Mathematical Sciences.en_ZA
dc.date.accessioned2023-03-06T15:19:13Zen_ZA
dc.date.accessioned2023-05-18T07:11:58Zen_ZA
dc.date.available2023-03-06T15:19:13Zen_ZA
dc.date.available2023-05-18T07:11:58Zen_ZA
dc.date.issued2023-03en_ZA
dc.descriptionThesis (MSc)--Stellenbosch University, 2023.en_ZA
dc.description.abstractENGLISH ABSTRACT: Diseases such as Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Ebola Virus disease (EVD), continue to challenge health systems worldwide. At the onset of outbreaks of unknown pathogens, there is often no cure, treatment or vaccine available to limit their impact. As the outbreak unfolds, randomised controlled trials are conducted, usually in patients with severe disease, to investigate candidate treatments. Often, several treatments end up being effective, raising the question of which one is most optimal to deploy. While clinical trials focus on individual-level outcomes, population-level outcomes are often more important for public health decision-making. This study answers two questions: First, when can a hypothetical treatment that increases hospital stay duration and probability of survival be used to improve the population-level mortality outcomes under constrained hospital capacity? Second, when is it preferable to invest in treatments versus beds, in a limited resource setting? We developed a transmission dynamic model, parameterised separately for SARS-CoV2 and Ebola, to address the questions posed. For the first question, we ran the model for baseline (no treatment) and treatment scenarios defined by the probability of surviving and duration of hospital stay. We used cumulative mortality as the metric to compare the population-level outcomes. The model shows that there is a substantial region of parameter space in which it is beneficial to use hypothetical treatments that increase probability of surviving and hospital stay duration. For the second question, we performed a cost-minimization analysis to examine when it is preferable to invest in treatments versus beds, in a limited resource setting. The model identified the number of additional beds that would be needed to obtain approximately the same outcomes compared to what is expected with existing treatments. We found that is it preferable to invest in additional beds rather than the existing treatments when the cost per course of treatment is greater than a threshold that depends on the drug under consideration. We estimated that this threshold is around R5 000 for existing SARS-CoV-2 drugs but higher for available Ebola therapies.en_ZA
dc.description.abstractAFRIKAANS OPSOMMING: Siektes soos Ernstige Akute Respiratoriese Sindroom Coronavirus (SARS-CoV) en Ebola Virussiekte (EVD), gaan voort om gesondheidstelsels wêreldwyd uit te daag. By die aanvang van uitbrake van onbekende patogene is daar dikwels geen geneesmiddel, behandeling of entstof beskikbaar om die impak daarvan te beperk nie. Soos die uitbraak ontvou, word ewekansige beheerde proewe uitgevoer, gewoonlik by ernstige siek pasiënte, om kandidaat-behandelings te ondersoek. Dikwels is verskeie behandelings uiteindelik effektief, wat die vraag laat ontstaan watter een die beste is om te ontplooi. Terwyl kliniese proewe op individuele-vlak uitkomste fokus, is bevolkingsvlak uitkomste dikwels belangriker vir besluitneming oor openbare gesondheid. Hierdie studie beantwoord twee vrae: Eerstens, wanneer kan ’n hipotetiese behandeling wat die duur van die hospitaalverblyf en die waarskynlikheid van oorlewing verhoog, gebruik word om die sterfte-uitkomste op bevolkingsvlak onder beperkte hospitaalkapasiteit te verbeter? Tweedens, wanneer is dit verkieslik om in behandelings teenoor beddens in ’n beperkte hulpbronomgewing te belê? Ons het ’n transmissie-dinamiese model ontwikkel, afsonderlik geparameteriseer vir SARS-CoV-2 en Ebola, om die twee vrae aan te spreek. Vir die eerste vraag het ons die model vir basislyn (geen behandeling) en behandeling scenario’s uitgevoer. Laasgenoemde word gedefinieer deur die waarskynlikheid van oorlewing en duur van hospitaalverblyf. Ons het kumulatiewe mortaliteit as die maatstaf gebruik om die bevolkingsvlak uitkomste te vergelyk. Die model toon dat daar ’n aansienlike gebied van parameter ruimte is waarin dit voordelig is om hipotetiese behandelings te gebruik wat die waarskynlikheid van oorlewing en die duur van die hospitaalverblyf verhoog. Vir die tweede vraag het ons ’n koste-minimaliseringsanalise uitgevoer om te ondersoek wanneer dit verkieslik is om in behandelings teenoor beddens in ’n beperkte hulpbronomgewing te belê. Die model het die aantal bykomende beddens geïdentifiseer wat nodig sou wees om ongeveer dieselfde uitkomste te verkry in vergelyking met wat verwag word met bestaande behandelings. Ons het gevind dat dit verkieslik is om in bykomende beddens te belê eerder as die bestaande behandelings wanneer die koste per kursus van behandeling groter is as ’n drempel wat afhang van die geneesmiddel wat oorweeg word. Ons het geskat dat hierdie drempel ongeveer R5 000 is vir bestaande SARS-CoV-2-middels, maar hoër vir beskikbare Ebola-terapieë.af_ZA
dc.description.versionMastersen_ZA
dc.format.extentxiii, 47 pages : illustrationsen_ZA
dc.identifier.urihttp://hdl.handle.net/10019.1/127249en_ZA
dc.language.isoen_ZAen_ZA
dc.publisherStellenbosch : Stellenbosch Universityen_ZA
dc.rights.holderStellenbosch Universityen_ZA
dc.subject.lcshCommunicable diseases -- Treatmenten_ZA
dc.subject.lcshSARS (Disease)en_ZA
dc.subject.lcshEbola virus diseaseen_ZA
dc.subject.lcshCOVID-19 (Disease)en_ZA
dc.titlePopulation-level considerations for the treatment of lethal diseases in resource-limited settingsen_ZA
dc.typeThesisen_ZA
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