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Modeling the effectiveness of control measures from the within-host dynamics to the population dynamics of sleeping sickness.

dc.contributor.advisorMambili-Mamboundou, Hermane.
dc.contributor.authorMulalo, Makhuvha.
dc.date.accessioned2025-01-08T19:33:10Z
dc.date.available2025-01-08T19:33:10Z
dc.date.created2024
dc.date.issued2024
dc.descriptionDoctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.
dc.description.abstractThis study addresses the persistent health challenge of sleeping sickness in sub-Saharan Africa by comprehensively exploring its transmission dynamics. The primary focus is on developing, studying, and analyzing mathematical models spanning from within-host dynamics to multiscale interactions of sleeping sickness. The thesis begins by investigating the dynamics within a single sleeping sickness-infected human host. The model considers the interplay between parasite types, macrophages, and cytokines within the human host. Findings suggest that the immune response play a pivotal part in regulating parasite growth, and the absence of switching enables effective immune system intervention. Two distinct optimal control problems emerge, emphasizing the need to identify the disease stage for effective drug application, thereby preventing parasite persistence and reducing drug toxicity. The study’s second phase focuses on developing an epidemiological model of sleeping sickness transmission among humans, non-human hosts, and tsetse flies. Sensitivity analysis reveals that parameters such as biting rate and death rate are particularly influential. The examination of bifurcation concerning the effective reproductive number (Re) indicates the presence of a backward bifurcation within the system which signifies that the traditional condition of Re < 1 is no longer adequate for achieving effective disease elimination. Disease dynamics are strongly scale dependent, so we propose a multi-temporal scale model that incorporates within-host and between-host disease dynamics. Results are compared with the single-scaled models. Furthermore, the numerical solutions for susceptible humans in both the between-host and multiscale models demonstrated a similar pattern: a rapid reduction in susceptible human populations within the first 50 days in the absence of intervention. The vector profiles in both the multiscale and between-host models showed similar trends, with intervention initially applied at maximum intensity and rapidly reduced within the first 50 days of use. However, a notable distinction arose regarding treatment profiles: whereas within-host results indicated that drugs needed to be administered at maximum dosage to reduce the burden of infection effectively, the opposite was observed in the between-host model. In conclusion, this thesis offers valuable insights into the disease transmission dynamics of sleeping sickness, highlighting the significance of comprehending both within host and between-host interactions. Essentially, our models proved to be more mathematically, numerically, and biologically tractable compared to most standard models used for projecting sleeping sickness.
dc.identifier.urihttps://hdl.handle.net/10413/23550
dc.language.isoen
dc.subject.otherHuman African Trypanosomiasis.
dc.subject.otherWithin-host dynamics.
dc.subject.otherMulti-scale modelling.
dc.subject.otherVector-borne disease.
dc.subject.otherOptimal control.
dc.titleModeling the effectiveness of control measures from the within-host dynamics to the population dynamics of sleeping sickness.
dc.typeThesis
local.sdgSDG4

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