In this thesis, we study these models and design and analyze robust numerical methods to solve them. To proceed in this direction, first we study the sub-models and then the full model. The first sub-model describes the transmission dynamics of HIV that accounts for behavior change. The impact of HIV educational campaigns is also studied. Further, we explore the effects of behavior change and different responses of individuals to educational campaigns in a situation where individuals may not react immediately to these campaigns. This is done by considering a distributed time delay in the HIV sub-model. This leads to Hopf bifurcations around the endemic equilibria of the model. These bifurcations correspond to the existence of periodic solutions that oscillate around the equilibria at given thresholds. Further, we show how the delay can result in more HIV infections causing more increase in the HIV prevalence. Part of this study is then extended to study a co-infection model of HIV-TB. A thorough bifurcation analysis is carried out for this model. Robust numerical methods are then designed and analyzed for these models. Comparative numerical results are also provided for each model.

Neste texto é feita uma discussão sobre alguns resultados que fornecem condições suficientes para que um difeomorfismo local, do espaço euclideano n-dimensional nele próprio, seja injetivo. Dentro deste cenário, são exploradas as contribuições destes resultados na tentativa de solucionar conhecidas conjecturas no meio científico como a Conjectura Jacobiana e a Conjectura de Ponto Fixo. Do ponto de vista dinâmico, existem relações entre injetividade global e estabilidade assintótica global. Neste sentido, os resultados também são contextualizados com respeito a importantes conjecturas de estabilidade assintótica: Conjectura de Markus-Yamabe e o Problema de LaSalle / We present some results which give suficient conditions for a local diffeomorphism from the n-dimensional Euclidean space into itself be globally injective. Within this context, we consider some partial results addressed to solve the well known Fixed Point Conjecture and Jacobian Conjecture. From the dynamical point of view, there are connections between global injectivity and global asymptotic stability. In this way, we present a solution of the Markus-Yamabe Conjecture and of the LaSalle Problem

Philosophiae Doctor - PhD / There is a growing interest in the dynamics of the co-infection of these two diseases. In this thesis, firstly we focus on studying the effect of a distributed delay representing the incubation period for the malaria parasite in the mosquito vector to possibly reduce the initial transmission and prevalence of malaria. This model can be regarded as a generalization of SEI models (with a class for the latently infected mosquitoes) and SI models with a discrete delay for the incubation period in mosquitoes. We study the possibility of occurrence of backward bifurcation. We then extend these ideas to study a full model of HIV and malaria co-infection. To get further inside into the dynamics of the model, we use the geometric singular perturbation theory to couple the fast and slow models from the full model. Finally, since the governing models are very complex, they cannot be solved analytically and hence we develop and analyze a special class of numerical methods to solve them. / South Africa

The thesis focuses on the qualitative analysis of a general class of SEIRS models in periodic and non-periodic environments. The classical SEIRS model, with standard incidence function, is, first of all, extended to incorporate multiple infectious stages. Using Lyapunov function theory and LaSalle's Invariance Principle, the disease-free equilibrium (DFE) of the resulting SEIⁿRS model is shown to be globally-asymptotically stable whenever the associated reproduction number is less than unity. Furthermore, this model has a unique endemic equilibrium point (EEP), which is shown (using a non-linear Lyapunov function of Goh-Volterra type) to be globally-asymptotically stable for a special case. The SEIⁿRS model is further extended to incorporate arbitrary number of latent stages. A notable feature of the resulting SE^mIⁿRS model is that it uses gamma distribution assumptions for the average waiting times in the latent (m) and infectious (n) stages. Like in the case of the SEIⁿRS model, the SE^mIⁿRS model also has a globally-asymptotically stable DFE when its associated reproduction threshold is less than unity, and it has a unique EEP (which is globally-stable for a special case) when the threshold exceeds unity. The SE^mIⁿRS model is further extended to incorporate the effect of periodicity on the disease transmission dynamics. The resulting non-autonomous SE^mIⁿRS model is shown to have a globally-stable disease-free solution when the associated reproduction ratio is less than unity. Furthermore, the non-autonomous model has at least one positive (non-trivial) periodic solution when the reproduction ratio exceeds unity. It is shown (using persistence theory) that, for the non-autonomous model, the disease will always persist in the population whenever the reproduction ratio is greater than unity. One of the main mathematical contributions of this thesis is that it shows that adding multiple latent and infectious stages, gamma distribution assumptions (for the average waiting times in these stages) and periodicity to the classical SEIRS model (with standard incidence) does not alter the main qualitative dynamics (pertaining to the persistence or elimination of the disease from the population) of the SEIRS model.

The thesis focuses on the qualitative analysis of a general class of SEIRS models in periodic and non-periodic environments. The classical SEIRS model, with standard incidence function, is, first of all, extended to incorporate multiple infectious stages. Using Lyapunov function theory and LaSalle's Invariance Principle, the disease-free equilibrium (DFE) of the resulting SEIⁿRS model is shown to be globally-asymptotically stable whenever the associated reproduction number is less than unity. Furthermore, this model has a unique endemic equilibrium point (EEP), which is shown (using a non-linear Lyapunov function of Goh-Volterra type) to be globally-asymptotically stable for a special case. The SEIⁿRS model is further extended to incorporate arbitrary number of latent stages. A notable feature of the resulting SE^mIⁿRS model is that it uses gamma distribution assumptions for the average waiting times in the latent (m) and infectious (n) stages. Like in the case of the SEIⁿRS model, the SE^mIⁿRS model also has a globally-asymptotically stable DFE when its associated reproduction threshold is less than unity, and it has a unique EEP (which is globally-stable for a special case) when the threshold exceeds unity. The SE^mIⁿRS model is further extended to incorporate the effect of periodicity on the disease transmission dynamics. The resulting non-autonomous SE^mIⁿRS model is shown to have a globally-stable disease-free solution when the associated reproduction ratio is less than unity. Furthermore, the non-autonomous model has at least one positive (non-trivial) periodic solution when the reproduction ratio exceeds unity. It is shown (using persistence theory) that, for the non-autonomous model, the disease will always persist in the population whenever the reproduction ratio is greater than unity. One of the main mathematical contributions of this thesis is that it shows that adding multiple latent and infectious stages, gamma distribution assumptions (for the average waiting times in these stages) and periodicity to the classical SEIRS model (with standard incidence) does not alter the main qualitative dynamics (pertaining to the persistence or elimination of the disease from the population) of the SEIRS model.

Dans ce travail de recherche, nous sommes intéresses par la modélisation de l'hématopoïèse. Les cellules souches hématopoïétiques (CSH) sont des cellules indifférenciées de la moelle osseuse, possédant la capacité de se renouveler et de se différencier (pour la production des globules rouges, globules blancs et les plaquettes). Le processus de l'hématopoïèse souvent révèle des irrégularités qui causent les maladies hématologiques. En modélisant la leucémie myéloide chronique (LMC), une maladie hématologique fréquente, nous représentons l'hématopoïèse des cellules normales et cancéreuses par un système d'équations différentielles ordinaires (EDO). L'homéostasie des cellules normales et différente de l'homéostasie des cellules cancéreuses, et dépend de quelques lignées des cellules normales et cancéreuses. Nous analysons la dynamique globale du modèle pour obtenir les conditions de régénération de l'hématopoïèse ou bien la persistance de la LMC. Nous démontrons aussi que la coexistence des cellules normales et cancéreuses ne peut avoir lieu pour longtemps. Imatinib est un traitement de base de la LMC, avec un dosage variant de 400 à 1000 mg par jour. Certains patients présentent des réponses différentes à la thérapie, pouvant être hématologique, cytogénétique et moléculaire. La thérapie échoue dans deux cas: le patient demande un temps plus long pour réagir, alors il s'agit d'une réponse suboptimale; ou bien le patient résiste après une bonne réponse initiale. Pour déterminer le dosage optimal, nécessaire à la réduction des cellules cancéreuses, nous représentons les effets de la thérapie par un problème de contrôle optimal. Notre but est de minimiser le cout du traitement et le nombre des cellules cancéreuses. La réponse suboptimale, la résistance et le rétablissement sont alors obtenus suivant l'influence de l'imatinib sur les taux de division et de mortalité des cellules cancéreuses. Nous étudions par ailleurs l'hématopoïèse selon un modèle structuré en age, décrivant l'évolution des CSH normales et cancéreuses. Nous démontrons que le taux de division des CSH cancéreuses joue un rôle important dans la détermination du contrôle optimal. En contrôlant la croissance des cellules normales et cancéreuses avec compétition inter spécifique, nous démontrons que le dosage optimal dépend de l'homéostasie des CSH cancéreuses. / Modelling hematopoiesis represents a feature of our research. Hematopoietic stem cells (HSC) are undifferentiated cells, located in bone marrow, with unique abilities of self-renewal and differentiation (production of white cells, red blood cells and platelets).The process of hematopoiesis often exhibits abnormalities causing hematological diseases. In modelling Chronic Myeloid Leukemia (CML), a frequent hematological disease, we represent hematopoiesis of normal and leukemic cells by means of ordinary differential equations (ODE). Homeostasis of normal and leukemic cells are supposed to be different and depend on some lines of normal and leukemic HSC. We analyze the global dynamics of the model to obtain the conditions for regeneration of hematopoiesis and persistence of CML. We prove as well that normal and leukemic cells can not coexist for a long time. Imatinib is the main treatment of CML, with posology varying from 400 to 1000 mg per day. Some affected individuals respond to therapy with various levels being hematologic, cytogenetic and molecular. Therapy fails in two cases: the patient takes a long time to react, then suboptimal response occurs; or the patient resists after an initial response. Determining the optimal dosage required to reduce leukemic cells is another challenge. We approach therapy effects as an optimal control problem to minimize the cost of treatment and the level of leukemic cells. Suboptimal response, resistance and recovery forms are obtained through the influence of imatinib onto the division and mortality rates of leukemic cells. Hematopoiesis can be investigated according to age of cells. An age-structured system, describing the evolution of normal and leukemic HSC shows that the division rate of leukemic HSC plays a crucial role when determining the optimal control. When controlling the growth of cells under interspecific competition within normal and leukemic HSC, we prove that optimal dosage is related to homeostasis of leukemic HSC.

Dans ce mémoire, nous considérons un modèle épidémiologique multigroupe dans une population hétérogène, pour décrire la situation de l’épidémie de la COVID-19 dans une résidence pour personnes âgées. L’hétérogénéité liée ici à l’âge reflète une transmission élevée dûe à des interactions accrues, et un taux de mortalité plus élevé chez les personnes âgées. Du point de vue mathématique, nous obtenons un modèle SEIR multigroupe d’équations intégro-différentielles dans lequel nous considérons une distribution générale de la période infectieuse. Nous utilisons la méthode des fonctions de Lyapunov et une approche de la théorie des graphes pour déterminer le rôle du nombre de reproduction de base \(\mathcal{R}_0\) : l’état d’équilibre sans maladie est globalement asymptotiquement stable et l’épidémie s’éteint dans les deux groupes lorsque \(\mathcal{R}_0 \leq 1\), par contre elle persiste et l’état d’équilibre endémique est globalement asymptotiquement stable lorsque \(\mathcal{R}_0>1\). Les simulations numériques illustrent l’impact des stratégies de contrôle de la santé publique. / In this thesis, we consider a multiple group epidemiological model in a heterogeneous population to describe COVID-19 outbreaks in an elderly residential population. Age-based heterogeneity reflects higher transmission with enhanced interactions, and higher fatality rates in the elderly. Mathematically, we analyse a SEIR model in the form of a system of integro-differential equations with general distribution function for the infectious period. Lyapunov functions and graph-theoretical methods are employed to establish the role played by the basic reproduction ratio \(\mathcal{R}_0\) : global asymptotic stability of the disease-free equilibrium and no sustained outbreak when \(\mathcal{R}_0 \leq 1\), as opposed to persistent outbreak and globally asymptotic endemic equilibrium when \(\mathcal{R}_0>1\). Numerical simulations are presented to illustrate public health control strategies.