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Mathematical modelling of the HIV/AIDS epidemic and the effect of public health educationVyambwera, Sibaliwe Maku January 2014 (has links)
>Magister Scientiae - MSc / HIV/AIDS is nowadays considered as the greatest public health disaster of modern time.
Its progression has challenged the global population for decades. Through mathematical
modelling, researchers have studied different interventions on the HIV pandemic, such as treatment, education, condom use, etc. Our research focuses on different compartmental models with emphasis on the effect of public health education. From the point of view of statistics, it is well known how the public health educational programs contribute towards the reduction of the spread of HIV/AIDS epidemic. Many models have been studied towards understanding the dynamics of the HIV/AIDS epidemic. The impact of ARV treatment have been observed and analysed by many researchers. Our research studies and investigates a compartmental model of HIV with treatment and education campaign. We study the existence of equilibrium points and their stability. Original contributions of this dissertation are the modifications on the model of Cai et al. [1], which enables us to use optimal control theory to identify optimal roll-out of strategies to control the HIV/AIDS. Furthermore, we introduce randomness into the model and we study the almost sure exponential stability of the disease free equilibrium. The randomness is regarded as environmental perturbations in the system. Another contribution is the global stability analysis on the model of Nyabadza et al. in [3]. The stability thresholds are compared for the HIV/AIDS in the absence of any intervention to assess the possible community benefit of public health educational campaigns. We illustrate the results by way simulation The following papers form the basis of much of the content of this dissertation, [1 ] L. Cai, Xuezhi Li, Mini Ghosh, Boazhu Guo. Stability analysis of an HIV/AIDS epidemic model with treatment, 229 (2009) 313-323. [2 ] C.P. Bhunu, S. Mushayabasa, H. Kojouharov, J.M. Tchuenche. Mathematical Analysis of an HIV/AIDS Model: Impact of Educational Programs and Abstinence in Sub-Saharan Africa. J Math Model Algor 10 (2011),31-55. [3 ] F. Nyabadza, C. Chiyaka, Z. Mukandavire, S.D. Hove-Musekwa. Analysis of an HIV/AIDS model with public-health information campaigns and individual with-drawal. Journal of Biological Systems, 18, 2 (2010) 357-375. Through this dissertation the author has contributed to two manuscripts [4] and [5], which are currently under review towards publication in journals, [4 ] G. Abiodun, S. Maku Vyambwera, N. Marcus, K. Okosun, P. Witbooi. Control and sensitivity of an HIV model with public health education (under submission). [5 ] P.Witbooi, M. Nsuami, S. Maku Vyambwera. Stability of a stochastic model of HIV population dynamics (under submission).
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Mathematical modeling of TB disease dynamics in a crowded population.Maku Vyambwera, Sibaliwe January 2020 (has links)
Philosophiae Doctor - PhD / Tuberculosis is a bacterial infection which is a major cause of death worldwide. TB is a
curable disease, however the bacterium can become resistant to the first line treatment
against the disease. This leads to a disease called drug resistant TB that is difficult
and expensive to treat. It is well-known that TB disease thrives in communities in overcrowded
environments with poor ventilation, weak nutrition, inadequate or inaccessible
medical care, etc, such as in some prisons or some refugee camps. In particular, the World
Health Organization discovered that a number of prisoners come from socio-economic disadvantaged
population where the burden of TB disease may be already high and access
to medical care may be limited. In this dissertation we propose compartmental models of
systems of differential equations to describe the population dynamics of TB disease under
conditions of crowding. Such models can be used to make quantitative projections of TB
prevalence and to measure the effect of interventions. Indeed we apply these models to
specific regions and for specific purposes. The models are more widely applicable, however
in this dissertation we calibrate and apply the models to prison populations.
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