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Modelling the optimal efficiency of industrial labour force in the presence of HIV/AIDs pandemic
Author(s)
Takaidza, Isaac
Date Issued
2012
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
In this thesis, we investigate certain key aspects of mathematical modelling to explain the epidemiology of HIV/AIDS at the workplace and to assess the potential benefits of proposed control strategies. Deterministic models to investigate the effects of the transmission dynamics of HIV/AIDS on labour force productivity are formulated. The population is divided into mutually exclusive but exhaustive compartments and a system of differential equations is derived to describe the spread of the epidemic. The qualitative features of their equilibria are analyzed and conditions under which they are stable are provided. Sensitivity analysis of the reproductive number is carried out to determine the relative importance of model parameters to initial disease transmission. Results suggest that optimal control theory in conjunction with standard numerical procedures and cost effective analysis can be used to determine the best intervention strategies to curtail the burden HIV/AIDS is imposing on the human population, in particular to the global economy through infection of the most productive individuals. We utilise Pontryagin’s Maximum Principle to derive and then analyze numerically the conditions for optimal control of the disease with effective use of condoms, enlightenment/educational programs, treatment regime and screening of infectives. We study the potential impact on productivity of combinations of these conventional control measures against HIV. Our numerical results suggest that increased access to antiretroviral therapy (ART) could decrease not only the HIV prevalence but also increase productivity of the infected especially when coupled with prevention, enlightenment and screening efforts.
Additional information
Thesis (DTech (Mechanical Engineering))--Cape Peninsula University of Technology, 2012
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Takaidza_I_DTechThesis_Modelling the optimal efficiency.pdf
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