Modeling the transmission dynamics of brucellosis

Abstract

Brucellosis, a neglected zoonotic disease remains a major public health problem world over. It affects domesticated animals, wildlife and humans. With large pastoral communities, and demand for meat and livestock production to double by 2050, brucellosis poses a major threat to the public health and economic growth of several developing nations whose economies rely heavily on agricultural exports. Since human-to-human transmission of the disease is rare the ultimate management of human brucellosis can be achieved through effective control of brucellosis in animal population. Hence there is need to gain a better and more comprehensive understanding of effective ways to control the disease in animal populations. Mathematical modeling, analysis and simulation offer a useful means to understand the transmission and spread of brucellosis so that effective disease control measures could be designed. In this dissertation, five epidemiological models that seek to evaluate the role of intervention strategies on the transmission dynamics of brucellosis in animal population have been studied. Firstly, a non-autonomous model that focuses on evaluating the impact of animal vaccination and environmental decontamination in a periodic environment, is introduced. Secondly, a modeling framework that seeks to improve our quantitative understanding of the influence of chronic brucellosis and culling control on brucellosis dynamics in periodic and non-periodic environments, is considered. Thirdly, a deterministic brucellosis model that incorporates heterogeneity and seasonality is studied. Fourthly, we evaluated the effects of short-term animal movements on the transmission dynamics of brucellosis through a two-patch model. Finally a model that incorporates two discrete delays and culling of infected animals displaying signs of brucellosis infection is proposed and analysed. All the proposed models incorporate relevant biological and ecological factors as well as possible disease intervention strategies. Epidemic and endemic analysis of the models have been performed, with a focus on the threshold dynamics characterized by the basic reproduction numbers. In addition, numerical simulation results are presented to demonstrate the analytical findings. A brief summary of the main results of the thesis and an outline of some possible future research directions rounds up the thesis.