Thesis (M.S.)--University of North Texas, August, 2009. / Title from title page display. Includes bibliographical references.

Thesis (M.S.)--University of North Texas, May, 2009. / Title from title page display. Includes bibliographical references.

published_or_final_version / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy

Thesis (M. S.)--Computing, Georgia Institute of Technology, 2009. / Committee Chair: David Bader; Committee Co-Chair: Peter Sloot; Committee Member: Richard Vuduc.

Thesis (M.A.)--University of North Carolina at Wilmington, 2005. / Includes bibliographical references (leaves: 157-172)

Thesis (MTech (Biomedical Technology))--Cape Peninsula University of Technology, 2007. . / Non-tuberculous mycobacteria (NTM) are often isolated from Human Immunodeficiency Virus (HIV) infected individuals, but there is very little information documented about the prevalence of NTM in community settings. An increase in NTM infection is also noted in HIV-negative people. Although it is as yet unknown whether the organisms cause desease in HIV-negative individuals or whether they are merely commensal organisms, their affect on HIV-positive individuals is unquestionable.

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For explanation and prediction of the evolution of infectious diseases in populations, researchers often use simplified mathematical models for simulation. We believe that the results from these models are often questionable when the epidemic dynamics becomes more complex, and that developing more realistic models is intractable. In this dissertation we propose to simulate infectious disease propagation using dynamic and complex networks. We present the Simulator of Epidemic Evolution using Complex Networks (SEECN), an expressive and high-performance framework that combines algorithms for graph generation and various operators for modeling temporal dynamics. For graph generation we use the Kronecker algorithm, derive its underlying statistical structure and exploit it for a variety of purposes. Then the epidemic is evolved over the network by simulating the dynamics of the population and the epidemic simultaneously, where each type of dynamics is performed by a separate operator. All dynamics operators can be fully and independently parameterized, facilitating incremental model development and enabling different influences to be toggled for differential analysis. As a prototype, we simulate two relatively complex models for the HIV epidemic and find a remarkable fit to reported data for AIDS incidence and prevalence. Our most important conclusion is that the mere dynamics of the HIV epidemic is sufficient to produce rather complex trends in the incidence and prevalence statistics, e.g. without the introduction of particularly effective treatments at specific times. We show that this invalidates assumptions and conclusions made previously in the literature, and argue that simulations used for explanation and prediction of trends should incorporate more realistic models for both the population and the epidemic than is currently done. In addition, we substantiate a previously predicted paradox that the availability of Highly Active Anti-Retroviral Treatment likely causes an increased HIV incidence.

Thesis (MTech (Biomedical Technology))--Cape Peninsula University of Technology, 2007 / Reinfection is an important mechanism leading to recurrent tuberculosis. Recently, molecular epidemiological studies have shown that in high incidence settings, recurrent tuberculosis may occur through reinfection. Animal model experiments have shown that a reinfecting mycobacterial strain is specifically targeted to existing granulomas and that these structures are more dynamic than was previously thought. In this study we hypothesised that primary infection with M. tuberculosis may reprogramme human macrophages thereby preventing or facilitating reinfection with a secondary mycobacterial strain. Two antibiotic-resistant M. tuberculosis H37Rv variants were generated by electrotransformation of marked plasmids, designated KanRand HygR . A THP1 human macrophage cell line was infected and reinfected with different combinations of these marked strains as well as a hypervirulent M. tuberculosis Beijing strain. Mycobacterial growth has been assessed by colony forming unit enumeration and confirmed with polymerase chain reaction (PCR) analysis. In vitro growth curves of wild-type and differentially marked M. tuberculosis H37Rv Kan Rand HygR strains were compared in the BACTECTM mycobacterial growth indicator tube (MGITTM) system in parallel with conventional liquid culturing. In vitro liquid culture growth curves of hypervirulent clinical Beijing strain isolates were also compared to M. tuberculosis H37Rv growth curves. Through this it was established that there was no fitness cost as result of plasmid integration and that these strains of varying virulence had similar growth curves. Competitive dynamics within THP1 human macrophage cells were then assessed and have shown that there were no significant differences in growth patterns between primary and secondary infecting strains during THP1 cell reinfection. The findings of this study answered fundamental questions regarding reinfection of mycobacterial strains. It was established here that human macrophages can indeed be reinfected with a second virulent mycobacterial strain.

Identifying and tracking individuals affected by this virus in densely populated areas is a unique and an urgent challenge in the public health sector. Currently, mapping the spread of the Ebola virus is done manually, however with the help of social contact networks we can model dynamic graphs and predictive diffusion models of Ebola virus based on the impact on either a specific person or a specific community. With the help of this model, we can make more precise forward predictions of the disease propagations and to identify possibly infected individuals which will help perform trace – back analysis to locate the possible source of infection for a social group. This model will visualize and identify the families and tightly connected social groups who have had contact with an Ebola patient and is a proactive approach to reduce the risk of exposure of Ebola spread within a community or geographic location. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection