Thesis (PhD)--Montana State University--Bozeman, 2009. / Typescript. Chairperson, Graduate Committee: Allen G. Harmsen. Includes bibliographical references (leaves 103-129).

Thesis (M.P.H.)--University of Hong Kong, 2005.

Thesis (M. PH) -- University of the Western Cape, 2008. / Includes bibliographic references (leaves 46-49).

Thesis (Ph. D.)--University of California, 1920. / "From George Williams Hooper foundation for medical research, University of California medical school, San Francisco." "Reprinted from the Journal of infectious diseases, vol. 27, no. 5, Nov. 1920." Typed approval page inserted. Bibliography: p. 93-96.

Thesis (M.S.)--University of Wisconsin--Madison, 1969. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

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Mosquito-borne diseases account for hundreds of thousands of deaths each year, highlighting the need for successful intervention methods, which can be targeted at either the pathogen, mosquito vector, or human host. This thesis aims to contribute to better intervention methods focused against malaria and dengue by either (i) improving available research tools, (ii) enhancing the understanding of a promising intervention method or (iii) designing new intervention candidates. Firstly, a superior method for studying in vitro malaria infection of the liver is shown, with implications for vaccine and drug interventions. Secondly, the biology of Wolbachia infection in Anopheles gambiae mosquitoes in the context of the target of rapamycin signalling cascade is investigated in an attempt to improve our understanding of its malaria inhibitory phenotype and inability to stably infect An. gambiae mosquitoes. Finally, an algorithm is developed for the design of a hypothesis driven conservation-based vaccine against viral mosquito diseases with a particular focus on dengue.

To investigate how an infectious disease spreads, it is desirable to use the observed surveil­lance data to discover the underlying (often hidden) disease transmission networks. Previous studies have provided methods for inferring information diffusion networks in which each node corresponds to an individual person within the diffusion network. However, in the case of disease transmission, to effectively propose and implement intervention strategies, it is more realistic and reasonable for policy makers to study the diffusion patterns at a metapop­ulation level, that is, to consider disease transmission networks in which nodes represent subpopulations, and links indicate their interrelationships. Such networks can be useful in several ways: (i) to investigate hidden impact factors that in.uence epidemic dynamics, (ii) to reveal possible sources of epidemic outbreaks, and (iii) to practically develop and/or improve strategies for controlling the spread of infectious diseases. Therefore, this thesis addresses the problem of inferring disease transmission networks at a metapopulation level. A network inference method called NetEpi (Network Epidemic) is developed and evaluated using both synthetic and real-world datasets. The experimental results show that NetEpi can recover most of the ground-truth disease transmission networks using only surveillance data.

Thesis (M.Sc.) (Applied Mathematics) --University of Limpopo, 2008. / In this dissertation, two non-linear mathematical models are proposed and analyzed to investigate the spread of infectious diseases in a variable size population through horizontal transmission in the presence of preventive or therapeutic vaccines which are capable of inducing temporary immunity and wane in time. In modeling the transmission dynamics, the population is divided into three subclasses namely; Susceptibles, Infectives and Vaccinated groups. It is assumed that both Vaccinated and Susceptible individuals are recruited into the community and can only become infected via contacts with the infectives group but the rate at which the vaccinated group may contract the diseases is extremely very low depending on the efficacy of the vaccine. All infectives are assumed to move at a constant rate to both Vaccinated and Susceptible groups. These models are analyzed by using the stability theory of differential equations and numerical simulation. The models exhibit two equilibria namely; the disease-free and the endemic equilibria. It is shown that if the vaccination reproduction number R0 < 1, the disease-free equilibrium is always globally asymptotically stable and in such a case the endemic equilibrium does not exist and the disease can be totally eliminated in the community. However, if R0 > 1, a unique endemic equilibrium exists that is locally asymptotically stable and consequently the equilibrium values of infective, vaccinated and susceptible population can be maintained at desired levels. Numerical simulations implemented on MAPLE using both Adomian decomposition technique and Runge-Kutta integration schemes, support our analytical conclusions and illustrate possible behaviour scenarios of the models. / International Pentecostal Holiness Church, Limpopo Provincial Treasury, National Student Financial Aid Scheme and National Research Foundation

Call number: LD2668 .T4 1943 C6 / Master of Science