Please use this identifier to cite or link to this item: https://hdl.handle.net/10646/937
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dc.contributor.authorMakukula, Zodwa-
dc.date.accessioned2012-09-03T07:31:16Z-
dc.date.available2012-09-03T07:31:16Z-
dc.date.issued2012-09-03-
dc.identifier.urihttp://hdl.handle.net/10646/937-
dc.description.abstractDue to high prevalence of tuberculosis (TB) in developing countries where HIV prevalence is also high, developing effective TB vaccines that will prevent infection and reactivation of latent infection is a high priority. This is because patients infected with HIV are at increased risk of developing active TB because of the high rate of reactivation of latent infection and high degree of susceptibility to new infection. Three mathematical models with TB vaccines were used to predict the most effective epidemic-control strategy in reducing active TB cases. The first model is with pre-exposure TB vaccines and treatment of TB, the second with post-exposure vaccines and treatment of TB, and the last one with both vaccines and treatment of TB. The comparison of effectiveness was based on the reproduction rates and numerical analysis using the forward fourth order Runge-Kutta scheme. The combined strategy was found to be the most effective as an epidemic-control strategy.en_ZW
dc.language.isoen_ZWen_ZW
dc.subjecttuberculosisen_ZW
dc.subjectvaccinesen_ZW
dc.subjecttreatmenten_ZW
dc.subjectTB transmissionen_ZW
dc.subjectmathematical modelen_ZW
dc.titleA Mathematical Model Of Combined Pre-Exposure, Post-Exposure Vaccines And Treatment Of Tuberculosisen_ZW
thesis.degree.advisorHove-Musekwa, S.D. (Dr)-
thesis.degree.countryZimbabween_ZW
thesis.degree.disciplineMathematicsen_ZW
thesis.degree.facultyFaculty of Scienceen_ZW
thesis.degree.grantorUniversity of Zimbabween_ZW
thesis.degree.grantoremailspecialcol@uzlib.uz.ac.zw
thesis.degree.levelMScen_ZW
thesis.degree.nameMaster of science in Mathematicsen_ZW
thesis.degree.thesistypeThesisen_ZW
dc.date.defense2005-06-30-
Appears in Collections:Faculty of Science e-Theses Collection

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