Modelling of smear positive tuberculosis (PTB+) treatment outcome data in Kenya for the period 2002-2007
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Date
2009Author
Kipruto, Hillary K
Type
ThesisLanguage
enMetadata
Show full item recordAbstract
In this research project, we review and use two statistical methods namely poisson
regression and multinomial logit regression are used to model rates of outcomes of
count data.
Thestudy reviews the research work on modelling of count data particularly infectious
diseases. There has been wide use of the two methods in literature but little application
to Tuberculosis modelling. The outcome of smear positive tuberculosis cases namely
cure, treatment completed, out of control, failures, transfer outs and deaths were
modelled using poisson regression and multinomial regression. The results showed that
the two methods can be used to model epidemiological behaviour of the infectious
Tuberculosis and the two methods can be adopted at the national and provincial levels
totrack the occurrence of the outcomes over the years and across the provinces.
The results can be used to track performance of country in terms of the occurrence of
treatment outcomes and the models can be used in provinces and districts. The models
can act as strong epidemiological analysis tools.
Citation
M.Sc (Biometry)Sponsorhip
University of NairobiPublisher
School of Mathematics, University of Nairobi
Description
Master of Science Thesis