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dc.contributor.authorOrangi, Mercy Kemunto
dc.date.accessioned2016-10-11T14:13:39Z
dc.date.available2016-10-11T14:13:39Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/11071/4871
dc.descriptionSubmitted in partial fulfillment of the requirements for the Degree of Master of Science in Mobile Telecommunication and Innovationen_US
dc.description.abstractThe ability of people to enjoy a long, healthy life is critical to a developing nation. In Kenya, the mortality and morbidity levels are high, with the World Health Organization closely linking the wide-spread disparities to underlying social, economic, gender and geographical factors. These levels can be lower, especially for a country striving to achieve a middle-income economy status. Further, any meaningful health policy or health program needs to be informed of the statistics of illnesses and deaths occurring and their causes. However, the main problem has been the lack of a clear association or connection between the illnesses and deaths reported and their attributing factors. Further, in Kenya, data on mortality and morbidity, published through various surveys, has mainly been presented in tabular form in spreadsheets and publications. This has proven to be hard to consume, let alone analyze, for purposes of informing health policy makers. In view of the above shortcomings, this study sought to establish a link between the mortality and morbidity levels in Kenyan counties and their causative factors. To understand the current state of health mortality and morbidity levels, this study looked into existing literature on the state of India’s and Kenya’s mortality and morbidity levels, with a keen focus on health policies and government initiatives. First hand data was also collected through questionnaires. Analysis of findings of the research conducted asserted the need of a visualization tool that provides dynamic, real-time manipulation of data on mortality, morbidity and their attributing factors. Consequently, a visualization tool was developed, allowing users to view the data in a more user-friendly format and further providing real-time manipulation of the data to produce user-defined visualizations, which can further be downloaded in various formats. This can, in turn, help policy makers and researchers make data-based decisions in their various studies.en_US
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectHealth Data Visualizationen_US
dc.subjectMortalityen_US
dc.subjectMorbidityen_US
dc.subjectHealth Policiesen_US
dc.subjectMobile Technologyen_US
dc.subjectKenyaen_US
dc.titleA mobile-web application for visualizing mortality and morbidity levels in Kenyan Counties and their attributing factors: a focus on Kenya health policiesen_US
dc.typeThesisen_US


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