An integrated knowledge ecosystem for infant mortality in Kilifi health and demographic surveillance system (KHDSS)

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dc.contributor.authorAmadi, David Kivuli
dc.date.accessioned2020-09-22T10:54:08Z
dc.date.available2020-09-22T10:54:08Z
dc.date.issued2019
dc.descriptionA Research Report submitted to the Faculty of Health Science in partial fulfillment of the requirements for the degree of Master of Science (MSc) in Epidemiology - Public Health Informatics October, 2019en_ZA
dc.description.abstractInfant mortality is a key population indicator and remains a problem that requires global attention. Kenya, like many countries in Sub Saharan Africa, did not achieve the Millennium Development Goal number 4 (Reducing childhood mortality by 2015). Factors that contribute to infant mortality require scientific evidence thus focus has been put on visualization applications for the generation of new hypotheses and to inform decision. The need for rapid access to information in an explosive data generation in the public health sector needs a more effective data automation procedure. The aim of this project is to develop a digital ecosystem platform that brings together data from selected observational studies, randomized controlled clinical trials, and national surveys into large composite datasets that give analytical power to answer important questions on child health and surface the insights that create impact. Using 2015 data from Kilifi HDSS for children aged less than one year. Shiny datadriven web application framework for R statistical computing explores and analyses data on a dashboard to run algorithms. The platform provides utilities for data analytics and modeling techniques to answer questions on child health such as the relative effects of pre and postnatal impacts on physical growth. Exploratory data analysis, descriptive statistics as well as multivariable analysis are presented by the use of graphs, tables, maps and rate(s) ratios. The visualization platform allows researchers and policymakers to generate actionable recommendations, predictions, and new hypotheses that will inform decisionen_ZA
dc.description.librarianMT 2020en_ZA
dc.facultyFaculty of Health Sciencesen_ZA
dc.identifier.urihttps://hdl.handle.net/10539/29716
dc.language.isoenen_ZA
dc.titleAn integrated knowledge ecosystem for infant mortality in Kilifi health and demographic surveillance system (KHDSS)en_ZA
dc.typeThesisen_ZA
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