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dc.contributor.authorLyavara, Micheal
dc.date.accessioned2020-01-14T09:19:35Z
dc.date.available2020-01-14T09:19:35Z
dc.date.issued2019-09
dc.identifier.urihttp://hdl.handle.net/10570/7958
dc.descriptionA Project report Submitted to the School of Computing and Informatics Technology, Makerere University for the Study Leading to a project report in Partial Fulfillment of the Requirements for the Award of the Degree of Master of Science in Information Systems of Makerere Universityen_US
dc.description.abstractEnvironmental factors like temperature, rainfall and humidity are assumed to play an important role in the incidence of typhoid fever. According to (Wang, 2012), climatic variables such as, rainfall, vapour pressure and temperature have an important effect on the transmission and distribution of typhoid infections in human populations. Kabwana noted that high typhoid incidences in 2015 indicate that the Ugandan population is susceptible to a typhoid outbreak. The Objectives of this study was to develop a Decision Support System for predicting occurrence of typhoid based on environmental risk factors which will help MoH and IPs in the Health sector to plan better and make informed decisions The project will focus on monthly typhoid data trends from MoH national reporting system for the period 2015-2017 and rainfall, temperature and humidity data from UNMA for the same period 2015-2017 for Kampala district which was used as the case study. The study followed a rigorous research process which included analyzing the current systems and Object-oriented strategy for design system design. Data collected for the same period was analyzed using STATA and a prediction model developed and integrated into the prototype. An interview guide was used to collect useful information to help in understanding the data flow. After running the prediction model, It was discovered that Temperature and rainfall affected the incidence of typhoid while humidity has no significant effect on the results. The DSS developed will facilitate the process of capturing environmental variables that have a causal effect to typhoid occurrence, predicting typhoid fever cases, and outputting the forecast typhoid cases. Integration of such a system with capabilities of predicting expected typhoid cases with eHMIS should be done to enable quick access to information, ease of use, making more informed decisions and planning.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectEnvironmental factoren_US
dc.subjectTyphoiden_US
dc.subjectFeveren_US
dc.titleDecision support system for predicting Typhoid disease occurrence based on environmental factorsen_US
dc.title.alternativeCase of Kampala District, Ugandaen_US
dc.typeThesisen_US


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