Browsing by Author "Ssemaluulu, Paul"

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    Conceptual Modeling of Nodding Syndrome: A System Dynamics and Sequence Approaches
    (2018-01) Ongaya, Kizito; Ssemaluulu, Paul; Oyo, Benedict; Bongomin, Pido
    Conceptual modelling of nodding syndrome (NS) has hardly been considered in most scientific literature although symptoms of the disease have been widely studied. A conceptual model is a representation of hypothesis about a system under investigation and enables a comparison between hypothesis and data. Since nodding syndrome is an unexplained neurological illness that mainly affects children aged between 5 to 15 years, without specific diagnosis and treatment, the aetiology remains unknown and under investigation, conceptual modelling may be a crucial ingredient in understanding the disease. The purpose of the study is therefore, to represent nodding syndrome occurrence and immune-pathogenic pathways in the causation of nodding syndrome using system dynamics approaches. We have used systematic review method to filter literature on nodding syndrome from the year. We also used Systems Dynamic Approach and we emphasized confirmed scientific investigation to enable the relationships conform to reality. Vensim software was preferred for implementation of the casual-loop diagrams. Microsoft Office Visio 2007 was identified as suitable for implementation of the sequence conceptual model of nodding syndrome for its ability to show interactions between electrolytes and other actors. Our findings were that system dynamics approach has not been used research of nodding syndrome. More so, conceptual modeling was not considered by most articles.
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    Mapping of Prevalence of Nodding Syndrome and Associated Epilepsy Reporting in Uganda: Spatial – Temporal Approach
    (AGILE, 2018-12-15) Ongaya, Kizito; Oyo, Benedict; Ssemaluulu, Paul; Maiga, Gilbert
    In recent years, transmission of diseases has exhibited new spatial and temporal patterns. Emerging diseases are being discovered more often. Some have unknown transmission patterns and mechanisms for diagnosis. This results to numerous hypothetical postulations just as in the case of nodding syndrome which has affected thousands of children in Uganda. Spatial-temporal analysis may provide a quick mechanism to establish comparative understanding of the various hypotheses ascribed to an emerging disease. This situation, is particularly seen in nodding syndrome where there is considerable suspicion that nodding syndrome is a form of epilepsy. Little literature is available on spatial-temporal comparison between incidences of these two ailments. The aim of this paper is to establish spatial-temporal relationships between ailments diagnosed as nodding syndrome and ailments diagnosed as epilepsy. We carried out an exploratory survey in three districts of Northern Uganda. Spatial data of health centres were recorded and ArcGIS was used for display. Our findings established that, there was significant spatial-temporal relationship of diagnosis reporting of nodding syndrome and epilepsy. The study concludes that the surveillance mechanisms for nodding syndrome established in 2012 are effective. At the same time, the study affirms that in the event of occurrence of an emerging disease, when there is no established clinical diagnosis, geographical information systems approach is an effective alternative investigation mechanism to establish relationships between hypothetically similar outbreaks.