Towards a Spatial-Temporal Model of Prevalence of Nodding Syndrome and Epilepsy
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Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
Nodding syndrome is an emerging disease which have unknown transmission patterns and no properly
established mechanisms for diagnosis leading to numerous hypothetical postulations. It has affected
thousands of children in Uganda with debilitating effect and serious economic consequences. Spatial temporal
analysis may provide a quick mechanism to establish comparative understanding of the various
hypotheses ascribed to nodding syndrome and any other emerging diseases with similar clinical
manifestation. There is considerable suspicion that “nodding syndrome is a form of epilepsy”, a hypothesis
that has hardly been investigated in literature. The aim of the study described in this paper is to establish
spatial-temporal relationships between ailments diagnosed as nodding syndrome and ailments diagnosed as
epilepsy. An exploratory cross section survey in three districts of Northern Uganda was done. Spatial data
of health centers were recorded and ArcGIS was used for display. The findings show significant spatial temporal
correlation of diagnosis reporting of nodding syndrome to epilepsy. The regression statistics
overall, epilepsy significantly (p < 0.05) ex-plains about 58% of Nodding syndrome variability. The F-statistic
shows a very highly significant value (p = 8.20481E-13; p < 0.05), meaning that the output of the
regression is not by chance.
Description
Keywords
Nodding syndrome, Emerging diseases, Surveillance, Spatial-temporal, Geographic information system