A-Geo-Informatics-Technique-for-the-Management-of-Meningitis-Epidemic-Distributions-in-Northern-Nigeria

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dc.contributor.authorJegede, Margaret O.
dc.contributor.authorAyanlade, Sina
dc.contributor.authorAyanlade, Oluwatoyin S. Ayanlade
dc.contributor.authorBaloye, David O.
dc.date.accessioned2023-05-13T17:06:51Z
dc.date.available2023-05-13T17:06:51Z
dc.date.issued2015-07
dc.descriptionInternational Journal of Information Resources Management,P.15-28en_US
dc.description.abstractThis study aims at examining and mapping the spatiotemporal distribution of meningitis epidemic, in relation to climate variability, using GIS and Remote Sensing techniques. Using the northern part of Nigeria as a case study, data on meningitis epidemic were obtained from the archive of National Bureau of Statistics, Nigeria for the periods between 1998 and 2013. The data were updated with collection from Nigeria Demographic and Health Survey (NDHS). Also, Nigerian Ministry of Health has compiled consistent statistics on meningitis incidence for the periods. A meningitis distribution map was derived from an environmentally-driven form of predicted probability of epidemic experience as it is in International Research Institute for Climate and Society (IRI) Database. The results showed that Meningitis Epidemic is very high during months with low rainfall. Thus, seasonality of rainfall and temperature are important determinants of Meningitis Epidemic incidence in the Northern part of Nigeria. Therefore, it can be conrmed, as cited in some literatures, that the distribu- tion of the epidemics has a strong association with the environment, especially climate variability. Although meningitis surveillance systems in Nigeria have improved, they still fall short of the sensitivity required to demonstrate incidence changes in vaccinated and non-vaccinated cohorts and complementary approaches may be needed to demonstrate the impact of the vaccines. There is however, a need for a new technology and innovation like an integrated GIS, and other environmental modeling system, to allow health practitioners as well as policy makers, for better management, productivity and protability.en_US
dc.identifier.otherDOI: 10.4018/IRMJ.2015070102
dc.identifier.urihttps://ir.oauife.edu.ng/123456789/5459
dc.language.isoenen_US
dc.publisherInformation Resources Management Journalen_US
dc.subjectGeo-Informaticsen_US
dc.subjectMeningitis Epidemicen_US
dc.subjectNigeriaen_US
dc.subjectmeningitis surveillance systems in Nigeriaen_US
dc.subjecthealth practitionersen_US
dc.titleA-Geo-Informatics-Technique-for-the-Management-of-Meningitis-Epidemic-Distributions-in-Northern-Nigeriaen_US
dc.typeJournalen_US
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