Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/27419
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dc.contributor.authorAbdullahi, Usman-
dc.contributor.authorIsah, A-
dc.contributor.authorAbubakar, U-
dc.contributor.authorMayaki, J-
dc.date.accessioned2024-04-24T15:49:59Z-
dc.date.available2024-04-24T15:49:59Z-
dc.date.issued2022-01-31-
dc.identifier.citationA. Usman; A. Isah; U. Abubakar, & M. Jamesen_US
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/27419-
dc.description.abstractThis study used a multivariate negative binomial model to capture the Spatiotemporal endemic-epidemic of infectious disease and explore the spatial and temporal patterns of cholera outbreaks in Nigeria. The model for the epidemic part measured spatial weights for the disease spread across the geographical neighboring regions and the endemic part accounted for temporal variation of disease incidence. Weekly count data on cholera from the Nigeria Department of Disease Control and Monitoring Epidemiology (NCDC SED) between January 1st and November 19th, 2018 was used to illustrate the model. In fitting the model, the study has shown that the model with seasonality and autoregressive components provided an adequate fit for the cholera count data and also perform better than the model without seasonality and autoregression for modelling the Spatiotemporal dependency structure of cholera diseaseen_US
dc.description.sponsorshipSelfen_US
dc.language.isoenen_US
dc.publisherAsian Journal of Probability and Statisticsen_US
dc.relation.ispartofseriesAJPAS.79858;16-
dc.subjectDiseaseen_US
dc.subjectSurveillanceen_US
dc.subjectEpidemic proportionen_US
dc.subjectNegative binomialen_US
dc.subjectSpatiotemporal dependenceen_US
dc.subjectCholeraen_US
dc.titleSpatiotemporal Modelling of Endemic-epidemic Cholera in Nigeriaen_US
dc.typeArticleen_US
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