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dc.rights.licenseCC BY
dc.contributor.authorAbdul, Iddrisu Wahab
dc.contributor.authorAnkamah, Sylvia
dc.contributor.authorIddrisu, Abdul-Karim
dc.contributor.authorDanso, Evans
dc.date.accessioned2020-02-12T14:19:44Z
dc.date.available2020-02-12T14:19:44Z
dc.date.issued2020
dc.identifier.citationAbdul, I. W., Ankamah, S., Iddrisu, A. & Danso, E. (2020) Space-time analysis and mapping of prevalence rate of tuberculosis in Ghana. Scientific African (In Press).
dc.identifier.issn2468-2276
dc.identifier.urihttps://eresearch.qmu.ac.uk/handle/20.500.12289/10523
dc.identifier.urihttps://doi.org/10.1016/j.sciaf.2020.e00307
dc.descriptionFrom Elsevier via Jisc Publications Router
dc.descriptionHistory: issue date 2020-02-08
dc.descriptionArticle version: AM
dc.descriptionItem not available in this repository.
dc.description.abstractBackground Global fight against tuberculosis (TB) has received increasing attention over the years. However, the disease remains one of the top-most global health problems, especially in Sub-Saharan Africa and Ghana.
dc.description.abstractAims This paper examined geographical (regional) and seasonal distribution of TB cases providing relative risk of TB exposure in Ghana and step by step procedure to perform the analysis.
dc.description.abstractMethods and material We modelled reported TB cases between 2015 and 2018 using wavelet analysis and applied maximum covariance analysis (MCA) to determine regional and seasonal patterns and the risk of TB exposure in Ghana. This study is based on the old administrative regions of Ghana.
dc.description.abstractResults More TB cases were recorded in the Greater Accra and Ashanti regions and less cases in the rest of the regions. There is significant increase in the number of TB cases from 2015 to 2018. High number of TB cases is observed in the dry season relative to the rainy season. There is high variability in TB prevalence with high prevalence moving towards the Southern part of Ghana.
dc.description.abstractConclusion The study highlights that TB cases is clustered in space and time and that even at small spatial scale, differences in prevalence can be substantial. The prevelance of TB exposure is higher in the dry season relative to the rainy season. Hence, enough resources should be timely provided during the dry season as well as intensifying preventive strategies to control the spread of the disease.
dc.description.urihttps://doi.org/10.1016/j.sciaf.2020.e00307
dc.publisherElsevier
dc.relation.ispartofScientific African
dc.rights©2020 The Author(s).
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectSpace-time Modeling
dc.subjectTuberculosis
dc.subjectTuberculosis Prevalence
dc.subjectWavelet Analysis
dc.subjectWavelet Cluster Analysis
dc.titleSpace-time analysis and mapping of prevalence rate of tuberculosis in Ghana
dc.typearticle
dcterms.accessRightsnone
dc.date.updated2020-02-11T01:34:36Z
dc.description.ispublishedinpress
refterms.dateAccepted2020-01-31
qmu.authorDanso, Evans
qmu.centreInstitute for Global Health and Development
dc.description.statusinpress


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