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[journal article]

dc.contributor.authorHiggins, Jeffde
dc.contributor.authorAdamu, Usmande
dc.contributor.authorAdewara, Kehindede
dc.contributor.authorAladeshawe, Adeshinade
dc.contributor.authorAregay, Aronde
dc.contributor.authorBarau, Inuwade
dc.contributor.authorBerens, Andrewde
dc.contributor.authorBolu, Omotayode
dc.contributor.authorDutton, Ninade
dc.contributor.authorIduma, Nnaemekade
dc.contributor.authorJones, Bryantde
dc.contributor.authorKaplan, Briande
dc.contributor.authorMeleh, Sulede
dc.contributor.authorMusa, Meltonde
dc.contributor.authorwa Nganda, Gateide
dc.contributor.authorSeaman, Vincentde
dc.contributor.authorSud, Anupmade
dc.contributor.authorVouillamoz, Stephanede
dc.contributor.authorWiesen, Ericde
dc.date.accessioned2021-11-29T16:06:42Z
dc.date.available2021-11-29T16:06:42Z
dc.date.issued2019de
dc.identifier.issn1476-072Xde
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/76004
dc.description.abstractBackground: Four wild polio-virus cases were reported in Borno State, Nigeria 2016, 1 year after Nigeria had been removed from the list of polio endemic countries by the World Health Organization. Resulting from Nigeria’s decade long conflict with Boko Haram, health officials had been unable to access as much as 60% of the settlements in Borno, hindering vaccination and surveillance efforts. This lack of accessibility made it difficult for the government to assess the current population distribution within Borno. This study aimed to use high resolution, visible band satellite imagery to assess the habitation of inaccessible villages in Borno State. Methods: Using high resolution (31–50 cm) imagery from DigitalGlobe, analysts evaluated the habitation status of settlements in Borno State identified by Nigeria’s Vaccination Tracking System. The analysts looked at imagery of each settlement and, using vegetation (overgrowth vs. cleared) as a proxy for human habitation, classified settlements into three categories: inhabited, partially abandoned, and abandoned. Analysts also classified the intact percentage of each settlement starting at 0% (totally destroyed since last assessment) and increasing in 25% intervals through 100% (completely intact but not expanded) up to 200+% (more than doubled in size) by looking for destroyed buildings. These assessments were then used to adjust previously established population estimates for each settlement. These new population distributions were compared to vaccination efforts to determine the number of children under 5 unreached by vaccination teams. Results: Of the 11,927 settlements assessed 3203 were assessed as abandoned (1892 of those completely destroyed), 662 as partially abandoned, and 8062 as fully inhabited as of December of 2017. Comparing the derived population estimates from the new assessments to previous assessment and the activities of vaccination teams shows that an estimated 180,155 of the 337,411 under five children who were unreached in 2016 were reached in 2017 (70.5% through vaccination efforts in previously inaccessible areas, 29.5% through displacement to accessible areas). Conclusions: This study’s methodology provides important planning and situation awareness information to health workers in Borno, Nigeria, and may serve as a model for future data gathering efforts in inaccessible regions.de
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.titleFinding inhabited settlements and tracking vaccination progress: the application of satellite imagery analysis to guide the immunization response to confirmation of previously-undetected, ongoing endemic wild poliovirus transmission in Borno State, Nigeriade
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalInternational Journal of Health Geographics
dc.source.volume18de
dc.publisher.countryGBRde
dc.subject.classozBevölkerungde
dc.subject.classozPopulation Studies, Sociology of Populationen
dc.subject.classozErhebungstechniken und Analysetechniken der Sozialwissenschaftende
dc.subject.classozMethods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methodsen
dc.subject.classozGesundheitspolitikde
dc.subject.classozHealth Policyen
dc.subject.thesozNigeriade
dc.subject.thesozNigeriaen
dc.subject.thesozImpfungde
dc.subject.thesozvaccinationen
dc.subject.thesozBevölkerungsdichtede
dc.subject.thesozpopulation densityen
dc.subject.thesozBesiedlungde
dc.subject.thesozsettlingen
dc.subject.thesozDatengewinnungde
dc.subject.thesozdata captureen
dc.subject.thesozKindde
dc.subject.thesozchilden
dc.subject.thesozPublic Healthde
dc.subject.thesozpublic healthen
dc.identifier.urnurn:nbn:de:0168-ssoar-76004-8
dc.rights.licenceCreative Commons - Namensnennung 4.0de
dc.rights.licenceCreative Commons - Attribution 4.0en
ssoar.contributor.institutionFDBde
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10035654
internal.identifier.thesoz10045567
internal.identifier.thesoz10038795
internal.identifier.thesoz10037814
internal.identifier.thesoz10040547
internal.identifier.thesoz10034597
internal.identifier.thesoz10053580
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo1-10de
internal.identifier.classoz10303
internal.identifier.classoz10105
internal.identifier.classoz11006
internal.identifier.journal1540
internal.identifier.document32
internal.identifier.ddc300
dc.identifier.doihttps://doi.org/10.1186/s12942-019-0175-yde
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence16
internal.identifier.pubstatus1
internal.identifier.review1
dc.subject.classhort10300de
dc.subject.classhort10100de
dc.subject.classhort11000de
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse


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