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Mapping tuberculosis treatment outcomes in Ethiopia

Alene, Kefyalew Addis; Viney, Kerri; Gray, Darren; McBryde, Emma; Wagnew, Maereg; Clements, Archie

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Background Tuberculosis (TB) is the leading cause of death from an infectious disease in Ethiopia, killing more than 30 thousand people every year. This study aimed to determine whether the rates of poor TB treatment outcome varied geographically across Ethiopia at district and zone levels and whether such variability was associated with socioeconomic, behavioural, health care access, or climatic conditions. Methods A geospatial analysis was conducted using national TB data reported to the...[Show more]

dc.contributor.authorAlene, Kefyalew Addis
dc.contributor.authorViney, Kerri
dc.contributor.authorGray, Darren
dc.contributor.authorMcBryde, Emma
dc.contributor.authorWagnew, Maereg
dc.contributor.authorClements, Archie
dc.date.accessioned2020-10-21T05:46:19Z
dc.date.available2020-10-21T05:46:19Z
dc.identifier.issn1471-2334
dc.identifier.urihttp://hdl.handle.net/1885/212812
dc.description.abstractBackground Tuberculosis (TB) is the leading cause of death from an infectious disease in Ethiopia, killing more than 30 thousand people every year. This study aimed to determine whether the rates of poor TB treatment outcome varied geographically across Ethiopia at district and zone levels and whether such variability was associated with socioeconomic, behavioural, health care access, or climatic conditions. Methods A geospatial analysis was conducted using national TB data reported to the health management information system (HMIS), for the period 2015–2017. The prevalence of poor TB treatment outcomes was calculated by dividing the sum of treatment failure, death and loss to follow-up by the total number of TB patients. Binomial logistic regression models were computed and a spatial analysis was performed using a Bayesian framework. Estimates of parameters were generated using Markov chain Monte Carlo (MCMC) simulation. Geographic clustering was assessed using the Getis-Ord Gi* statistic, and global and local Moran’s I statistics. Results A total of 223,244 TB patients were reported from 722 districts in Ethiopia during the study period. Of these, 63,556 (28.5%) were cured, 139,633 (62.4%) completed treatment, 6716 (3.0%) died, 1459 (0.7%) had treatment failure, and 12,200 (5.5%) were lost to follow-up. The overall prevalence of a poor TB treatment outcome was 9.0% (range, 1–58%). Hot-spots and clustering of poor TB treatment outcomes were detected in districts near the international borders in Afar, Gambelia, and Somali regions and cold spots were detected in Oromia and Amhara regions. Spatial clustering of poor TB treatment outcomes was positively associated with the proportion of the population with low wealth index (OR: 1.01; 95%CI: 1.0, 1.01), the proportion of the population with poor knowledge about TB (OR: 1.02; 95%CI: 1.01, 1.03), and higher annual mean temperature per degree Celsius (OR: 1.15; 95% CI: 1.08, 1.21). Conclusions This study showed significant spatial variation in poor TB treatment outcomes in Ethiopia that was related to underlying socioeconomic status, knowledge about TB, and climatic conditions. Clinical and public health interventions should be targeted in hot spot areas to reduce poor TB treatment outcomes and to achieve the national End-TB Strategy targets.
dc.description.sponsorshipKerri Viney is funded by the National Health and Medical Research Council (NHMRC) through a Sidney Sax Early Career Fellowship from the Australian National Health and Medical Research Council, GNT1121611.
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherBioMed Central
dc.rights© The Author(s).
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceBMC Infectious Diseases
dc.titleMapping tuberculosis treatment outcomes in Ethiopia
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume19
dc.date.issued2019
local.identifier.absfor111706 - Epidemiology
local.identifier.ariespublicationu3102795xPUB1944
local.publisher.urlhttp://www.biomedcentral.com/bmcinfectdis/
local.type.statusPublished Version
local.contributor.affiliationAlene, Kefyalew, College of Health and Medicine, ANU
local.contributor.affiliationViney, Kerri, College of Health and Medicine, ANU
local.contributor.affiliationGray, Darren, College of Health and Medicine, ANU
local.contributor.affiliationMcBryde, Emma, James Cook University
local.contributor.affiliationWagnew, Maereg, Ethiopia Federal Ministry of Health
local.contributor.affiliationClements, Archie, Curtin University
dc.relationhttp://purl.org/au-research/grants/nhmrc/GNT1121611
local.bibliographicCitation.issue474
local.bibliographicCitation.startpage1
local.bibliographicCitation.lastpage11
local.identifier.doi10.1186/s12879-019-4099-8
local.identifier.absseo920503 - Health Related to Specific Ethnic Groups
dc.date.updated2020-07-06T08:20:53Z
local.identifier.scopusID2-s2.0-85066411461
local.identifier.thomsonID4.69331E+11
dcterms.accessRightsOpen Access
dc.provenance© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated
dc.rights.licenseCreative Commons Attribution 4.0 International License
CollectionsANU Research Publications

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