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Mapping tuberculosis treatment outcomes in Ethiopia

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 whet...

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Autores principales: Alene, Kefyalew Addis, Viney, Kerri, Gray, Darren J., McBryde, Emma S., Wagnew, Maereg, Clements, Archie C. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540408/
https://www.ncbi.nlm.nih.gov/pubmed/31138129
http://dx.doi.org/10.1186/s12879-019-4099-8
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author Alene, Kefyalew Addis
Viney, Kerri
Gray, Darren J.
McBryde, Emma S.
Wagnew, Maereg
Clements, Archie C. A.
author_facet Alene, Kefyalew Addis
Viney, Kerri
Gray, Darren J.
McBryde, Emma S.
Wagnew, Maereg
Clements, Archie C. A.
author_sort Alene, Kefyalew Addis
collection PubMed
description 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 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-4099-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-65404082019-06-03 Mapping tuberculosis treatment outcomes in Ethiopia Alene, Kefyalew Addis Viney, Kerri Gray, Darren J. McBryde, Emma S. Wagnew, Maereg Clements, Archie C. A. BMC Infect Dis Research Article 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 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-4099-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-05-28 /pmc/articles/PMC6540408/ /pubmed/31138129 http://dx.doi.org/10.1186/s12879-019-4099-8 Text en © The Author(s). 2019 Open AccessThis 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.
spellingShingle Research Article
Alene, Kefyalew Addis
Viney, Kerri
Gray, Darren J.
McBryde, Emma S.
Wagnew, Maereg
Clements, Archie C. A.
Mapping tuberculosis treatment outcomes in Ethiopia
title Mapping tuberculosis treatment outcomes in Ethiopia
title_full Mapping tuberculosis treatment outcomes in Ethiopia
title_fullStr Mapping tuberculosis treatment outcomes in Ethiopia
title_full_unstemmed Mapping tuberculosis treatment outcomes in Ethiopia
title_short Mapping tuberculosis treatment outcomes in Ethiopia
title_sort mapping tuberculosis treatment outcomes in ethiopia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540408/
https://www.ncbi.nlm.nih.gov/pubmed/31138129
http://dx.doi.org/10.1186/s12879-019-4099-8
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