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Comparing different technologies for active TB case-finding among the homeless: a transmission-dynamic modelling study

Homeless persons have elevated risk of tuberculosis (TB) and are under-served by conventional health services. Approaches to active case-finding (ACF) and treatment tailored to their needs are required. A transmission-dynamic model was developed to assess the effectiveness and efficiency of screenin...

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Autores principales: Mugwagwa, Tendai, Stagg, Helen R., Abubakar, Ibrahim, White, Peter J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5780390/
https://www.ncbi.nlm.nih.gov/pubmed/29362378
http://dx.doi.org/10.1038/s41598-018-19757-5
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author Mugwagwa, Tendai
Stagg, Helen R.
Abubakar, Ibrahim
White, Peter J.
author_facet Mugwagwa, Tendai
Stagg, Helen R.
Abubakar, Ibrahim
White, Peter J.
author_sort Mugwagwa, Tendai
collection PubMed
description Homeless persons have elevated risk of tuberculosis (TB) and are under-served by conventional health services. Approaches to active case-finding (ACF) and treatment tailored to their needs are required. A transmission-dynamic model was developed to assess the effectiveness and efficiency of screening with mobile Chest X-ray, GeneXpert, or both. Effectiveness of ACF depends upon the prevalence of infection in the population (which determines screening ‘yield’), patient willingness to wait for GeneXpert results, and treatment adherence. ACF is efficient when TB prevalence exceeds 78/100,000 and 46% of drug sensitive TB cases and 33% of multi-drug resistant TB cases complete treatment. This threshold increases to 92/100,000 if additional post-ACF enhanced case management (ECM) increases treatment completion to 85%. Generally, the most efficient option is one-step screening of all patients with GeneXpert, but if too many patients (>27% without ECM, >19% with ECM) are unwilling to wait the 90 minutes required then two-step screening using chest X-ray (which is rapid) followed by GeneXpert for confirmation of TB is the most efficient option. Targeted ACF and support services benefit health through early successful treatment and averting TB transmission and disease. The optimal strategy is setting-specific, requiring careful consideration of patients’ needs regarding testing and treatment.
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spelling pubmed-57803902018-02-06 Comparing different technologies for active TB case-finding among the homeless: a transmission-dynamic modelling study Mugwagwa, Tendai Stagg, Helen R. Abubakar, Ibrahim White, Peter J. Sci Rep Article Homeless persons have elevated risk of tuberculosis (TB) and are under-served by conventional health services. Approaches to active case-finding (ACF) and treatment tailored to their needs are required. A transmission-dynamic model was developed to assess the effectiveness and efficiency of screening with mobile Chest X-ray, GeneXpert, or both. Effectiveness of ACF depends upon the prevalence of infection in the population (which determines screening ‘yield’), patient willingness to wait for GeneXpert results, and treatment adherence. ACF is efficient when TB prevalence exceeds 78/100,000 and 46% of drug sensitive TB cases and 33% of multi-drug resistant TB cases complete treatment. This threshold increases to 92/100,000 if additional post-ACF enhanced case management (ECM) increases treatment completion to 85%. Generally, the most efficient option is one-step screening of all patients with GeneXpert, but if too many patients (>27% without ECM, >19% with ECM) are unwilling to wait the 90 minutes required then two-step screening using chest X-ray (which is rapid) followed by GeneXpert for confirmation of TB is the most efficient option. Targeted ACF and support services benefit health through early successful treatment and averting TB transmission and disease. The optimal strategy is setting-specific, requiring careful consideration of patients’ needs regarding testing and treatment. Nature Publishing Group UK 2018-01-23 /pmc/articles/PMC5780390/ /pubmed/29362378 http://dx.doi.org/10.1038/s41598-018-19757-5 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Mugwagwa, Tendai
Stagg, Helen R.
Abubakar, Ibrahim
White, Peter J.
Comparing different technologies for active TB case-finding among the homeless: a transmission-dynamic modelling study
title Comparing different technologies for active TB case-finding among the homeless: a transmission-dynamic modelling study
title_full Comparing different technologies for active TB case-finding among the homeless: a transmission-dynamic modelling study
title_fullStr Comparing different technologies for active TB case-finding among the homeless: a transmission-dynamic modelling study
title_full_unstemmed Comparing different technologies for active TB case-finding among the homeless: a transmission-dynamic modelling study
title_short Comparing different technologies for active TB case-finding among the homeless: a transmission-dynamic modelling study
title_sort comparing different technologies for active tb case-finding among the homeless: a transmission-dynamic modelling study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5780390/
https://www.ncbi.nlm.nih.gov/pubmed/29362378
http://dx.doi.org/10.1038/s41598-018-19757-5
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