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The impact of active case finding on transmission dynamics of tuberculosis: A modelling study

BACKGROUND: In the last decade, active case finding (ACF) strategies for tuberculosis (TB) have been implemented in many diverse settings, with some showing large increases in case detection and reporting at the sub-national level. There have also been several studies which seek to provide evidence...

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Autores principales: Ayabina, Diepreye Victoria, Gomes, M. Gabriela M., Nguyen, Nhung Viet, Vo, Luan, Shreshta, Suvesh, Thapa, Anil, Codlin, Andrew James, Mishra, Gokul, Caws, Maxine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604297/
https://www.ncbi.nlm.nih.gov/pubmed/34797864
http://dx.doi.org/10.1371/journal.pone.0257242
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author Ayabina, Diepreye Victoria
Gomes, M. Gabriela M.
Nguyen, Nhung Viet
Vo, Luan
Shreshta, Suvesh
Thapa, Anil
Codlin, Andrew James
Mishra, Gokul
Caws, Maxine
author_facet Ayabina, Diepreye Victoria
Gomes, M. Gabriela M.
Nguyen, Nhung Viet
Vo, Luan
Shreshta, Suvesh
Thapa, Anil
Codlin, Andrew James
Mishra, Gokul
Caws, Maxine
author_sort Ayabina, Diepreye Victoria
collection PubMed
description BACKGROUND: In the last decade, active case finding (ACF) strategies for tuberculosis (TB) have been implemented in many diverse settings, with some showing large increases in case detection and reporting at the sub-national level. There have also been several studies which seek to provide evidence for the benefits of ACF to individuals and communities in the broader context. However, there remains no quantification of the impact of ACF with regards to reducing the burden of transmission. We sought to address this knowledge gap and quantify the potential impact of active case finding on reducing transmission of TB at the national scale and further, to determine the intensification of intervention efforts required to bring the reproduction number (R(0)) below 1 for TB. METHODS: We adopt a dynamic transmission model that incorporates heterogeneity in risk to TB to assess the impact of an ACF programme (IMPACT TB) on reducing TB incidence in Vietnam and Nepal. We fit the models to country-level incidence data using a Bayesian Markov Chain Monte Carlo approach. We assess the impact of ACF using a parameter in our model, which we term the treatment success rate. Using programmatic data, we estimate how much this parameter has increased as a result of IMPACT TB in the implementation districts of Vietnam and Nepal and quantify additional efforts needed to eliminate transmission of TB in these countries by 2035. RESULTS: Extending the IMPACT TB programme to national coverage would lead to moderate decreases in TB incidence and would not be enough to interrupt transmission by 2035. Decreasing transmission sufficiently to bring the reproduction number (R0) below 1, would require a further intensification of current efforts, even at the sub-national level. CONCLUSIONS: Active case finding programmes are effective in reducing TB in the short term. However, interruption of transmission in high-burden countries, like Vietnam and Nepal, will require comprehensive incremental efforts. Complementary measures to reduce progression from infection to disease, and reactivation of latent infection, are needed to meet the WHO End TB incidence targets.
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spelling pubmed-86042972021-11-20 The impact of active case finding on transmission dynamics of tuberculosis: A modelling study Ayabina, Diepreye Victoria Gomes, M. Gabriela M. Nguyen, Nhung Viet Vo, Luan Shreshta, Suvesh Thapa, Anil Codlin, Andrew James Mishra, Gokul Caws, Maxine PLoS One Research Article BACKGROUND: In the last decade, active case finding (ACF) strategies for tuberculosis (TB) have been implemented in many diverse settings, with some showing large increases in case detection and reporting at the sub-national level. There have also been several studies which seek to provide evidence for the benefits of ACF to individuals and communities in the broader context. However, there remains no quantification of the impact of ACF with regards to reducing the burden of transmission. We sought to address this knowledge gap and quantify the potential impact of active case finding on reducing transmission of TB at the national scale and further, to determine the intensification of intervention efforts required to bring the reproduction number (R(0)) below 1 for TB. METHODS: We adopt a dynamic transmission model that incorporates heterogeneity in risk to TB to assess the impact of an ACF programme (IMPACT TB) on reducing TB incidence in Vietnam and Nepal. We fit the models to country-level incidence data using a Bayesian Markov Chain Monte Carlo approach. We assess the impact of ACF using a parameter in our model, which we term the treatment success rate. Using programmatic data, we estimate how much this parameter has increased as a result of IMPACT TB in the implementation districts of Vietnam and Nepal and quantify additional efforts needed to eliminate transmission of TB in these countries by 2035. RESULTS: Extending the IMPACT TB programme to national coverage would lead to moderate decreases in TB incidence and would not be enough to interrupt transmission by 2035. Decreasing transmission sufficiently to bring the reproduction number (R0) below 1, would require a further intensification of current efforts, even at the sub-national level. CONCLUSIONS: Active case finding programmes are effective in reducing TB in the short term. However, interruption of transmission in high-burden countries, like Vietnam and Nepal, will require comprehensive incremental efforts. Complementary measures to reduce progression from infection to disease, and reactivation of latent infection, are needed to meet the WHO End TB incidence targets. Public Library of Science 2021-11-19 /pmc/articles/PMC8604297/ /pubmed/34797864 http://dx.doi.org/10.1371/journal.pone.0257242 Text en © 2021 Ayabina et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ayabina, Diepreye Victoria
Gomes, M. Gabriela M.
Nguyen, Nhung Viet
Vo, Luan
Shreshta, Suvesh
Thapa, Anil
Codlin, Andrew James
Mishra, Gokul
Caws, Maxine
The impact of active case finding on transmission dynamics of tuberculosis: A modelling study
title The impact of active case finding on transmission dynamics of tuberculosis: A modelling study
title_full The impact of active case finding on transmission dynamics of tuberculosis: A modelling study
title_fullStr The impact of active case finding on transmission dynamics of tuberculosis: A modelling study
title_full_unstemmed The impact of active case finding on transmission dynamics of tuberculosis: A modelling study
title_short The impact of active case finding on transmission dynamics of tuberculosis: A modelling study
title_sort impact of active case finding on transmission dynamics of tuberculosis: a modelling study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604297/
https://www.ncbi.nlm.nih.gov/pubmed/34797864
http://dx.doi.org/10.1371/journal.pone.0257242
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