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

<h4>Background</h4> 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...

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Autores principales: Diepreye Victoria Ayabina, M. Gabriela M. Gomes, Nhung Viet Nguyen, Luan Vo, Suvesh Shreshta, Anil Thapa, Andrew James Codlin, Gokul Mishra, Maxine Caws
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Publicado: Public Library of Science (PLoS) 2021
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spelling oai:doaj.org-article:aa75dfba7e21427981f90146e0bc204d2021-11-25T06:19:32ZThe impact of active case finding on transmission dynamics of tuberculosis: A modelling study1932-6203https://doaj.org/article/aa75dfba7e21427981f90146e0bc204d2021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604297/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4> 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 (R0) below 1 for TB. <h4>Methods</h4> 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. <h4>Results</h4> 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. <h4>Conclusions</h4> 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.Diepreye Victoria AyabinaM. Gabriela M. GomesNhung Viet NguyenLuan VoSuvesh ShreshtaAnil ThapaAndrew James CodlinGokul MishraMaxine CawsPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Diepreye Victoria Ayabina
M. Gabriela M. Gomes
Nhung Viet Nguyen
Luan Vo
Suvesh Shreshta
Anil Thapa
Andrew James Codlin
Gokul Mishra
Maxine Caws
The impact of active case finding on transmission dynamics of tuberculosis: A modelling study
description <h4>Background</h4> 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 (R0) below 1 for TB. <h4>Methods</h4> 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. <h4>Results</h4> 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. <h4>Conclusions</h4> 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.
format article
author Diepreye Victoria Ayabina
M. Gabriela M. Gomes
Nhung Viet Nguyen
Luan Vo
Suvesh Shreshta
Anil Thapa
Andrew James Codlin
Gokul Mishra
Maxine Caws
author_facet Diepreye Victoria Ayabina
M. Gabriela M. Gomes
Nhung Viet Nguyen
Luan Vo
Suvesh Shreshta
Anil Thapa
Andrew James Codlin
Gokul Mishra
Maxine Caws
author_sort Diepreye Victoria Ayabina
title 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_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_sort impact of active case finding on transmission dynamics of tuberculosis: a modelling study
publisher Public Library of Science (PLoS)
publishDate 2021
url https://doaj.org/article/aa75dfba7e21427981f90146e0bc204d
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