Cargando…

The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis

BACKGROUND: Routine services for tuberculosis (TB) are being disrupted by stringent lockdowns against the novel SARS-CoV-2 virus. We sought to estimate the potential long-term epidemiological impact of such disruptions on TB burden in high-burden countries, and how this negative impact could be miti...

Descripción completa

Detalles Bibliográficos
Autores principales: Cilloni, Lucia, Fu, Han, Vesga, Juan F, Dowdy, David, Pretorius, Carel, Ahmedov, Sevim, Nair, Sreenivas A., Mosneaga, Andrei, Masini, Enos, Sahu, Suvanand, Arinaminpathy, Nimalan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584493/
https://www.ncbi.nlm.nih.gov/pubmed/33134905
http://dx.doi.org/10.1016/j.eclinm.2020.100603
_version_ 1783599603825770496
author Cilloni, Lucia
Fu, Han
Vesga, Juan F
Dowdy, David
Pretorius, Carel
Ahmedov, Sevim
Nair, Sreenivas A.
Mosneaga, Andrei
Masini, Enos
Sahu, Suvanand
Arinaminpathy, Nimalan
author_facet Cilloni, Lucia
Fu, Han
Vesga, Juan F
Dowdy, David
Pretorius, Carel
Ahmedov, Sevim
Nair, Sreenivas A.
Mosneaga, Andrei
Masini, Enos
Sahu, Suvanand
Arinaminpathy, Nimalan
author_sort Cilloni, Lucia
collection PubMed
description BACKGROUND: Routine services for tuberculosis (TB) are being disrupted by stringent lockdowns against the novel SARS-CoV-2 virus. We sought to estimate the potential long-term epidemiological impact of such disruptions on TB burden in high-burden countries, and how this negative impact could be mitigated. METHODS: We adapted mathematical models of TB transmission in three high-burden countries (India, Kenya and Ukraine) to incorporate lockdown-associated disruptions in the TB care cascade. The anticipated level of disruption reflected consensus from a rapid expert consultation. We modelled the impact of these disruptions on TB incidence and mortality over the next five years, and also considered potential interventions to curtail this impact. FINDINGS: Even temporary disruptions can cause long-term increases in TB incidence and mortality. If lockdown-related disruptions cause a temporary 50% reduction in TB transmission, we estimated that a 3-month suspension of TB services, followed by 10 months to restore to normal, would cause, over the next 5 years, an additional 1⋅19 million TB cases (Crl 1⋅06–1⋅33) and 361,000 TB deaths (CrI 333–394 thousand) in India, 24,700 (16,100–44,700) TB cases and 12,500 deaths (8.8–17.8 thousand) in Kenya, and 4,350 (826–6,540) cases and 1,340 deaths (815–1,980) in Ukraine. The principal driver of these adverse impacts is the accumulation of undetected TB during a lockdown. We demonstrate how long term increases in TB burden could be averted in the short term through supplementary “catch-up” TB case detection and treatment, once restrictions are eased. INTERPRETATION: Lockdown-related disruptions can cause long-lasting increases in TB burden, but these negative effects can be mitigated with rapid restoration of TB services, and targeted interventions that are implemented as soon as restrictions are lifted. FUNDING: USAID and Stop TB Partnership
format Online
Article
Text
id pubmed-7584493
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-75844932020-10-26 The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis Cilloni, Lucia Fu, Han Vesga, Juan F Dowdy, David Pretorius, Carel Ahmedov, Sevim Nair, Sreenivas A. Mosneaga, Andrei Masini, Enos Sahu, Suvanand Arinaminpathy, Nimalan EClinicalMedicine Research Paper BACKGROUND: Routine services for tuberculosis (TB) are being disrupted by stringent lockdowns against the novel SARS-CoV-2 virus. We sought to estimate the potential long-term epidemiological impact of such disruptions on TB burden in high-burden countries, and how this negative impact could be mitigated. METHODS: We adapted mathematical models of TB transmission in three high-burden countries (India, Kenya and Ukraine) to incorporate lockdown-associated disruptions in the TB care cascade. The anticipated level of disruption reflected consensus from a rapid expert consultation. We modelled the impact of these disruptions on TB incidence and mortality over the next five years, and also considered potential interventions to curtail this impact. FINDINGS: Even temporary disruptions can cause long-term increases in TB incidence and mortality. If lockdown-related disruptions cause a temporary 50% reduction in TB transmission, we estimated that a 3-month suspension of TB services, followed by 10 months to restore to normal, would cause, over the next 5 years, an additional 1⋅19 million TB cases (Crl 1⋅06–1⋅33) and 361,000 TB deaths (CrI 333–394 thousand) in India, 24,700 (16,100–44,700) TB cases and 12,500 deaths (8.8–17.8 thousand) in Kenya, and 4,350 (826–6,540) cases and 1,340 deaths (815–1,980) in Ukraine. The principal driver of these adverse impacts is the accumulation of undetected TB during a lockdown. We demonstrate how long term increases in TB burden could be averted in the short term through supplementary “catch-up” TB case detection and treatment, once restrictions are eased. INTERPRETATION: Lockdown-related disruptions can cause long-lasting increases in TB burden, but these negative effects can be mitigated with rapid restoration of TB services, and targeted interventions that are implemented as soon as restrictions are lifted. FUNDING: USAID and Stop TB Partnership Elsevier 2020-10-24 /pmc/articles/PMC7584493/ /pubmed/33134905 http://dx.doi.org/10.1016/j.eclinm.2020.100603 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Paper
Cilloni, Lucia
Fu, Han
Vesga, Juan F
Dowdy, David
Pretorius, Carel
Ahmedov, Sevim
Nair, Sreenivas A.
Mosneaga, Andrei
Masini, Enos
Sahu, Suvanand
Arinaminpathy, Nimalan
The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis
title The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis
title_full The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis
title_fullStr The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis
title_full_unstemmed The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis
title_short The potential impact of the COVID-19 pandemic on the tuberculosis epidemic a modelling analysis
title_sort potential impact of the covid-19 pandemic on the tuberculosis epidemic a modelling analysis
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584493/
https://www.ncbi.nlm.nih.gov/pubmed/33134905
http://dx.doi.org/10.1016/j.eclinm.2020.100603
work_keys_str_mv AT cillonilucia thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT fuhan thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT vesgajuanf thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT dowdydavid thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT pretoriuscarel thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT ahmedovsevim thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT nairsreenivasa thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT mosneagaandrei thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT masinienos thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT sahusuvanand thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT arinaminpathynimalan thepotentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT cillonilucia potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT fuhan potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT vesgajuanf potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT dowdydavid potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT pretoriuscarel potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT ahmedovsevim potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT nairsreenivasa potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT mosneagaandrei potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT masinienos potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT sahusuvanand potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis
AT arinaminpathynimalan potentialimpactofthecovid19pandemiconthetuberculosisepidemicamodellinganalysis