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The impact of the COVID-19 pandemic and associated suppression measures on the burden of tuberculosis in India

BACKGROUND: Tuberculosis (TB) is a major cause of death globally. India carries the highest share of the global TB burden. The COVID-19 pandemic has severely impacted diagnosis of TB in India, yet there is limited data on how TB case reporting has changed since the pandemic began and which factors d...

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Autores principales: Arentz, Matthew, Ma, Jianing, Zheng, Peng, Vos, Theo, Murray, Christopher J. L., Kyu, Hmwe H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8792515/
https://www.ncbi.nlm.nih.gov/pubmed/35086472
http://dx.doi.org/10.1186/s12879-022-07078-y
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author Arentz, Matthew
Ma, Jianing
Zheng, Peng
Vos, Theo
Murray, Christopher J. L.
Kyu, Hmwe H.
author_facet Arentz, Matthew
Ma, Jianing
Zheng, Peng
Vos, Theo
Murray, Christopher J. L.
Kyu, Hmwe H.
author_sort Arentz, Matthew
collection PubMed
description BACKGROUND: Tuberculosis (TB) is a major cause of death globally. India carries the highest share of the global TB burden. The COVID-19 pandemic has severely impacted diagnosis of TB in India, yet there is limited data on how TB case reporting has changed since the pandemic began and which factors determine differences in case notification. METHODS: We utilized publicly available data on TB case reporting through the Indian Central TB Division from January 2017 through April of 2021 (prior to the first COVID-19 related lockdown). Using a Poisson model, we estimated seasonal and yearly patterns in TB case notification in India from January 2017 through February 2020 and extended this estimate as the counterfactual expected TB cases notified from March 2020 through April 2021. We characterized the differences in case notification observed and those expected in the absence of the pandemic by State and Territory. We then performed a linear regression to examine the relationship between the logit ratio of reported TB to counterfactual cases and mask use, mobility, daily hospitalizations/100,000 population, and public/total TB case reporting. RESULTS: We found 1,320,203 expected cases of TB (95% uncertainty interval (UI) 1,309,612 to 1,330,693) were not reported during the period from March 2020 through April 2021. This represents a 63.3% difference (95% UI 62.8 to 63.8) in reporting. We found that mobility data and average hospital admissions per month per population were correlated with differences in TB case notification, compared to the counterfactual in the absence of the pandemic (p > 0.001). CONCLUSION: There was a large difference between reported TB cases in India and those expected in the absence of the pandemic. This information can help inform the Indian TB program as they consider interventions to accelerate case finding and notification once the pandemic related TB service disruptions improve. Mobility data and hospital admissions are surrogate measures that correlate with a greater difference in reported/expected TB cases and may correlate with a disruption in TB diagnostic services. However, further research is needed to clarify this association and identify other key contributors to gaps in TB case notifications in India. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07078-y.
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spelling pubmed-87925152022-01-27 The impact of the COVID-19 pandemic and associated suppression measures on the burden of tuberculosis in India Arentz, Matthew Ma, Jianing Zheng, Peng Vos, Theo Murray, Christopher J. L. Kyu, Hmwe H. BMC Infect Dis Research BACKGROUND: Tuberculosis (TB) is a major cause of death globally. India carries the highest share of the global TB burden. The COVID-19 pandemic has severely impacted diagnosis of TB in India, yet there is limited data on how TB case reporting has changed since the pandemic began and which factors determine differences in case notification. METHODS: We utilized publicly available data on TB case reporting through the Indian Central TB Division from January 2017 through April of 2021 (prior to the first COVID-19 related lockdown). Using a Poisson model, we estimated seasonal and yearly patterns in TB case notification in India from January 2017 through February 2020 and extended this estimate as the counterfactual expected TB cases notified from March 2020 through April 2021. We characterized the differences in case notification observed and those expected in the absence of the pandemic by State and Territory. We then performed a linear regression to examine the relationship between the logit ratio of reported TB to counterfactual cases and mask use, mobility, daily hospitalizations/100,000 population, and public/total TB case reporting. RESULTS: We found 1,320,203 expected cases of TB (95% uncertainty interval (UI) 1,309,612 to 1,330,693) were not reported during the period from March 2020 through April 2021. This represents a 63.3% difference (95% UI 62.8 to 63.8) in reporting. We found that mobility data and average hospital admissions per month per population were correlated with differences in TB case notification, compared to the counterfactual in the absence of the pandemic (p > 0.001). CONCLUSION: There was a large difference between reported TB cases in India and those expected in the absence of the pandemic. This information can help inform the Indian TB program as they consider interventions to accelerate case finding and notification once the pandemic related TB service disruptions improve. Mobility data and hospital admissions are surrogate measures that correlate with a greater difference in reported/expected TB cases and may correlate with a disruption in TB diagnostic services. However, further research is needed to clarify this association and identify other key contributors to gaps in TB case notifications in India. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07078-y. BioMed Central 2022-01-27 /pmc/articles/PMC8792515/ /pubmed/35086472 http://dx.doi.org/10.1186/s12879-022-07078-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Arentz, Matthew
Ma, Jianing
Zheng, Peng
Vos, Theo
Murray, Christopher J. L.
Kyu, Hmwe H.
The impact of the COVID-19 pandemic and associated suppression measures on the burden of tuberculosis in India
title The impact of the COVID-19 pandemic and associated suppression measures on the burden of tuberculosis in India
title_full The impact of the COVID-19 pandemic and associated suppression measures on the burden of tuberculosis in India
title_fullStr The impact of the COVID-19 pandemic and associated suppression measures on the burden of tuberculosis in India
title_full_unstemmed The impact of the COVID-19 pandemic and associated suppression measures on the burden of tuberculosis in India
title_short The impact of the COVID-19 pandemic and associated suppression measures on the burden of tuberculosis in India
title_sort impact of the covid-19 pandemic and associated suppression measures on the burden of tuberculosis in india
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8792515/
https://www.ncbi.nlm.nih.gov/pubmed/35086472
http://dx.doi.org/10.1186/s12879-022-07078-y
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