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Modeling the impact of COVID-19 on future tuberculosis burden
BACKGROUND: The ongoing COVID-19 pandemic has greatly disrupted our everyday life, forcing the adoption of non-pharmaceutical interventions in many countries and putting public health services and healthcare systems worldwide under stress. These circumstances are leading to unintended effects such a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243113/ https://www.ncbi.nlm.nih.gov/pubmed/35784445 http://dx.doi.org/10.1038/s43856-022-00145-0 |
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author | Tovar, Mario Aleta, Alberto Sanz, Joaquín Moreno, Yamir |
author_facet | Tovar, Mario Aleta, Alberto Sanz, Joaquín Moreno, Yamir |
author_sort | Tovar, Mario |
collection | PubMed |
description | BACKGROUND: The ongoing COVID-19 pandemic has greatly disrupted our everyday life, forcing the adoption of non-pharmaceutical interventions in many countries and putting public health services and healthcare systems worldwide under stress. These circumstances are leading to unintended effects such as the increase in the burden of other diseases. METHODS: Here, using a data-driven epidemiological model for tuberculosis (TB) spreading, we describe the expected rise in TB incidence and mortality if COVID-associated changes in TB notification are sustained and attributable entirely to disrupted diagnosis and treatment adherence. RESULTS: Our calculations show that the reduction in diagnosis of new TB cases due to the COVID-19 pandemic could result in 228k (CI 187–276) excess deaths in India, 111k (CI 93–134) in Indonesia, 27k (CI 21–33) in Pakistan, and 12k (CI 9–18) in Kenya. CONCLUSIONS: We show that it is possible to reverse these excess deaths by increasing the pre-covid diagnosis capabilities from 15 to 50% for 2 to 4 years. This would prevent almost all TB-related excess mortality that could be caused by the COVID-19 pandemic if no additional preventative measures are introduced. Our work therefore provides guidelines for mitigating the impact of COVID-19 on tuberculosis epidemic in the years to come. |
format | Online Article Text |
id | pubmed-9243113 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92431132022-06-30 Modeling the impact of COVID-19 on future tuberculosis burden Tovar, Mario Aleta, Alberto Sanz, Joaquín Moreno, Yamir Commun Med (Lond) Article BACKGROUND: The ongoing COVID-19 pandemic has greatly disrupted our everyday life, forcing the adoption of non-pharmaceutical interventions in many countries and putting public health services and healthcare systems worldwide under stress. These circumstances are leading to unintended effects such as the increase in the burden of other diseases. METHODS: Here, using a data-driven epidemiological model for tuberculosis (TB) spreading, we describe the expected rise in TB incidence and mortality if COVID-associated changes in TB notification are sustained and attributable entirely to disrupted diagnosis and treatment adherence. RESULTS: Our calculations show that the reduction in diagnosis of new TB cases due to the COVID-19 pandemic could result in 228k (CI 187–276) excess deaths in India, 111k (CI 93–134) in Indonesia, 27k (CI 21–33) in Pakistan, and 12k (CI 9–18) in Kenya. CONCLUSIONS: We show that it is possible to reverse these excess deaths by increasing the pre-covid diagnosis capabilities from 15 to 50% for 2 to 4 years. This would prevent almost all TB-related excess mortality that could be caused by the COVID-19 pandemic if no additional preventative measures are introduced. Our work therefore provides guidelines for mitigating the impact of COVID-19 on tuberculosis epidemic in the years to come. Nature Publishing Group UK 2022-06-29 /pmc/articles/PMC9243113/ /pubmed/35784445 http://dx.doi.org/10.1038/s43856-022-00145-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Tovar, Mario Aleta, Alberto Sanz, Joaquín Moreno, Yamir Modeling the impact of COVID-19 on future tuberculosis burden |
title | Modeling the impact of COVID-19 on future tuberculosis burden |
title_full | Modeling the impact of COVID-19 on future tuberculosis burden |
title_fullStr | Modeling the impact of COVID-19 on future tuberculosis burden |
title_full_unstemmed | Modeling the impact of COVID-19 on future tuberculosis burden |
title_short | Modeling the impact of COVID-19 on future tuberculosis burden |
title_sort | modeling the impact of covid-19 on future tuberculosis burden |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243113/ https://www.ncbi.nlm.nih.gov/pubmed/35784445 http://dx.doi.org/10.1038/s43856-022-00145-0 |
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