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COVID-19-related healthcare impacts: an uncontrolled, segmented time-series analysis of tuberculosis diagnosis services in Mozambique, 2017–2020

INTRODUCTION: Currently, COVID-19 dominates the public health agenda and poses a permanent threat, leading to health systems’ exhaustion and unprecedented service disruption. Primary healthcare services, including tuberculosis services, are at increased risk of facing severe disruptions, particularl...

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Autores principales: Manhiça, Ivan, Augusto, Orvalho, Sherr, Kenneth, Cowan, James, Cuco, Rosa Marlene, Agostinho, Sãozinha, Macuacua, Bachir C., Ramiro, Isaías, Carimo, Naziat, Matsinhe, Maria Benigna, Gloyd, Stephen, Chicumbe, Sergio, Machava, Raimundo, Tembe, Stélio, Fernandes, Quinhas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021460/
https://www.ncbi.nlm.nih.gov/pubmed/35443938
http://dx.doi.org/10.1136/bmjgh-2021-007878
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author Manhiça, Ivan
Augusto, Orvalho
Sherr, Kenneth
Cowan, James
Cuco, Rosa Marlene
Agostinho, Sãozinha
Macuacua, Bachir C.
Ramiro, Isaías
Carimo, Naziat
Matsinhe, Maria Benigna
Gloyd, Stephen
Chicumbe, Sergio
Machava, Raimundo
Tembe, Stélio
Fernandes, Quinhas
author_facet Manhiça, Ivan
Augusto, Orvalho
Sherr, Kenneth
Cowan, James
Cuco, Rosa Marlene
Agostinho, Sãozinha
Macuacua, Bachir C.
Ramiro, Isaías
Carimo, Naziat
Matsinhe, Maria Benigna
Gloyd, Stephen
Chicumbe, Sergio
Machava, Raimundo
Tembe, Stélio
Fernandes, Quinhas
author_sort Manhiça, Ivan
collection PubMed
description INTRODUCTION: Currently, COVID-19 dominates the public health agenda and poses a permanent threat, leading to health systems’ exhaustion and unprecedented service disruption. Primary healthcare services, including tuberculosis services, are at increased risk of facing severe disruptions, particularly in low-income and middle-income countries. Indeed, corroborating model-based forecasts, there is increasing evidence of the COVID-19 pandemic’s negative impact on tuberculosis case detection. METHODS: Applying a segmented time-series analysis, we assessed the effects of COVID-19-related measures on tuberculosis diagnosis service across districts in Mozambique. Ministry health information system data were used from the first quarter of 2017 to the end of 2020. The model, performed under the Bayesian premises, was estimated as a negative binomial with random effects for districts and provinces. RESULTS: A total of 154 districts were followed for 16 consecutive quarters. Together, these districts reported 96 182 cases of all forms of tuberculosis in 2020. At baseline (first quarter of 2017), Mozambique had an estimated incidence rate of 283 (95% CI 200 to 406) tuberculosis cases per 100 000 people and this increased at a 5% annual rate through the end of 2019. We estimated that 17 147 new tuberculosis cases were potentially missed 9 months after COVID-19 onset, resulting in a 15.1% (95% CI 5.9 to 24.0) relative loss in 2020. The greatest impact was observed in the southern region at 40.0% (95% CI 30.1 to 49.0) and among men at 15% (95% CI 4.0 to 25.0). The incidence of pulmonary tuberculosis increased at an average rate of 6.6% annually; however, an abrupt drop (15%) was also observed immediately after COVID-19 onset in March 2020. CONCLUSION: The most significant impact of the state of emergency was observed between April and June 2020, the quarter after COVID-19 onset. Encouragingly, by the end of 2020, clear signs of health system recovery were visible despite the initial shock.
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spelling pubmed-90214602022-04-22 COVID-19-related healthcare impacts: an uncontrolled, segmented time-series analysis of tuberculosis diagnosis services in Mozambique, 2017–2020 Manhiça, Ivan Augusto, Orvalho Sherr, Kenneth Cowan, James Cuco, Rosa Marlene Agostinho, Sãozinha Macuacua, Bachir C. Ramiro, Isaías Carimo, Naziat Matsinhe, Maria Benigna Gloyd, Stephen Chicumbe, Sergio Machava, Raimundo Tembe, Stélio Fernandes, Quinhas BMJ Glob Health Original Research INTRODUCTION: Currently, COVID-19 dominates the public health agenda and poses a permanent threat, leading to health systems’ exhaustion and unprecedented service disruption. Primary healthcare services, including tuberculosis services, are at increased risk of facing severe disruptions, particularly in low-income and middle-income countries. Indeed, corroborating model-based forecasts, there is increasing evidence of the COVID-19 pandemic’s negative impact on tuberculosis case detection. METHODS: Applying a segmented time-series analysis, we assessed the effects of COVID-19-related measures on tuberculosis diagnosis service across districts in Mozambique. Ministry health information system data were used from the first quarter of 2017 to the end of 2020. The model, performed under the Bayesian premises, was estimated as a negative binomial with random effects for districts and provinces. RESULTS: A total of 154 districts were followed for 16 consecutive quarters. Together, these districts reported 96 182 cases of all forms of tuberculosis in 2020. At baseline (first quarter of 2017), Mozambique had an estimated incidence rate of 283 (95% CI 200 to 406) tuberculosis cases per 100 000 people and this increased at a 5% annual rate through the end of 2019. We estimated that 17 147 new tuberculosis cases were potentially missed 9 months after COVID-19 onset, resulting in a 15.1% (95% CI 5.9 to 24.0) relative loss in 2020. The greatest impact was observed in the southern region at 40.0% (95% CI 30.1 to 49.0) and among men at 15% (95% CI 4.0 to 25.0). The incidence of pulmonary tuberculosis increased at an average rate of 6.6% annually; however, an abrupt drop (15%) was also observed immediately after COVID-19 onset in March 2020. CONCLUSION: The most significant impact of the state of emergency was observed between April and June 2020, the quarter after COVID-19 onset. Encouragingly, by the end of 2020, clear signs of health system recovery were visible despite the initial shock. BMJ Publishing Group 2022-04-19 /pmc/articles/PMC9021460/ /pubmed/35443938 http://dx.doi.org/10.1136/bmjgh-2021-007878 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Manhiça, Ivan
Augusto, Orvalho
Sherr, Kenneth
Cowan, James
Cuco, Rosa Marlene
Agostinho, Sãozinha
Macuacua, Bachir C.
Ramiro, Isaías
Carimo, Naziat
Matsinhe, Maria Benigna
Gloyd, Stephen
Chicumbe, Sergio
Machava, Raimundo
Tembe, Stélio
Fernandes, Quinhas
COVID-19-related healthcare impacts: an uncontrolled, segmented time-series analysis of tuberculosis diagnosis services in Mozambique, 2017–2020
title COVID-19-related healthcare impacts: an uncontrolled, segmented time-series analysis of tuberculosis diagnosis services in Mozambique, 2017–2020
title_full COVID-19-related healthcare impacts: an uncontrolled, segmented time-series analysis of tuberculosis diagnosis services in Mozambique, 2017–2020
title_fullStr COVID-19-related healthcare impacts: an uncontrolled, segmented time-series analysis of tuberculosis diagnosis services in Mozambique, 2017–2020
title_full_unstemmed COVID-19-related healthcare impacts: an uncontrolled, segmented time-series analysis of tuberculosis diagnosis services in Mozambique, 2017–2020
title_short COVID-19-related healthcare impacts: an uncontrolled, segmented time-series analysis of tuberculosis diagnosis services in Mozambique, 2017–2020
title_sort covid-19-related healthcare impacts: an uncontrolled, segmented time-series analysis of tuberculosis diagnosis services in mozambique, 2017–2020
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021460/
https://www.ncbi.nlm.nih.gov/pubmed/35443938
http://dx.doi.org/10.1136/bmjgh-2021-007878
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