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Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study
Background: We aimed to visualize and classify the time series of COVID-19, tuberculosis (TB) notification, and TB outcomes (cure, treatment abandonment, and death), verify the impact of the new coronavirus pandemic on these indices in Brazil, and verify the presence of spatial autocorrelation betwe...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9500936/ https://www.ncbi.nlm.nih.gov/pubmed/36136658 http://dx.doi.org/10.3390/tropicalmed7090247 |
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author | Berra, Thaís Zamboni Ramos, Antônio Carlos Vieira Alves, Yan Mathias Tavares, Reginaldo Bazon Vaz Tartaro, Ariela Fehr do Nascimento, Murilo César Moura, Heriederson Sávio Dias Delpino, Felipe Mendes de Almeida Soares, Débora Silva, Ruan Víctor dos Santos Gomes, Dulce Monroe, Aline Aparecida Arcêncio, Ricardo Alexandre |
author_facet | Berra, Thaís Zamboni Ramos, Antônio Carlos Vieira Alves, Yan Mathias Tavares, Reginaldo Bazon Vaz Tartaro, Ariela Fehr do Nascimento, Murilo César Moura, Heriederson Sávio Dias Delpino, Felipe Mendes de Almeida Soares, Débora Silva, Ruan Víctor dos Santos Gomes, Dulce Monroe, Aline Aparecida Arcêncio, Ricardo Alexandre |
author_sort | Berra, Thaís Zamboni |
collection | PubMed |
description | Background: We aimed to visualize and classify the time series of COVID-19, tuberculosis (TB) notification, and TB outcomes (cure, treatment abandonment, and death), verify the impact of the new coronavirus pandemic on these indices in Brazil, and verify the presence of spatial autocorrelation between COVID-19 and TB. Methods: This was an ecological time series study that considered TB and COVID-19 cases. Seasonal Trend Decomposition using Loess (STL) was used to trace the temporal trend, Prais–Winsten was used to classify the temporal trend, Interrupted Time Series (ITS) was used to verify the impact of COVID-19 on TB rates, and the Bivariate Moran Index (Global and Local) was used to verify the spatial autocorrelation of events. Results: Brazil and its macro-regions showed an increasing temporal trend for the notification of TB in the pre-pandemic period. Only the Northeast Region showed a decreasing temporal trend for cured cases. For treatment abandonment, all regions except for the Northeast showed an increasing temporal trend, and regarding death, Brazil and the Northeast Region showed an increasing temporal trend. With the ITS, COVID-19 caused a decline in TB notification rates and TB outcome rates. With the global spatial analysis, it was possible to identify the existence of spatial autocorrelation between the notification rate of COVID-19 and the TB notification rate and deaths. With the local analysis, it was possible to map the Brazilian municipalities and classify them according to the relationship between the rates of both diseases and space. Conclusions: COVID-19 influenced the follow-up of and adherence to TB treatment and intensified social vulnerability and, consequently, affected the notification of TB since the relationship between the disease and social determinants of health is already known. The restoration and strengthening of essential services for the prevention and detection of cases and treatment of TB in endemic environments such as Brazil have been oriented as a priority in the global health agenda. |
format | Online Article Text |
id | pubmed-9500936 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95009362022-09-24 Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study Berra, Thaís Zamboni Ramos, Antônio Carlos Vieira Alves, Yan Mathias Tavares, Reginaldo Bazon Vaz Tartaro, Ariela Fehr do Nascimento, Murilo César Moura, Heriederson Sávio Dias Delpino, Felipe Mendes de Almeida Soares, Débora Silva, Ruan Víctor dos Santos Gomes, Dulce Monroe, Aline Aparecida Arcêncio, Ricardo Alexandre Trop Med Infect Dis Article Background: We aimed to visualize and classify the time series of COVID-19, tuberculosis (TB) notification, and TB outcomes (cure, treatment abandonment, and death), verify the impact of the new coronavirus pandemic on these indices in Brazil, and verify the presence of spatial autocorrelation between COVID-19 and TB. Methods: This was an ecological time series study that considered TB and COVID-19 cases. Seasonal Trend Decomposition using Loess (STL) was used to trace the temporal trend, Prais–Winsten was used to classify the temporal trend, Interrupted Time Series (ITS) was used to verify the impact of COVID-19 on TB rates, and the Bivariate Moran Index (Global and Local) was used to verify the spatial autocorrelation of events. Results: Brazil and its macro-regions showed an increasing temporal trend for the notification of TB in the pre-pandemic period. Only the Northeast Region showed a decreasing temporal trend for cured cases. For treatment abandonment, all regions except for the Northeast showed an increasing temporal trend, and regarding death, Brazil and the Northeast Region showed an increasing temporal trend. With the ITS, COVID-19 caused a decline in TB notification rates and TB outcome rates. With the global spatial analysis, it was possible to identify the existence of spatial autocorrelation between the notification rate of COVID-19 and the TB notification rate and deaths. With the local analysis, it was possible to map the Brazilian municipalities and classify them according to the relationship between the rates of both diseases and space. Conclusions: COVID-19 influenced the follow-up of and adherence to TB treatment and intensified social vulnerability and, consequently, affected the notification of TB since the relationship between the disease and social determinants of health is already known. The restoration and strengthening of essential services for the prevention and detection of cases and treatment of TB in endemic environments such as Brazil have been oriented as a priority in the global health agenda. MDPI 2022-09-14 /pmc/articles/PMC9500936/ /pubmed/36136658 http://dx.doi.org/10.3390/tropicalmed7090247 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Berra, Thaís Zamboni Ramos, Antônio Carlos Vieira Alves, Yan Mathias Tavares, Reginaldo Bazon Vaz Tartaro, Ariela Fehr do Nascimento, Murilo César Moura, Heriederson Sávio Dias Delpino, Felipe Mendes de Almeida Soares, Débora Silva, Ruan Víctor dos Santos Gomes, Dulce Monroe, Aline Aparecida Arcêncio, Ricardo Alexandre Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study |
title | Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study |
title_full | Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study |
title_fullStr | Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study |
title_full_unstemmed | Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study |
title_short | Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study |
title_sort | impact of covid-19 on tuberculosis indicators in brazil: a time series and spatial analysis study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9500936/ https://www.ncbi.nlm.nih.gov/pubmed/36136658 http://dx.doi.org/10.3390/tropicalmed7090247 |
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