Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study

• Autor(a) principal: Zamboni Berra, Thaís
• Data de Publicação: 2022
• Outros Autores: Ramos, Antônio, Alves, Yan, Tavares, Reginaldo, Fehr Tartaro, Ariela, Nascimento, Murilo, Moura, Heriederson, Delpino, Filipe, Soares, Débora, Silva, Ruan, Gomes, Dulce, Monroe, Aline, Arcêncio, Ricardo Alexandre
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10174/32618; https://doi.org/Berra, T.Z.; Ramos, A.C.V.; Alves, Y.M.; Tavares, R.B.V.; Tartaro, A.F.; Nascimento, M.C.d.; Moura, H.S.D.; Delpino, F.M.; de Almeida Soares, D.; Silva, R.V.d.S.; et al. Impact of COVID-19 on Tuberculosis Indicators in Brazil: A Time Series and Spatial Analysis Study. Trop. Med. Infect. Dis. 2022, 7, 247. https://doi.org/10.3390/ tropicalmed7090247; https://doi.org/10.3390/ tropicalmed7090247
• topic: Tuberculosis; COVID-19; Time Series Analysis; Spatial Analysis

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 prepandemic 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.