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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/39559
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| Title: | The Temporal Trends of Mortality Due to Tuberculosis in Brazil: Tracing the Coronavirus Disease 2019 (COVID-19) Pandemic’s Effect Through a Bayesian Approach and Unmasking Disparities |
| Authors: | Tavares, Reginaldo
Gomes, Dulce
Berra, Thaís Zamboni
Alves, Yan
Ramos, Antônio
Popolin, Marcela
Abade, André
Zini, Natália
Tártaro, Ariela
Alves, Josilene
Costa, Fernanda
Pelodan, Maria
Vigato, Beatriz
Pinheiro, Daniele
Paiva, Juliana
Souza, Clara
Arcêncio, Ricardo Alexandre |
| Editors: | Pando, Rogelio Hernández |
| Keywords: | Tuberculosis
COVID-19
Temporal Time Series Trends
Bayesian Structural Time Series |
| Issue Date: | 16-May-2025 |
| Publisher: | Microorganisms |
| Citation: | Tavares, R.B.V.; Gomes, D.;
Berra, T.Z.; Alves, Y.M.; Ramos, A.C.V.;
Popolin, M.A.P.; Abade, A.d.S.; Zini,
N.; Tártaro, A.F.; Alves, J.D.; et al. The
Temporal Trends of Mortality Due to
Tuberculosis in Brazil: Tracing the
Coronavirus Disease 2019 (COVID-19)
Pandemic’s Effect Through a Bayesian
Approach and Unmasking Disparities.
Microorganisms 2025, 13, 1145. https://
doi.org/10.3390/microorganisms13051145 |
| Abstract: | An ecological study of TB deaths recorded in
the Mortality Information System (SIM) from 2012 to 2022 was conducted. Trends and
percentage changes in the mortality were estimated. A Bayesian Structural Time Series
model combined with an Autoregressive Integrated Moving Average model was used
to assess the pandemic’s effect on TB. |
| URI: | https://www.mdpi.com/2076-2607/13/5/1145
http://hdl.handle.net/10174/39559 |
| Type: | article |
| Appears in Collections: | CIMA - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
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