Corrigendum to: "Bayesian spatio-temporal modeling of severe acute respiratory syndrome in Brazil: A comparative analysis across pre-, during, and post-COVID-19 eras" [Infectious Disease Modelling, 10 (2) (2025) 466-476]

Rodrigo de Souza Bulhões^{1

2}, Jonatha Sousa Pimentel³, Paulo Canas Rodrigues^{1

4}

Affiliations

¹ Department of Statistics, IME, Federal University of Bahia, Salvador, BA, Brazil.
² Department of Statistical Methods, IM, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
³ Department of Statistics, CCEN, Federal University of Pernambuco, Recife, PE, Brazil.
⁴ Econometrics and Business Statistics, Monash University, Australia.

Published Erratum

Rodrigo de Souza Bulhões et al. Infect Dis Model. 2025.

. 2025 Dec 30;11(2):751.

doi: 10.1016/j.idm.2025.12.017. eCollection 2026 Jun.

Rodrigo de Souza Bulhões^{1

2}, Jonatha Sousa Pimentel³, Paulo Canas Rodrigues^{1

4}

¹ Department of Statistics, IME, Federal University of Bahia, Salvador, BA, Brazil.
² Department of Statistical Methods, IM, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
³ Department of Statistics, CCEN, Federal University of Pernambuco, Recife, PE, Brazil.
⁴ Econometrics and Business Statistics, Monash University, Australia.

Abstract

[This corrects the article DOI: 10.1016/j.idm.2024.12.010.].

Bayesian spatio-temporal modeling of severe acute respiratory syndrome in Brazil: A comparative analysis across pre-, during, and post-COVID-19 eras.
Souza Bulhões R, Pimentel JS, Rodrigues PC. Souza Bulhões R, et al. Infect Dis Model. 2024 Dec 19;10(2):466-476. doi: 10.1016/j.idm.2024.12.010. eCollection 2025 Jun. Infect Dis Model. 2024. PMID: 39834649 Free PMC article.

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1. World Health Organization . World Health Organization; 2020. Severe acute respiratory syndrome (SARS) [Internet]https://www.who.int/health-topics/severe-acute-respiratory-syndrome#tab&...