Bayesian spatio-temporal modeling of severe acute respiratory syndrome in Brazil: A comparative analysis across pre-, during, and post-COVID-19 eras.
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| Title: | Bayesian spatio-temporal modeling of severe acute respiratory syndrome in Brazil: A comparative analysis across pre-, during, and post-COVID-19 eras. |
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| Authors: | Souza Bulhões R; Department of Statistics, IME, Federal University of Bahia, Salvador, BA, Brazil.; Department of Statistical Methods, IM, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil., Pimentel JS; Department of Statistics, CCEN, Federal University of Pernambuco, Recife, PE, Brazil., Rodrigues PC; Department of Statistics, IME, Federal University of Bahia, Salvador, BA, Brazil.; Econometrics and Business Statistics, Monash University, Australia. |
| Source: | Infectious Disease Modelling [Infect Dis Model] 2024 Dec 19; Vol. 10 (2), pp. 466-476. Date of Electronic Publication: 2024 Dec 19 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: KeAi Communications Co., Ltd Country of Publication: China NLM ID: 101692406 Publication Model: eCollection Cited Medium: Internet ISSN: 2468-0427 (Electronic) Linking ISSN: 24680427 NLM ISO Abbreviation: Infect Dis Model Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2468-0427 |
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| DOI: | 10.1016/j.idm.2024.12.010 |
