Modelling COVID-19 with a SIR Variant Using Real-World Data: A Case Study in Brazil

Daniel Leto; Elizabeth Wanner; Roberto Alamino; Thais Webber

doi:10.1007/978-3-031-87908-1_3

Modelling COVID-19 with a SIR Variant Using Real-World Data: A Case Study in Brazil

Daniel Leto^*, Elizabeth Wanner, Roberto Alamino, Thais Webber

^*Corresponding author for this work

Centro Federal de Educação Tecnológica de Minas Gerais

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

This study utilises a SIR model variant to analyse the dynamics of COVID-19 transmission in Brazil. The model incorporates compartments for different population states and optimises infection and loss of immunity rates to achieve a closer fit to real-world data, improving the characterisation of diseases’ behaviours and informing public health strategies. Data from the Our World in Data portal, including information on vaccines, variants’ dominance, and new developed cases, is used to calibrate the model by minimising the quadratic error between its projections and actual case numbers. Key parameters include infection rates, loss of immunity, vaccination, and the duration of infection and exposure. The study addresses mathematical challenges and discusses non-mathematical variables that influence outcomes. The goal is to explain infection dynamics in Brazil over time by determining infection and loss of immunity rates through simulations, considering various scenarios, including the impact of vaccination.

Original language	English
Title of host publication	From Data to Models and Back
Subtitle of host publication	12th International Symposium, DataMod 2024, Aveiro, Portugal, November 4-5, 2024, Revised Selected Papers
Editors	Ricardo M. Czekster, Paolo Milazzo
Publisher	Springer
Pages	34-51
Number of pages	18
ISBN (Print)	9783031879074
DOIs	https://doi.org/10.1007/978-3-031-87908-1_3
Publication status	Published - 19 Apr 2025
Event	12th International Symposium on From Data Models and Back, DataMod 2024 - Aveiro, Portugal Duration: 4 Nov 2024 → 5 Nov 2024

Publication series

Name	Lecture Notes in Computer Science (LNCS)
Volume	15556
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Symposium on From Data Models and Back, DataMod 2024
Country/Territory	Portugal
City	Aveiro
Period	4/11/24 → 5/11/24

Bibliographical note

Copyright © 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG.
This is an accepted manuscript of a Proceedings paper published in:
Leto, D., Wanner, E., Alamino, R., Webber, T. (2025). Modelling COVID-19 with a SIR Variant Using Real-World Data: A Case Study in Brazil. In: Czekster, R.M., Milazzo, P. (eds) From Data to Models and Back. DataMod 2024. Lecture Notes in Computer Science, vol 15556. Springer, Cham. https://doi.org/10.1007/978-3-031-87908-1_3

Keywords

COVID-19
Single-objective optimisation
SIR Modelling

Access to Document

10.1007/978-3-031-87908-1_3

Cite this

Leto, D., Wanner, E., Alamino, R., & Webber, T. (2025). Modelling COVID-19 with a SIR Variant Using Real-World Data: A Case Study in Brazil. In R. M. Czekster, & P. Milazzo (Eds.), From Data to Models and Back: 12th International Symposium, DataMod 2024, Aveiro, Portugal, November 4-5, 2024, Revised Selected Papers (pp. 34-51). (Lecture Notes in Computer Science (LNCS); Vol. 15556). Springer. https://doi.org/10.1007/978-3-031-87908-1_3

Leto, Daniel ; Wanner, Elizabeth ; Alamino, Roberto et al. / Modelling COVID-19 with a SIR Variant Using Real-World Data: A Case Study in Brazil. From Data to Models and Back: 12th International Symposium, DataMod 2024, Aveiro, Portugal, November 4-5, 2024, Revised Selected Papers. editor / Ricardo M. Czekster ; Paolo Milazzo. Springer, 2025. pp. 34-51 (Lecture Notes in Computer Science (LNCS)).

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Leto, D, Wanner, E , Alamino, R & Webber, T 2025, Modelling COVID-19 with a SIR Variant Using Real-World Data: A Case Study in Brazil. in RM Czekster & P Milazzo (eds), From Data to Models and Back: 12th International Symposium, DataMod 2024, Aveiro, Portugal, November 4-5, 2024, Revised Selected Papers. Lecture Notes in Computer Science (LNCS), vol. 15556, Springer, pp. 34-51, 12th International Symposium on From Data Models and Back, DataMod 2024, Aveiro, Portugal, 4/11/24. https://doi.org/10.1007/978-3-031-87908-1_3

Modelling COVID-19 with a SIR Variant Using Real-World Data: A Case Study in Brazil. / Leto, Daniel; Wanner, Elizabeth ; Alamino, Roberto et al.
From Data to Models and Back: 12th International Symposium, DataMod 2024, Aveiro, Portugal, November 4-5, 2024, Revised Selected Papers. ed. / Ricardo M. Czekster; Paolo Milazzo. Springer, 2025. p. 34-51 (Lecture Notes in Computer Science (LNCS); Vol. 15556).

Research output: Chapter in Book/Published conference output › Conference publication

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Leto D, Wanner E , Alamino R , Webber T. Modelling COVID-19 with a SIR Variant Using Real-World Data: A Case Study in Brazil. In Czekster RM, Milazzo P, editors, From Data to Models and Back: 12th International Symposium, DataMod 2024, Aveiro, Portugal, November 4-5, 2024, Revised Selected Papers. Springer. 2025. p. 34-51. (Lecture Notes in Computer Science (LNCS)). doi: 10.1007/978-3-031-87908-1_3