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

Research output: Chapter in Book/Published conference outputConference 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 languageEnglish
Title of host publicationFrom Data to Models and Back
Subtitle of host publication12th International Symposium, DataMod 2024, Aveiro, Portugal, November 4-5, 2024, Revised Selected Papers
EditorsRicardo M. Czekster, Paolo Milazzo
PublisherSpringer
Pages34-51
Number of pages18
ISBN (Print)9783031879074
DOIs
Publication statusPublished - 19 Apr 2025
Event12th International Symposium on From Data Models and Back, DataMod 2024 - Aveiro, Portugal
Duration: 4 Nov 20245 Nov 2024

Publication series

NameLecture Notes in Computer Science (LNCS)
Volume15556
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Symposium on From Data Models and Back, DataMod 2024
Country/TerritoryPortugal
CityAveiro
Period4/11/245/11/24

Keywords

  • COVID-19
  • Single-objective optimisation
  • SIR Modelling

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