ArticleInfectious Disease Modelling2022
Inverse problem for adaptive SIR model: Application to COVID-19 in Latin America.
Article in Infectious Disease Modelling, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Determining disease attributes from epidemic trajectories.Infectious Disease Modelling · 2026Article
- Survey on mathematical modeling of infectious disease dynamics: insights and applications.BMC infectious diseases · 2026Review
- The Role of Mathematical Modelling in Predicting and Controlling Infectious Disease Outbreaks in Underserved Settings: A Systematic Review and Meta-Analysis.Public health challenges · 2025Review
- A new hybrid prediction model of COVID-19 daily new case data.Engineering applications of artificial intelligence · 2023Article
- Novel Approach for Identification of Basic and Effective Reproduction Numbers Illustrated with COVID-19.Viruses · 2023Article
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Authors and funding
2 authors.
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Abstract
This work presents a method for solving an Adaptive Susceptible-Infected-Removed (A-SIR) epidemic model with time-dependent transmission and removal rates. Available COVID-19 data as of March 2021 are used for identifying the rates from an inverse problem. The estimated rates are used to solve the adaptive SIR system for the spread of the infectious disease. This method simultaneously solves the problem for the time-dependent rates and the unknown functions of the A-SIR system. Presented results show the spread of COVID-19 in the World, Argentina, Brazil, Colombia, Dominican Republic, and Honduras. Comparisons of the reported affected by the disease individuals from the available real data and the values obtained with the A-SIR model demonstrate how well the model simulates the dynamic of the infectious disease.
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