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October 16, 2025An International Journal of Optimization and Control Theories & Applications (IJOCTA)Open Access

Data-driven optimization and parameter estimation for a metric graph epidemic model with applications to COVID-19 spread in Poland: A real-world example of optimization for a challenging Rosenbrock-type objective function

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Authors

HKHannah KravitzCDChristina DurónBNBryttani Nieves

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Overview

Data-driven optimization estimates key parameters in epidemic models, suggesting insights on COVID-19 spread in Poland.

Key Points

  • COVID-19 spread in Poland analyzed using a metric graph epidemic model, revealing patterns in case reporting.
  • Data integration from daily case reports and traffic studies led to parameter estimation using a Rosenbrock-type function.
  • Optimization strategies developed for fitting the model to epidemiological data improved understanding of disease transmission.
  • Findings indicate that reducing traffic flow may help mitigate the spread of COVID-19 in urban areas.

Cite This Study

Kravitz et al. (2025) studied this question.

synapsesocial.com/papers/68f04920e559138a1a06d8bdhttps://doi.org/10.36922/ijocta025220106
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