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Authors: Martina Brunetti ; Paolo Di Giamberardino ; Daniela Iacoviello and Marialourdes Ingrosso

Affiliation: Department of Computer Control and Management Engineering Antonio Ruberi, Sapienza University of Rome, Rome, Italy

Keyword(s): Modelling, Breast Cancer, Containment Strategies, Optimal Control.

Abstract: The breast cancer represents one of the most frequent disease diagnosed worldwide; with the modern improvements in medicine and technology a fast detection of tumor could allow a total recovery. In this paper, it is proposed a compartmental epidemiological model in which the female population is partitioned depending on the condition with respect to the tumor diagnosis. The model is identified referring to the population of a region of Italy, using real data; increasing levels of control are introduced, from noninvasive prevention to combination of surgery and chemotherapy. In the framework of optimal control, aiming at reducing the number of severe cases and of women dead by tumor, a suitable combination of control effort is determined, considering constraints in the containment measures. Numerical results stress the importance of prevention that at the very beginning increases the number of discovered positive diagnosis, and, successively, significantly contains the fatal consequen ces of breast cancer on the population by reducing the late diagnosis. (More)

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Paper citation in several formats:
Brunetti, M.; Di Giamberardino, P.; Iacoviello, D. and Ingrosso, M. (2023). Breast Cancer Epidemic Model and Optimal Control. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO; ISBN 978-989-758-670-5; ISSN 2184-2809, SciTePress, pages 195-202. DOI: 10.5220/0012232000003543

@conference{icinco23,
author={Martina Brunetti. and Paolo {Di Giamberardino}. and Daniela Iacoviello. and Marialourdes Ingrosso.},
title={Breast Cancer Epidemic Model and Optimal Control},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO},
year={2023},
pages={195-202},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012232000003543},
isbn={978-989-758-670-5},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO
TI - Breast Cancer Epidemic Model and Optimal Control
SN - 978-989-758-670-5
IS - 2184-2809
AU - Brunetti, M.
AU - Di Giamberardino, P.
AU - Iacoviello, D.
AU - Ingrosso, M.
PY - 2023
SP - 195
EP - 202
DO - 10.5220/0012232000003543
PB - SciTePress

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