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Optimal Resource Allocation to Reduce an Epidemic Spread and Its Complication

Department of Computer Control and Management Engineering Antonio Ruberti, Sapienza University of Rome, via Ariosto 25, 00185 Rome, Italy
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This paper is an extended version of our paper published in Proceedings of the 22nd International Conference on System Theory, Control and Computing (ICSTCC 2018), Sinaia, Romania, 10–12 October 2018.
Information 2019, 10(6), 213; https://doi.org/10.3390/info10060213
Received: 30 April 2019 / Revised: 7 June 2019 / Accepted: 11 June 2019 / Published: 13 June 2019
(This article belongs to the Special Issue ICSTCC 2018: Advances in Control and Computers)
Mathematical modeling represents a useful instrument to describe epidemic spread and to propose useful control actions, such as vaccination scheduling, quarantine, informative campaign, and therapy, especially in the realistic hypothesis of resources limitations. Moreover, the same representation could efficiently describe different epidemic scenarios, involving, for example, computer viruses spreading in the network. In this paper, a new model describing an infectious disease and a possible complication is proposed; after deep-model analysis discussing the role of the reproduction number, an optimal control problem is formulated and solved to reduce the number of dead patients, minimizing the control effort. The results show the reasonability of the proposed model and the effectiveness of the control action, aiming at an efficient resource allocation; the model also describes the different reactions of a population with respect to an epidemic disease depending on the economic and social original conditions. The optimal control theory applied to the proposed new epidemic model provides a sensible reduction in the number of dead patients, also suggesting the suitable scheduling of the vaccination control. Future work will be devoted to the identification of the model parameters referring to specific epidemic disease and complications, also taking into account the geographic and social scenario. View Full-Text
Keywords: epidemic diseases modeling; optimal control; vaccination and therapy; optimal resource allocation epidemic diseases modeling; optimal control; vaccination and therapy; optimal resource allocation
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Di Giamberardino, P.; Iacoviello, D. Optimal Resource Allocation to Reduce an Epidemic Spread and Its Complication. Information 2019, 10, 213.

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