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DESCRIPTION:IEEE SMC Italian Chapter Virtual Lecture Series on\n\n“Smart\
 , PErvasive and Mobile Systems Engineering”\n\nLecture Title “Optimal 
 control strategies to mitigate the COVID-19 outbreak in a multi-region sce
 nario”\n\nUniversity of Calabria\n\nOn-line\n\nFebruary 26\, 2021\n\n12.
 00-13.00 CET\n\nby\n\nProf. Mariagrazia Dotoli\n\nPolitecnico di Bari\, It
 aly\n\nAbstract:\n\nIn this talk\, after revising the main models used in 
 the related literature for analyzing the dynamics of infectious diseases\,
  we present a novel time-varying epidemiological model for COVID-19. The m
 odel belongs to the class of SIRCQTHE models (i.e.\, considering Susceptib
 le\, Infected\, Removed\, Contagious\, Quarantined\, Threatened\, Healed\,
  and Extinct categories of individuals) and allows to get reliable predict
 ions on the pandemic’s dynamics on a regional basis. We present an innov
 ative stochastic non-linear control approach that supports the decision or
  policy makers in determining robust optimal strategies to tackle the COVI
 D-19 secondary waves. More precisely\, based on the presented SIRCQTHE mod
 el\, a stochastic model predictive control problem is defined that allows 
 policy makers to select the control actions that minimize the pandemic’s
  socio-economic costs\, i.e.\, various types of people’s mobility restri
 ctions (for example\, closure of shops and restaurants\, closure of region
 al/municipality borders). In addition\, considering the unavoidable uncert
 ainty characterizing the model’s parameters that strongly affect the dec
 ision-making process\, we impose that the capacity of the network of regio
 nal healthcare systems is not violated\, in accordance with a chance const
 raint approach. The effectiveness of the presented modeling and control te
 chnique in supporting the definition of diversified regional strategies fo
 r tackling the COVID-19 spread is effectively tested on the network of Ita
 lian regions using real data from the Italian Civil Protection Department.
 \n\nSpeaker(s): Prof. Mariagrazia Dotoli\, \n\nVia P. Bucci cubo 41C\, Ren
 de\, Calabria\, Italy\, 87036\, Virtual: https://events.vtools.ieee.org/m/
 263247
LOCATION:Via P. Bucci cubo 41C\, Rende\, Calabria\, Italy\, 87036\, Virtual
 : https://events.vtools.ieee.org/m/263247
ORGANIZER:g.fortino@unical.it
SEQUENCE:1
SUMMARY:IEEE SMC Italian Chapter Lecture Series on “Smart\, PErvasive and
  Mobile Systems Engineering”: Prof. Dotoli&#39;s Lecture
URL;VALUE=URI:https://events.vtools.ieee.org/m/263247
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;&lt;strong&gt;IEEE SMC Italian Chapter Virtual L
 ecture Series on &lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;&amp;ldquo\;Smart\, PErvasive and M
 obile Systems Engineering&amp;rdquo\;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;
 &lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Lecture Title &amp;ldquo\;&lt;/strong&gt;&lt;strong&gt;Optimal control st
 rategies to mitigate the COVID-19 outbreak in a multi-region scenario&lt;/str
 ong&gt;&lt;strong&gt;&amp;rdquo\;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;&amp;nbsp\;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;em
 &gt;University of Calabria&lt;/em&gt;&lt;/p&gt;\n&lt;p&gt;&lt;em&gt;On-line&lt;/em&gt;&lt;/p&gt;\n&lt;p&gt;&lt;em&gt;February
  26\, 2021&lt;/em&gt;&lt;/p&gt;\n&lt;p&gt;&lt;em&gt;12.00-13.00 CET&lt;/em&gt;&lt;/p&gt;\n&lt;p&gt;by&lt;/p&gt;\n&lt;p&gt;&lt;stron
 g&gt;Prof. Mariagrazia Dotoli&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;Politecnico di Bari\, Italy&lt;/p
 &gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Abstract:&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;In this talk\, af
 ter revising the main models used in the related literature for analyzing 
 the dynamics of infectious diseases\, we present a novel time-varying epid
 emiological model for COVID-19. The model belongs to the class of SIRCQTHE
  models (i.e.\, considering Susceptible\, Infected\, Removed\, Contagious\
 , Quarantined\, Threatened\, Healed\, and Extinct categories of individual
 s) and allows to get reliable predictions on the pandemic&amp;rsquo\;s dynamic
 s on a regional basis. We present an innovative stochastic non-linear cont
 rol approach that supports the decision or policy makers in determining ro
 bust optimal strategies to tackle the COVID-19 secondary waves. More preci
 sely\, based on the presented SIRCQTHE model\, a stochastic model predicti
 ve control problem is defined that allows policy makers to select the cont
 rol actions that minimize the pandemic&amp;rsquo\;s socio-economic costs\, i.e
 .\, various types of people&amp;rsquo\;s mobility restrictions (for example\, 
 closure of shops and restaurants\, closure of regional/municipality border
 s). In addition\, considering the unavoidable uncertainty characterizing t
 he model&amp;rsquo\;s parameters that strongly affect the decision-making proc
 ess\, we impose that the capacity of the network of regional healthcare sy
 stems is not violated\, in accordance with a chance constraint approach. T
 he effectiveness of the presented modeling and control technique in suppor
 ting the definition of diversified regional strategies for tackling the CO
 VID-19 spread is effectively tested on the network of Italian regions usin
 g real data from the Italian Civil Protection Department.&lt;/p&gt;
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