About: An optimal predictive control strategy for COVID-19 (SARS-CoV-2) social distancing policies in Brazil

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About: An optimal predictive control strategy for COVID-19 (SARS-CoV-2) social distancing policies in Brazil Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	An optimal predictive control strategy for COVID-19 (SARS-CoV-2) social distancing policies in Brazil
Creator	Bastos, Saulo Cajueiro, Daniel Morato, Marcelo Normey-Rico, Julio
Source	Elsevier; Medline; PMC
abstract	This paper formulates a Model Predictive Control (MPC) policy to mitigate the COVID-19 contagion in Brazil, designed as optimal On-Off social isolation strategy. The proposed optimization algorithm is able to determine the time and duration of social distancing policies in the country. The achieved results are based on data from the period between March and May of 2020, regarding the cumulative number of infections and deaths due to the SARS-CoV-2 virus. This dataset is assumably largely sub-notified due to the absence of mass testing in Brazil. Thus, the MPC is based on a SIR model which is identified using an uncertainty-weighted Least-Squares criterion. Furthermore, this model includes an additional dynamic variable that mimics the response of the population to the social distancing policies determined by the government, which affect the COVID-19 transmission rate. The proposed control method is set within a mixed-logical formalism, since the decision variable is forcefully binary (existence or the absence of social distance policy). A dwell-time constraint is included to avoid too frequent shifts between these two inputs. The achieved simulation results illustrate how such optimal control method would operate in practice, pointing out that no social distancing should be relaxed before mid August 2020. If relaxations are necessary, they should not be performed before this date and should be in small periods, no longer than 25 days. This paradigm would proceed roughly until January/2021. The results also indicate a possible second peak of infections, which has a forecast to the beginning of October. This peak can be reduced if the periods of days with relaxed social isolation measures are shortened.
has issue date	2020-07-29(xsd:dateTime)
bibo:doi	10.1016/j.arcontrol.2020.07.001
bibo:pmid	32837241
has license	no-cc
sha1sum (hex)	4cde8f0090e5b895ad4ae7cd3cc0ab118c7d1b43
schema:url	https://doi.org/10.1016/j.arcontrol.2020.07.001
resource representing a document's title	An optimal predictive control strategy for COVID-19 (SARS-CoV-2) social distancing policies in Brazil
has PubMed Central identifier	PMC7388786
has PubMed identifier	32837241
schema:publication	Annu Rev Control
resource representing a document's body	covid:4cde8f0090e5b895ad4ae7cd3cc0ab118c7d1b43#body_text
is schema:about of	named entity 'transmission rate' named entity 'COVID-19' named entity 'weighted Least-Squares' named entity 'social distancing' named entity 'COVID-19' named entity 'SARS-CoV-2' named entity 'SARS-CoV-2 virus' named entity 'COVID-19 pandemic' named entity 'COVID' named entity 'ICU beds' named entity 'social distancing' named entity 'social distancing' named entity 'social traumas' named entity 'SARS-CoV-2' named entity 'social isolation' named entity 'ICUs' named entity 'susceptible individual' named entity 'SIR model' named entity 'COVID' named entity 'virus' named entity 'optimal control' named entity 'infection' named entity 'MPC' named entity 'federated states' named entity 'self-isolation' named entity 'MPC' named entity 'Brazil' named entity 'COVID-19' named entity 'infection' named entity 'MPC' named entity 'SARS-CoV-2 outbreak' named entity 'August 14' named entity 'social isolation' named entity 'health systems' named entity 'COVID-19' named entity 'infection' named entity 'COVID-19 pandemic' named entity 'MPC' named entity 'Brazil' named entity 'infection' named entity 'mathematical problem' named entity 'social distancing' named entity 'rash decisions' named entity 'social distancing' named entity 'ICU' named entity 'social isolation' named entity 'social distancing' named entity 'virus' named entity 'social isolation' named entity 'Brazil' named entity 'Belgium' named entity 'May 23' named entity 'COVID-19 pandemic' named entity 'stay home' named entity 'virus' named entity 'ICU beds' named entity 'cost function' named entity 'COVID' named entity 'MPC' named entity 'virus' named entity 'social distancing' named entity 'MPC' named entity 'COVID-19' named entity 'China' named entity 'social distancing' named entity 'community transmission' named entity 'ICU beds' named entity 'ICU beds' named entity 'COVID-19' named entity 'social isolation' named entity 'SARS-CoV-2' named entity 'Brazil' named entity 'WHO' named entity 'social distance' named entity 'vaccine' named entity 'SIR model' named entity 'COVID-19' named entity 'COVID-19 pandemic'

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