Evidence map›Paper›PMID 33309260›Full record

ArticleISA transactions2022

A parametrized nonlinear predictive control strategy for relaxing COVID-19 social distancing measures in Brazil.

Marcelo M Morato, Igor M L Pataro, Marcus V Americano da Costa, Julio E Normey-Rico

Abstract read
In one paragraph

Article in ISA transactions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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  10. Hybrid Model-Based Simulation Analysis on the Effects of Social Distancing Policy of the COVID-19 Epidemic.International journal of environmental research and public health · 2021
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  11. Article
  12. Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.IEEE access : practical innovations, open solutions · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Marcelo M MoratoRenewable Energy Research Group (GPER), Department of Automation and Systems (DAS), Federal University of Santa Catarina (UFSC), Florianópolis, Brazil. Electronic address: marcelomnzm@gmail.com.
Igor M L PataroCIESOL, Department of Informatics, University of Almería, Ctra. Sacramento s/n 04120, Almería, Spain. Electronic address: ilp428@inlumine.ual.es.
Marcus V Americano da CostaDepartment of Chemical Engineering (DEQ), Federal University of Bahia (UFBA), 02 Professor Aristides Novis St., Salvador, BA-40210910, Brazil. Electronic address: marcus.americano@ufba.br.
Julio E Normey-RicoRenewable Energy Research Group (GPER), Department of Automation and Systems (DAS), Federal University of Santa Catarina (UFSC), Florianópolis, Brazil. Electronic address: julio.normey@ufsc.br.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 virus was first registered in Brazil by the end of February 2020. Since then, the country counts over 150000 deaths due to COVID-19 and faces a profound social and economic crisis; there is also an ongoing health catastrophe, with the majority of hospital beds in many Brazilian cities currently occupied with COVID-19 patients. Thus, a Nonlinear Model Predictive Control (NMPC) scheme used to plan appropriate social distancing measures (and relaxations) in order to mitigate the effects of this pandemic is formulated in this paper. The strategy is designed upon an adapted data-driven Susceptible-Infected-Recovered-Deceased (SIRD) model, which includes time-varying auto-regressive immunological parameters. A novel identification procedure is proposed, composed of analytical regressions, Least-Squares optimization and auto-regressive model fits. The adapted SIRD model is validated with real data and able to adequately represent the contagion curves over large forecast horizons. The NMPC strategy is designed to generate piecewise constant quarantine guidelines, which can be reassessed (relaxed/strengthened) each week. Simulation results show that the proposed NMPC technique is able to mitigate the number of infections and progressively loosen social distancing measures. With respect to a "no-control" condition, the number of deaths could be reduced in up to 30% if the proposed NMPC coordinated health policy measures are enacted.

Indexed as

COVID-19BrazilHumansPandemicsPhysical DistancingSARS-CoV-2COVID-19Nonlinear Model Predictive ControlSIRD ModelSocial isolationSystem Identification

Identifiers

PMID33309260
PMCPMC7834916

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.