33 results match your criteria Annual Reviews In Control[Journal]

COVID-19 epidemic control using short-term lockdowns for collective gain.

Annu Rev Control 2021 26;52:573-586. Epub 2021 Nov 26.

Department of Information Engineering, University of Padova, Padova, Italy.

While many efforts are currently devoted to vaccines development and administration, social distancing measures, including severe restrictions such as lockdowns, remain fundamental tools to contain the spread of COVID-19. A crucial point for any government is to understand, on the basis of the epidemic curve, the right temporal instant to set up a lockdown and then to remove it. Different strategies are being adopted with distinct shades of intensity. Read More

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November 2021

Convex output feedback model predictive control for mitigation of COVID-19 pandemic.

Annu Rev Control 2021 27;52:543-553. Epub 2021 Oct 27.

Pázmány Péter Catholic University, H-1083 Práter u. 50/a, Budapest, Hungary.

In this paper, a model predictive control approach is proposed for epidemic mitigation. The disease spreading dynamics is described by an 8-compartment smooth nonlinear model of the COVID-19 pandemic in Hungary known from the literature, where the manipulable control input is the stringency of the introduced non-pharmaceutical measures. It is assumed that only the number of hospitalized people is measured on-line, and the other state variables are computed using a state observer which is based on the dynamic inversion of a linear sub-system of the model. Read More

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October 2021

Modeling and control of epidemics through testing policies.

Annu Rev Control 2021 14;52:554-572. Epub 2021 Oct 14.

Sorbonne Université, Université Paris-Diderot SPC, Inria, CNRS, Laboratoire Jacques-Louis Lions, équipe Mamba, 75005 Paris, France.

Testing is a crucial control mechanism in the beginning phase of an epidemic when the vaccines are not yet available. It enables the public health authority to detect and isolate the infected cases from the population, thereby limiting the disease transmission to susceptible people. However, despite the significance of testing in epidemic control, the recent literature on the subject lacks a control-theoretic perspective. Read More

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October 2021

Hysteresis-based supervisory control with application to non-pharmaceutical containment of COVID-19.

Annu Rev Control 2021 13;52:508-522. Epub 2021 Aug 13.

School of Computing Science, University of Glasgow, Glasgow, Scotland.

The recent COVID-19 outbreak has motivated an extensive development of non-pharmaceutical intervention policies for epidemics containment. While a total lockdown is a viable solution, interesting policies are those allowing some degree of normal functioning of the society, as this allows a continued, albeit reduced, economic activity and lessens the many societal problems associated with a prolonged lockdown. Recent studies have provided evidence that fast periodic alternation of lockdown and normal-functioning days may effectively lead to a good trade-off between outbreak abatement and economic activity. Read More

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Data-driven methods for present and future pandemics: Monitoring, modelling and managing.

Annu Rev Control 2021 29;52:448-464. Epub 2021 Jun 29.

Department of Industrial Engineering, University of Trento, Trento, Italy.

This survey analyses the role of data-driven methodologies for pandemic modelling and control. We provide a roadmap from the access to epidemiological data sources to the control of epidemic phenomena. We review the available methodologies and discuss the challenges in the development of data-driven strategies to combat the spreading of infectious diseases. Read More

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Dynamical characterization of antiviral effects in COVID-19.

Annu Rev Control 2021 28;52:587-601. Epub 2021 May 28.

Institute of Technological Development for the Chemical Industry (INTEC), CONICET-UNL, Santa Fe, Argentina.

Mathematical models describing SARS-CoV-2 dynamics and the corresponding immune responses in patients with COVID-19 can be critical to evaluate possible clinical outcomes of antiviral treatments. In this work, based on the concept of virus spreadability in the host, antiviral effectiveness thresholds are determined to establish whether or not a treatment will be able to clear the infection. In addition, the virus dynamic in the host - including the time-to-peak and the final monotonically decreasing behavior - is characterized as a function of the time to treatment initiation. Read More

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Multitask learning and nonlinear optimal control of the COVID-19 outbreak: A geometric programming approach.

Annu Rev Control 2021 19;52:495-507. Epub 2021 May 19.

Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.

We propose a multitask learning approach to learn the parameters of a compartmental discrete-time epidemic model from various data sources and use it to design optimal control strategies of human-mobility restrictions that both curb the epidemic and minimize the economic costs associated with implementing non-pharmaceutical interventions. We develop an extension of the SEIR epidemic model that captures the effects of changes in human mobility on the spread of the disease. The parameters of the model are learned using a multitask learning approach that leverages both data on the number of deaths across a set of regions, and cellphone data on individuals' mobility patterns specific to each region. Read More

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Universal features of epidemic models under social distancing guidelines.

Annu Rev Control 2021 23;51:426-440. Epub 2021 Apr 23.

Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, United States.

Social distancing as a form of nonpharmaceutical intervention has been enacted in many countries as a form of mitigating the spread of COVID-19. There has been a large interest in mathematical modeling to aid in the prediction of both the total infected population and virus-related deaths, as well as to aid government agencies in decision making. As the virus continues to spread, there are both economic and sociological incentives to minimize time spent with strict distancing mandates enforced, and/or to adopt periodically relaxed distancing protocols, which allow for scheduled economic activity. Read More

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Crowd management COVID-19.

Annu Rev Control 2021 12;52:465-478. Epub 2021 Apr 12.

CINVESTAV Unidad Guadalajara, Av del Bosque 1145, El Bajío, 45017 Zapopan, Jalisco, Mexico1URL:.

Crowds are a source of transmission in the COVID-19 spread. Contention and mitigation measures have focused on reducing people's mass gathering. Such efforts have led to a drop in the economy. Read More

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Forecasting COVID-19 cases based on a parameter-varying stochastic SIR model.

Annu Rev Control 2021 8;51:460-476. Epub 2021 Apr 8.

University of California, Santa Barbara, USA.

We address the prediction of the number of new cases and deaths for the coronavirus disease 2019 (COVID-19) over a future horizon from historical data (forecasting). We use a model-based approach based on a stochastic Susceptible-Infections-Removed (SIR) model with time-varying parameters, which captures the evolution of the disease dynamics in response to changes in social behavior, non-pharmaceutical interventions, and testing rates. We show that, in the presence of asymptomatic cases, such model includes internal parameters and states that cannot be uniquely identified solely on the basis of measurements of new cases and deaths, but this does not preclude the construction of reliable forecasts for future values of these measurements. Read More

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Smart testing and selective quarantine for the control of epidemics.

Annu Rev Control 2021 26;51:540-550. Epub 2021 Mar 26.

Service d'Automatique et d'Analyse des Systèmes: Université Libre de Bruxelles (ULB), Av. F.D. Roosvelt 50, CP 165/55, 1050 Brussels, Belgium.

This paper is based on the observation that, during Covid-19 epidemic, the choice of which individuals should be tested has an important impact on the effectiveness of selective confinement measures. This decision problem is closely related to the problem of optimal sensor selection, which is a very active research subject in control engineering. The goal of this paper is to propose a policy to smartly select the individuals to be tested. Read More

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A time-modulated Hawkes process to model the spread of COVID-19 and the impact of countermeasures.

Annu Rev Control 2021 12;51:551-563. Epub 2021 Mar 12.

IAC-CNR, Via dei Taurini 19, Roma, Italy.

Motivated by the recent outbreak of coronavirus (COVID-19), we propose a stochastic model of epidemic temporal growth and mitigation based on a time-modulated Hawkes process. The model is sufficiently rich to incorporate specific characteristics of the novel coronavirus, to capture the impact of undetected, asymptomatic and super-diffusive individuals, and especially to take into account time-varying counter-measures and detection efforts. Yet, it is simple enough to allow scalable and efficient computation of the temporal evolution of the epidemic, and exploration of what-if scenarios. Read More

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Monitoring and forecasting the COVID-19 epidemic in the UK.

Annu Rev Control 2021 18;51:488-499. Epub 2021 Feb 18.

School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China.

This paper shows how existing methods of time series analysis and modeling can be exploited in novel ways to monitor and forecast the COVID-19 epidemic. In the past, epidemics have been monitored by various statistical and model metrics, such as evaluation of the effective reproduction number, . However, can be difficult and time consuming to compute. Read More

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February 2021

On an interval prediction of COVID-19 development based on a SEIR epidemic model.

Annu Rev Control 2021 18;51:477-487. Epub 2021 Feb 18.

Inria, Univ. Lille, CNRS, UMR 9189 - CRIStAL, F-59000 Lille, France.

In this paper, a new version of the well-known epidemic mathematical SEIR model is used to analyze the pandemic course of COVID-19 in eight different countries. One of the proposed model's improvements is to reflect the societal feedback on the disease and confinement features. The SEIR model parameters are allowed to be time-varying, and the ranges of their values are identified by using publicly available data for France, Italy, Spain, Germany, Brazil, Russia, New York State (US), and China. Read More

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February 2021

The Ockham's razor applied to COVID-19 model fitting French data.

Annu Rev Control 2021 29;51:500-510. Epub 2021 Jan 29.

Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, 38000 Grenoble, France.

This paper presents a data-based simple model for fitting the available data of the Covid-19 pandemic evolution in France. The time series concerning the 13 regions of mainland France have been considered for fitting and validating the model. An extremely simple, two-dimensional model with only two parameters demonstrated to be able to reproduce the time series concerning the number of daily demises caused by Covid-19, the hospitalizations, intensive care and emergency accesses, the daily number of positive tests and other indicators, for the different French regions. Read More

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January 2021

Optimal design of lock-down and reopening policies for early-stage epidemics through SIR-D models.

Annu Rev Control 2021 23;51:511-524. Epub 2020 Dec 23.

Istituto di Analisi dei Sistemi ed Informatica "A. Ruberti", Consiglio Nazionale delle Ricerche (IASI-CNR), 00185 Roma, Italy.

The diffusion of COVID-19 represents a real threat for the health and economic system of a country. Therefore the governments have to adopt fast containment measures in order to stop its spread and to prevent the related devastating consequences. In this paper, a technique is proposed to optimally design the lock-down and reopening policies so as to minimize an aggregate cost function accounting for the number of individuals that decease due to the spread of COVID-19. Read More

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December 2020

Robust and optimal predictive control of the COVID-19 outbreak.

Annu Rev Control 2021 23;51:525-539. Epub 2020 Dec 23.

Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany.

We investigate adaptive strategies to robustly and optimally control the COVID-19 pandemic via social distancing measures based on the example of Germany. Our goal is to minimize the number of fatalities over the course of two years without inducing excessive social costs. We consider a tailored model of the German COVID-19 outbreak with different parameter sets to design and validate our approach. Read More

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December 2020

Structural identifiability and observability of compartmental models of the COVID-19 pandemic.

Annu Rev Control 2021 21;51:441-459. Epub 2020 Dec 21.

BioProcess Engineering Group, IIM-CSIC, Vigo 36208, Galicia, Spain.

The recent coronavirus disease (COVID-19) outbreak has dramatically increased the public awareness and appreciation of the utility of dynamic models. At the same time, the dissemination of contradictory model predictions has highlighted their limitations. If some parameters and/or state variables of a model cannot be determined from output measurements, its ability to yield correct insights - as well as the possibility of controlling the system - may be compromised. Read More

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December 2020

A time-varying SIRD model for the COVID-19 contagion in Italy.

Annu Rev Control 2020 26;50:361-372. Epub 2020 Oct 26.

Istituto di Analisi dei Sistemi ed Informatica "A. Ruberti," Consiglio Nazionale delle Ricerche (IASI-CNR), Roma 00185, Italy.

The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered-Deceased (SIRD) model for the contagion, and we used official data of the pandemic for identifying the parameters of this model. Our approach features two main non-standard aspects. Read More

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October 2020

Modelling a pandemic with asymptomatic patients, impact of lockdown and herd immunity, with applications to SARS-CoV-2.

Annu Rev Control 2020 9;50:432-447. Epub 2020 Oct 9.

Indian Institute of Technology Hyderabad India.

The SARS-CoV-2 is a type of coronavirus that has caused the pandemic known as the Coronavirus Disease of 2019, or COVID-19. In traditional epidemiological models such as SEIR (Susceptible, Exposed, Infected, Removed), the exposed group does not infect the susceptible group . A distinguishing feature of COVID-19 is that, unlike with previous viral diseases, there is a distinct "asymptomatic" group , which does not show any symptoms, but can nevertheless infect others, at the same rate as infected symptomatic patients. Read More

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October 2020

Characterization of SARS-CoV-2 dynamics in the host.

Annu Rev Control 2020 6;50:457-468. Epub 2020 Oct 6.

Institute of Technological Development for the Chemical Industry (INTEC), CONICET-UNL, Santa Fe, Argentina.

While many epidemiological models were proposed to understand and handle COVID-19 pandemic, too little has been invested to understand human viral replication and the potential use of novel antivirals to tackle the infection. In this work, using a control theoretical approach, validated mathematical models of SARS-CoV-2 in humans are characterized. A complete analysis of the main dynamic characteristic is developed based on the reproduction number. Read More

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October 2020

Transport effect of COVID-19 pandemic in France.

Annu Rev Control 2020 5;50:394-408. Epub 2020 Oct 5.

Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, F-38000 Grenoble, France.

An extension of the classical pandemic SIRD model is considered for the regional spread of COVID-19 in France under lockdown strategies. This compartment model divides the infected and the recovered individuals into undetected and detected compartments respectively. By fitting the extended model to the real detected data during the lockdown, an optimization algorithm is used to derive the optimal parameters, the initial condition and the epidemics start date of regions in France. Read More

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October 2020

From the hospital scale to nationwide: observability and identification of models for the COVID-19 epidemic waves.

Annu Rev Control 2020 3;50:409-416. Epub 2020 Oct 3.

DIAG, Università di Roma, via Ariosto 25, Roma 00184, Italy.

Two mathematical models of the COVID-19 dynamics are considered as the health system in some country consists in a network of regional hospital centers. The first model for the virus dynamics at the level of the general population of the country is derived from a standard SIR model. The second model refers to a single node of the health system network, i. Read More

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October 2020

Model predictive control to mitigate the COVID-19 outbreak in a multi-region scenario.

Annu Rev Control 2020 1;50:373-393. Epub 2020 Oct 1.

Dept. of Electrical and Information Engineering, Polytechnic of Bari via Orabona 4, 70125 Bari, Italy.

The COVID-19 outbreak is deeply influencing the global social and economic framework, due to restrictive measures adopted worldwide by governments to counteract the pandemic contagion. In multi-region areas such as Italy, where the contagion peak has been reached, it is crucial to find targeted and coordinated optimal exit and restarting strategies on a regional basis to effectively cope with possible onset of further epidemic waves, while efficiently returning the economic activities to their standard level of intensity. Differently from the related literature, where modeling and controlling the pandemic contagion is typically addressed on a national basis, this paper proposes an optimal control approach that supports governments in defining the most effective strategies to be adopted during post-lockdown mitigation phases in a multi-region scenario. Read More

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October 2020

In-host Mathematical Modelling of COVID-19 in Humans.

Annu Rev Control 2020 30;50:448-456. Epub 2020 Sep 30.

Instituto de Matemáticas, Universidad Nacional Autonoma de Mexico, Boulevard Juriquilla 3001, Querétaro, Qro., 76230, México.

COVID-19 pandemic has underlined the impact of emergent pathogens as a major threat to human health. The development of quantitative approaches to advance comprehension of the current outbreak is urgently needed to tackle this severe disease. Considering different starting times of infection, mathematical models are proposed to represent SARS-CoV-2 dynamics in infected patients. Read More

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September 2020

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

Annu Rev Control 2020 29;50:417-431. Epub 2020 Jul 29.

Renewable Energy Research Group (GPER), Departamento de Automação e Sistemas (DAS), Universidade Federal de Santa Catarina, Florianópolis, Brazil.

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. Read More

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A Review of Electrical Impedance Tomography in Lung Applications: Theory and Algorithms for Absolute Images.

Annu Rev Control 2019 17;48:442-471. Epub 2019 May 17.

Computational Geometry Laboratory, Escola Politécnica da Universidade de São Paulo, Brazil.

Electrical Impedance Tomography (EIT) is under fast development, the present paper is a review of some procedures that are contributing to improve spatial resolution and material properties accuracy, admitivitty or impeditivity accuracy. A review of EIT medical applications is presented and they were classified into three broad categories: ARDS patients, obstructive lung diseases and perioperative patients. The use of absolute EIT image may enable the assessment of absolute lung volume, which may significantly improve the clinical acceptance of EIT. Read More

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