ArticleAnnual reviews in control2020
Model predictive control to mitigate the COVID-19 outbreak in a multi-region scenario.
Article in Annual reviews in control, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Data-driven strategies for model-informed decision-making during the COVID-19 pandemic: a systematic review.BMJ open · 2026Pooled it
- Optimal control prevents itself from eradicating stochastic disease epidemics.PLoS computational biology · 2025Article
- A novel compartmental approach for modeling stomach motility and gastric emptying.Computers in biology and medicine · 2024Article
- Enhanced SARS-CoV-2 case prediction using public health data and machine learning models.JAMIA open · 2024Article
- Optimal social distancing in epidemic control: cost prioritization, adherence and insights into preparedness principles.Scientific reports · 2024Article
- Optimal strategies for coordinating infection control and socio-economic activities.Mathematics and computers in simulation · 2023Article
- Effective pandemic policy design through feedback does not need accurate predictions.PLOS global public health · 2023Article
- The Importance of Uncertainty in Health Scenarios: A Scoping Review on COVID-19 Scenarios.Medical journal of the Islamic Republic of Iran · 2023Article
- A stochastic inventory model of COVID-19 and robust, real-time identification of carriers at large and infection rate via asymptotic laws.European journal of operational research · 2023Article
- Multi-criteria decision making of COVID-19 vaccines (in India) based on ranking interpreter technique under single valued bipolar neutrosophic environment.Expert systems with applications · 2022Article
- Consequences of SARS-CoV-2 pandemic on urological surgery in France: a nationwide analysis of the healthcare system database.BMJ open · 2022Observational
- Recursive state and parameter estimation of COVID-19 circulating variants dynamics.Scientific reports · 2022Article
- Decision analysis of international joint prevention and control of public health emergencies.Environment, development and sustainability · 2022Article
- Chasing up and locking down the virus: Optimal pandemic interventions within a network.Journal of public economic theory · 2022Article
- Modelling the spreading of the SARS-CoV-2 in presence of the lockdown and quarantine measures by a kinetic-type reactions approach.Mathematical medicine and biology : a journal of the IMA · 2022Article
- Dynamic resource allocation for controlling pathogen spread on a large metapopulation network.Journal of the Royal Society, Interface · 2022Article
- A multi-layer network model to assess school opening policies during a vaccination campaign: a case study on COVID-19 in France.Applied network science · 2022Article
- Age structure in SIRD models for the COVID-19 pandemic-A case study on Italy data and effects on mortality.PloS one · 2022Article
- COVID-19 Testing Unit Munich: Impact of Public Health and Safety Measures on Patient Characteristics and Test Results, January to September 2020.Frontiers in public health · 2022Article
- Design a robust sliding mode controller based on the state and parameter estimation for the nonlinear epidemiological model of Covid-19.Nonlinear dynamics · 2022Article
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5 authors.
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Abstract
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. Based on the joint use of a non-linear Model Predictive Control scheme and a modified Susceptible-Infected-Recovered (SIR)-based epidemiological model, the approach is aimed at minimizing the cost of the so-called non-pharmaceutical interventions (that is, mitigation strategies), while ensuring that the capacity of the network of regional healthcare systems is not violated. In addition, the proposed approach supports policy makers in taking targeted intervention decisions on different regions by an integrated and structured model, thus both respecting the specific regional health systems characteristics and improving the system-wide performance by avoiding uncoordinated actions of the regions. The methodology is tested on the COVID-19 outbreak data related to the network of Italian regions, showing its effectiveness in properly supporting the definition of effective regional strategies for managing the COVID-19 diffusion.
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