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Robust Pandemic Control Synthesis with Formal Specifications: A Case Study on COVID-19 Pandemic
60th IEEE Conference on Decision and Control (CDC) ; : 2830-2835, 2021.
Article in English | Web of Science | ID: covidwho-1868524
ABSTRACT
Pandemics can bring a range of devastating consequences to public health and the world economy. Identifying the most effective control strategies has been the imperative task all around the world. Various public health control strategies have been proposed and tested against pandemic diseases (e.g., COVID-19). We study two specific pandemic control models the susceptible, exposed, infectious, recovered (SEIR) model with vaccination control;and the SEIR model with shield immunity control. We express the pandemic control requirement in metric temporal logic (MTL) formulas. We then develop an iterative approach for synthesizing the optimal control strategies with MTL specifications. We provide simulation results in two different scenarios for robust control of the COVID-19 pandemic one for vaccination control, and another for shield immunity control, with the model parameters estimated from data in Lombardy, Italy. The results show that the proposed synthesis approach can generate control inputs such that the time-varying numbers of individuals in each category (e.g., infectious, immune) satisfy the MTL specifications with robustness against initial state and parameter uncertainties.

Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Case report / Observational study Language: English Journal: 60th IEEE Conference on Decision and Control (CDC) Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Type of study: Case report / Observational study Language: English Journal: 60th IEEE Conference on Decision and Control (CDC) Year: 2021 Document Type: Article