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Title: Model Predictive Control in Optimal Intervention of Covid-19 with Mixed Epistemic-Aleatoric Uncertainty
Non-pharmaceutical interventions (NPI) have been proven vital in the fight against the COVID-19 pandemic before the massive rollout of vaccinations. Considering the inherent epistemic-aleatoric uncertainty of parameters, accurate simulation and modeling of the interplay between the NPI and contagion dynamics are critical to the optimal design of intervention policies. We propose a modified SIRD-MPC model that combines a modified stochastic Susceptible-Infected-Recovered-Deceased (SIRD) compartment model with mixed epistemic-aleatoric parameters and Model Predictive Control (MPC), to develop robust NPI control policies to contain the infection of the COVID-19 pandemic with minimum economic impact. The simulation result indicates that our proposed model can significantly decrease the infection rate compared to the practical results under the same initial conditions.  more » « less
Award ID(s):
2119334
PAR ID:
10548187
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
IEEE
Date Published:
ISBN:
979-8-3503-6966-3
Page Range / eLocation ID:
722 to 733
Format(s):
Medium: X
Location:
San Antonio, TX, USA
Sponsoring Org:
National Science Foundation
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