Journal Article Ppublish 11 citations
PubMed: 34630624 DOI: 10.1016/j.bspc.2021.103227
Epidemic model dynamics and fuzzy neural-network optimal control with impulsive traveling and migrating: Case study of COVID-19 vaccination.
Biomed Signal Process Control 71:103227
Authors: C Treesatayapun
Affiliations
- Department of Robotic and Advanced Manufacturing, CINVESTAV-IPN, Mexico.
Abstract
To suppress the epidemics caused by a virus such as COVID-19, three effective strategies listing vaccination, quarantine and medical treatments, are employed under suitable policies. Quarantine motions may affect the economic systems and pharmaceutical medications may be recently in the developing phase. Thus, vaccination seems the best hope of the current situation to control COVID-19 epidemics. In this work, the dynamic model of COVID-19 epidemic is developed when the quarantine factor and the antiviral factor are established as free variables. Moreover, the impulsive populations are comprehended for traveling and migrating of individuals. The proposed dynamics with impulsive distractions are employed to generate the online data. Thereafter, the equivalent model is developed by using only the daily data of symptomatic infectious individuals and the optimal vaccination policy is derived by utilizing the closed-loop control topology. The theoretical framework of the proposed schemes validates the reduction of symptomatic infectious individuals by using fewer doses of vaccines comparing with the scheduling vaccination.
MeSH
Vaccines, Vaccination, Covid-19, Work, Quarantine, Epidemics
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- Kalman-based compartmental estimation for covid-19 pandemic using advanced epidemic model. Biomed Signal Process Control, 2023
- Interval type-2 Fuzzy control and stochastic modeling of COVID-19 spread based on vaccination and social distancing rates. Comput Methods Programs Biomed, 2023