Dynamics of COVID-19 Using SEIQR Epidemic Model
Journal of Mathematics
; 2022, 2022.
Article
in English
| ProQuest Central | ID: covidwho-2064324
ABSTRACT
The major goal of this study is to create an optimal technique for managing COVID-19 spread by transforming the SEIQR model into a dynamic (multistage) programming problem with continuous and discrete time-varying transmission rates as optimizing variables. We have developed an optimal control problem for a discrete-time, deterministic susceptible class (S), exposed class (E), infected class (I), quarantined class (Q), and recovered class (R) epidemic with a finite time horizon. The problem involves finding the minimum objective function of a controlled process subject to the constraints of limited resources. For our model, we present a new technique based on dynamic programming problem solutions that can be used to minimize infection rate and maximize recovery rate. We developed suitable conditions for obtaining monotonic solutions and proposed a dynamic programming model to obtain optimal transmission rate sequences. We explored the positivity and unique solvability nature of these implicit and explicit time-discrete models. According to our findings, isolating the affected humans can limit the danger of COVID-19 spreading in the future.
Mathematics; Infections; Infectious diseases; Social distancing; Dynamic programming; Mathematical models; Severe acute respiratory syndrome coronavirus 2; Epidemiology; Pandemics; Epidemics; Optimization; Medical research; Public health; Viral diseases; Constraint modelling; Optimal control; Coronaviruses; Disease transmission; COVID-19
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
Journal of Mathematics
Year:
2022
Document Type:
Article
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