Susceptible-Exposed-Infectious Model Using Markov Chains

In the present work we introduced and analyzed the most basic transmission SEI (susceptible-exposed-infective) model for a directly transmitted infectious disease caused by Coronavirus disease 2019 (COVID-19). The SEI model is modeling as a Markov chain and we computed a closed form formula of the m...

Full description

Saved in:
Bibliographic Details
Published inJournal of nonlinear mathematical physics Vol. 31; no. 1; p. 8
Main Authors Omar, F. M., Sohaly, M. A., El-Metwally, H.
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 06.02.2024
Springer Nature B.V
Subjects
Algorithms
COVID-19
Disease transmission
Epidemics
Infections
Infectious diseases
Markov analysis
Markov chains
Mathematical models
Mathematical Physics
Mathematics
Mathematics and Statistics
Media coverage
Pandemics
Probability
Public health
Random walk
Research Article
Viral diseases
COVID-19
Markov chain
MFPT’s vecto
Epidemic SEI model
State reduction
Random walk
Online AccessGet full text

Cover

More Information
Summary:In the present work we introduced and analyzed the most basic transmission SEI (susceptible-exposed-infective) model for a directly transmitted infectious disease caused by Coronavirus disease 2019 (COVID-19). The SEI model is modeling as a Markov chain and we computed a closed form formula of the mean first passage times (MFPT’s) vector arising from non-homogeneous Markov chain random walk (NHMC-RW) on the non-negative integers. Some particular cases, which lead to a relationship between the elements of the MFPT’s vectors. An efficient algorithm applied on mathematica program for computing MFPT’s vector of the NHMC-RW is given.
ISSN:1776-0852
1402-9251
1776-0852
DOI:10.1007/s44198-024-00167-3