On a SVEIRS Markov chain epidemic model with multiple discrete delay times and sensitivity analysis to determine vaccination effects
Document Type
Presentation
Presentation Date
4-3-2021
Abstract or Description
Presentation given at the Southern Georgia Mathematics Conference.
A novel discrete time general Markov chain SEIRS epidemic model with vaccination is derived and studied. The model incorporates finite delay times for disease incubation, natural and artificial immunity periods, and the period of infectiousness of infected individuals. The novel platform for representing the different states of the disease in the population utilizes two discrete time measures for the current time of a person’s state, and how long a person has been in the current state. Two sub-models are derived based on whether the drive to get vaccinated is inspired by close contacts with infectious individuals or otherwise. Sensitivity analysis is conducted on the two models to determine how vaccination affects disease eradication.
Sponsorship/Conference/Institution
Southern Georgia Mathematics Conference
Location
Virtual
Source
https://sites.google.com/biust.ac.bw/mathsstats-conference2021/schedule?authuser=0
Recommended Citation
Jegede, Omotomilola, Divine Wanduku, Chinmoy R. Rahul.
2021.
"On a SVEIRS Markov chain epidemic model with multiple discrete delay times and sensitivity analysis to determine vaccination effects."
Department of Mathematical Sciences Faculty Presentations.
Presentation 762.
source: https://sites.google.com/biust.ac.bw/mathsstats-conference2021/schedule?authuser=0
https://digitalcommons.georgiasouthern.edu/math-sci-facpres/762
