Open AccessGlobal stability mathematical analysis for virus transmission model with latent age structure
Author(s) -
Shanjing Ren,
AUTHOR_ID,
Lingling Li,
AUTHOR_ID
Publication year - 2022
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2022154
Subject(s) - epidemic model , basic reproduction number , lyapunov function , stability theory , transmission (telecommunications) , stability (learning theory) , population , age structure , mathematical model , mathematics , transmission rate , infectious disease (medical specialty) , computer science , disease , statistics , medicine , physics , environmental health , telecommunications , pathology , nonlinear system , quantum mechanics , machine learning
Background and objective Mathematical model is a very important method for the control and prevention of disease transmissing. Based on the communication characteristics of diseases, it is necesssery to add fast and slow process into the model of infectious diseases, which more effectively shows the transmission mechanism of infectious diseases. Methods This paper proposes an age structure epidemic model with fast and slow progression. We analyze the model's dynamic properties by using the stability theory of differential equation under the assumption of constant population size. Results The very important threshold $ R_{0} $ was calculated. If $ R_{0} < 1 $, the disease-free equilibrium is globally asymptotically stable, whereas if $ R_{0} > 1 $, the Lyapunov function is used to show that endemic equilibrium is globally stable. Through more in-depth analysis for basic reproduction number, we obtain the greater the rate of slow progression of an infectious disease, the fewer the threshold results. In addition, we also provided some numerical simulations to prove our result. Conclusions Vaccines do not provide lifelong immunity, but can reduce the mortality of those infected. By vaccinating, the rate of patients entering slow progression increases and the threshold is correspondingly reduced. Therefore, vaccination can effectively control the transmission of Coronavirus. The theoretical incidence predicted by mathematical model can provide evidence for prevention and controlling the spread of the epidemic.