A mathematical model of infectious disease transmission

Abstract

In this paper we consider a three-dimensional nonlinear system which models the dynamics of a population during an epidemic disease. The considered model is a SIS-type system in which a recovered individual automatically becomes a susceptible one. We take into account the births and deaths, and we also consider that susceptible individuals are divided into two groups: non-vaccinated and vaccinated. In addition, we assume a medical scenario in which vaccinated people take a special measure to quarantine their newborns. We study the stability of the considered system. Numerical simulations point out the behavior of the considered population.

On the Duration of an Epidemic

“…The authors are generally interested in the stability analysis of their models and/or in computing the very important basic reproduction number . [ 4 ], among others, proposed a SIS-type (for Susceptible, Infected, Susceptible) model, and they studied its stability. In this paper, we consider a basic SIR (R standing for Recovered or Removed) model, to which random perturbations will be added to make it more realistic.…”

Estimation of COVID-19 Transmission and Advice on Public Health Interventions

“…Later, scholars around the globe conducted additional research on infectious diseases. For instance, Florea and Lzureanu (2020) simulated the spread of infectious diseases by using the Susceptible Infected Susceptible Model (SIS) system [13]; Zhang et al (2017) studied the spread of infectious diseases in the transportation system [14]. Under the circumstances of a pandemic, it is necessary to conduct research accounting for public health intervention measures.…”