A note on persistence about structured population models.

J Biol Dyn

Graduate School of Mathematical Sciences, The University of Tokyo, Tokyo, Japan.

Published: October 2008

AI Article Synopsis

  • The paper discusses persistence in two structured population models related to epidemics: a chronic age-structured model and an age-duration-structured model.
  • The authors find that if the basic reproduction ratio is greater than one, the proportion of the infected population remains positive over time, regardless of initial conditions.
  • They use Thieme's technique and Fréchet-Kolmogorov criteria to address challenges in proving conditions related to positivity and compactness in these infinite-dimensional models.

Article Abstract

In this paper, we report some results on persistence in two structured population models: a chronic- age-structured epidemic model and an age-duration-structured epidemic model. Regarding these models, we observe that the system is uniformly strongly persistent, which means, roughly speaking, that the proportion of infected subpopulation is bounded away from 0 and the bound does not depend on the initial data after a sufficient long time, if the basic reproduction ratio is larger than one. We derive this by adopting Thieme's technique, which requires some conditions about positivity and compactness. Although the compactness condition is rather difficult to show in general infinite-dimensional function spaces, we can apply Fréchet-Kolmogorov L(1)-compactness criteria to our models. The two examples that we study illuminate a useful method to show persistence in structured population models.

Download full-text PDF

Source
http://dx.doi.org/10.1080/17513750802213581DOI Listing

Publication Analysis

Top Keywords

persistence structured
12
structured population
12
population models
12
epidemic model
8
models
5
note persistence
4
models paper
4
paper report
4
report persistence
4
models chronic-
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!