Literature DB >> 31256205

Dynamics and asymptotic profiles of endemic equilibrium for SIS epidemic patch models.

Huicong Li1, Rui Peng2.   

Abstract

In this paper, we perform qualitative analysis to two SIS epidemic models in a patchy environment, without and with linear recruitment. The model without linear recruitment was proposed and studied by Allen et al. (SIAM J Appl Math 67(5):1283-1309, 2007). This model possesses a conserved total population number, whereas the model with linear recruitment has a varying total population. However, both models have the same basic reproduction number. For both models, we establish the global stability of endemic equilibrium in a special case, which partially solves an open problem. Then we investigate the asymptotic behavior of endemic equilibrium as the mobility of infected and/or susceptible population tends to zero. Though the basic reproduction number is a well-known critical index, our theoretical results strongly suggest that other factors such as the variation of total population number and individual movement may also play vital roles in disease prediction and control. In particular, our results imply that the variation of total population number can cause infectious disease to become more threatening and difficult to control.

Entities:  

Keywords:  Asymptotic profile; Basic reproduction number; Disease-free equilibrium; Endemic equilibrium; Global dynamics; SIS epidemic patch model

Year:  2019        PMID: 31256205     DOI: 10.1007/s00285-019-01395-8

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  14 in total

1.  Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission.

Authors:  P van den Driessche; James Watmough
Journal:  Math Biosci       Date:  2002 Nov-Dec       Impact factor: 2.144

2.  An epidemic model in a patchy environment.

Authors:  Wendi Wang; Xiao-Qiang Zhao
Journal:  Math Biosci       Date:  2004-07       Impact factor: 2.144

3.  On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations.

Authors:  O Diekmann; J A Heesterbeek; J A Metz
Journal:  J Math Biol       Date:  1990       Impact factor: 2.259

4.  Spatial patterns in a discrete-time SIS patch model.

Authors:  L J S Allen; Y Lou; A L Nevai
Journal:  J Math Biol       Date:  2008-06-12       Impact factor: 2.259

5.  Dynamics of an SIS reaction-diffusion epidemic model for disease transmission.

Authors:  Wenzhang Huang; Maoan Han; Kaiyu Liu
Journal:  Math Biosci Eng       Date:  2010-01       Impact factor: 2.080

6.  Dynamics of an epidemic model with non-local infections for diseases with latency over a patchy environment.

Authors:  Jing Li; Xingfu Zou
Journal:  J Math Biol       Date:  2009-07-01       Impact factor: 2.259

7.  A sharp threshold for disease persistence in host metapopulations.

Authors:  Thanate Dhirasakdanon; Horst R Thieme; P Van Den Driessche
Journal:  J Biol Dyn       Date:  2007-10       Impact factor: 2.179

8.  Multi-patch and multi-group epidemic models: a new framework.

Authors:  Derdei Bichara; Abderrahman Iggidr
Journal:  J Math Biol       Date:  2017-11-17       Impact factor: 2.259

9.  The effects of human movement on the persistence of vector-borne diseases.

Authors:  C Cosner; J C Beier; R S Cantrell; D Impoinvil; L Kapitanski; M D Potts; A Troyo; S Ruan
Journal:  J Theor Biol       Date:  2009-03-03       Impact factor: 2.691

10.  Effect of media-induced social distancing on disease transmission in a two patch setting.

Authors:  Chengjun Sun; Wei Yang; Julien Arino; Kamran Khan
Journal:  Math Biosci       Date:  2011-02-04       Impact factor: 2.144

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  2 in total

1.  On the Supervision of a Saturated SIR Epidemic Model with Four Joint Control Actions for a Drastic Reduction in the Infection and the Susceptibility through Time.

Authors:  Manuel De la Sen; Asier Ibeas; Santiago Alonso-Quesada
Journal:  Int J Environ Res Public Health       Date:  2022-01-28       Impact factor: 3.390

2.  Impact of State-Dependent Dispersal on Disease Prevalence.

Authors:  Daozhou Gao; Yuan Lou
Journal:  J Nonlinear Sci       Date:  2021-07-03       Impact factor: 3.621

  2 in total

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