Dynamics of a Filippov epidemic model with limited hospital beds

A Filippov epidemic model is proposed to explore the impact of capacity and limited resources of public health system on the control of epidemic diseases. The number of infected cases is chosen as an index to represent a threshold policy, that is, the capacity dependent treatment policy is implement...

Full description

Saved in:
Bibliographic Details
Main Authors: Aili Wang, Yanni Xiao, Huaiping Zhu
Format: Article
Language:English
Published: AIMS Press 2018-05-01
Series:Mathematical Biosciences and Engineering
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2018033
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832590049322991616
author Aili Wang
Yanni Xiao
Huaiping Zhu
author_facet Aili Wang
Yanni Xiao
Huaiping Zhu
author_sort Aili Wang
collection DOAJ
description A Filippov epidemic model is proposed to explore the impact of capacity and limited resources of public health system on the control of epidemic diseases. The number of infected cases is chosen as an index to represent a threshold policy, that is, the capacity dependent treatment policy is implemented when the case number exceeds a critical level, and constant treatment rate is adopted otherwise. The proposed Filippov model exhibits various local sliding bifurcations, including boundary focus or node bifurcation, boundary saddle bifurcation and boundary saddle-node bifurcation, and global sliding bifurcations, including grazing bifurcation and sliding homoclinic bifurcation to pseudo-saddle. The impact of some key parameters including the threshold level on disease control is examined by numerical analysis. Our results suggest that strengthening the basic medical conditions, i.e. increasing the minimum treatment ratio, or enlarging the input of medical resources, i.e. increasing HBPR (i.e. hospital bed-population ratio) as well as the possibility and level of maximum treatment ratio, can help to contain the case number at a relatively low level when the basic reproduction number $R_0 \gt 1$. If $R_0 \lt 1$, implementing these strategies can help in eradicating the disease although the disease cannot always be eradicated due to the occurring of backward bifurcation in the system.
format Article
id doaj-art-5eb1d868c4f244ba96282ed74008bbc6
institution Kabale University
issn 1551-0018
language English
publishDate 2018-05-01
publisher AIMS Press
record_format Article
series Mathematical Biosciences and Engineering
spelling doaj-art-5eb1d868c4f244ba96282ed74008bbc62025-01-24T02:40:50ZengAIMS PressMathematical Biosciences and Engineering1551-00182018-05-0115373976410.3934/mbe.2018033Dynamics of a Filippov epidemic model with limited hospital bedsAili WangYanni XiaoHuaiping ZhuA Filippov epidemic model is proposed to explore the impact of capacity and limited resources of public health system on the control of epidemic diseases. The number of infected cases is chosen as an index to represent a threshold policy, that is, the capacity dependent treatment policy is implemented when the case number exceeds a critical level, and constant treatment rate is adopted otherwise. The proposed Filippov model exhibits various local sliding bifurcations, including boundary focus or node bifurcation, boundary saddle bifurcation and boundary saddle-node bifurcation, and global sliding bifurcations, including grazing bifurcation and sliding homoclinic bifurcation to pseudo-saddle. The impact of some key parameters including the threshold level on disease control is examined by numerical analysis. Our results suggest that strengthening the basic medical conditions, i.e. increasing the minimum treatment ratio, or enlarging the input of medical resources, i.e. increasing HBPR (i.e. hospital bed-population ratio) as well as the possibility and level of maximum treatment ratio, can help to contain the case number at a relatively low level when the basic reproduction number $R_0 \gt 1$. If $R_0 \lt 1$, implementing these strategies can help in eradicating the disease although the disease cannot always be eradicated due to the occurring of backward bifurcation in the system.https://www.aimspress.com/article/doi/10.3934/mbe.2018033filippov systemlimited hospital bedssliding mode dynamicspseudo-equilibriumthreshold policysliding bifurcation
spellingShingle Aili Wang
Yanni Xiao
Huaiping Zhu
Dynamics of a Filippov epidemic model with limited hospital beds
Mathematical Biosciences and Engineering
filippov system
limited hospital beds
sliding mode dynamics
pseudo-equilibrium
threshold policy
sliding bifurcation
title Dynamics of a Filippov epidemic model with limited hospital beds
title_full Dynamics of a Filippov epidemic model with limited hospital beds
title_fullStr Dynamics of a Filippov epidemic model with limited hospital beds
title_full_unstemmed Dynamics of a Filippov epidemic model with limited hospital beds
title_short Dynamics of a Filippov epidemic model with limited hospital beds
title_sort dynamics of a filippov epidemic model with limited hospital beds
topic filippov system
limited hospital beds
sliding mode dynamics
pseudo-equilibrium
threshold policy
sliding bifurcation
url https://www.aimspress.com/article/doi/10.3934/mbe.2018033
work_keys_str_mv AT ailiwang dynamicsofafilippovepidemicmodelwithlimitedhospitalbeds
AT yannixiao dynamicsofafilippovepidemicmodelwithlimitedhospitalbeds
AT huaipingzhu dynamicsofafilippovepidemicmodelwithlimitedhospitalbeds