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Published in: BMC Infectious Diseases 1/2021

Open Access 01-12-2021 | Coronavirus | Research

The effect of self-limiting on the prevention and control of the diffuse COVID-19 epidemic with delayed and temporal-spatial heterogeneous

Authors: Cheng-Cheng Zhu, Jiang Zhu

Published in: BMC Infectious Diseases | Issue 1/2021

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Abstract

Background

The global spread of the novel coronavirus pneumonia is still continuing, and a new round of more serious outbreaks has even begun in some countries. In this context, this paper studies the dynamics of a type of delayed reaction-diffusion novel coronavirus pneumonia model with relapse and self-limiting treatment in a temporal-spatial heterogeneous environment.

Methods

First, focus on the self-limiting characteristics of COVID-19, incorporate the relapse and self-limiting treatment factors into the diffusion model, and study the influence of self-limiting treatment on the diffusion of the epidemic. Second, because the traditional Lyapunov stability method is difficult to determine the spread of the epidemic with relapse and self-limiting treatment, we introduce a completely different method, relying on the existence conditions of the exponential attractor of our newly established in the infinite-dimensional dynamic system to determine the diffusion of novel coronavirus pneumonia. Third, relapse and self-limiting treatment have led to a change in the structure of the delayed diffusion COVID-19 model, and the traditional basic reproduction number \(R_0\) no longer has threshold characteristics. With the help of the Krein-Rutman theorem and the eigenvalue method, we studied the threshold characteristics of the principal eigenvalue and found that it can be used as a new threshold to describe the diffusion of the epidemic.

Results

Our results prove that the principal eigenvalue \(\uplambda ^{*}\) of the delayed reaction-diffusion COVID-19 system with relapse and self-limiting treatment can replace the basic reproduction number \(R_0\) to describe the threshold effect of disease transmission. Combine with the latest official data and the prevention and control strategies, some numerical simulations on the stability and global exponential attractiveness of the diffusion of the COVID-19 epidemic in China and the USA are given.

Conclusions

Through the comparison of numerical simulations, we find that self-limiting treatment can significantly promote the prevention and control of the epidemic. And if the free activities of asymptomatic infected persons are not restricted, it will seriously hinder the progress of epidemic prevention and control.
Literature
1.
go back to reference Algehyne EA, Ru D. On global dynamics of COVID-19 by using SQIR type model under non-linear saturatedincidence rate. Alex Eng J. 2021; 60: 393–399.CrossRef Algehyne EA, Ru D. On global dynamics of COVID-19 by using SQIR type model under non-linear saturatedincidence rate. Alex Eng J. 2021; 60: 393–399.CrossRef
2.
go back to reference Amaro JE, Dudouet J, Orce JN. Global analysis of the COVID-19 pandemic using simple epidemiological models. Appl Math Model. 2020;90:995–1008.CrossRef Amaro JE, Dudouet J, Orce JN. Global analysis of the COVID-19 pandemic using simple epidemiological models. Appl Math Model. 2020;90:995–1008.CrossRef
3.
go back to reference Appadu AR, Kelil AS, Tijani YO. Comparison of some forecasting methods for COVID-19. Alex Eng J. 2021;60:1565–89.CrossRef Appadu AR, Kelil AS, Tijani YO. Comparison of some forecasting methods for COVID-19. Alex Eng J. 2021;60:1565–89.CrossRef
4.
go back to reference Bentout S, Tridane A, Djilali S, Touaoula TM, Bentout S, Tridane A, Djilali S, Touaoula TM. Age-structured modeling of COVID-19 epidemic in the USA, UAE and Algeria. Alex Eng J. 2021;60:401–11.CrossRef Bentout S, Tridane A, Djilali S, Touaoula TM, Bentout S, Tridane A, Djilali S, Touaoula TM. Age-structured modeling of COVID-19 epidemic in the USA, UAE and Algeria. Alex Eng J. 2021;60:401–11.CrossRef
5.
go back to reference Çakan S. Dynamic analysis of a mathematical model with health care capacity for COVID-19 pandemic. Chaos Solitons Fractals. 2020;139:110033.CrossRef Çakan S. Dynamic analysis of a mathematical model with health care capacity for COVID-19 pandemic. Chaos Solitons Fractals. 2020;139:110033.CrossRef
6.
go back to reference Cooper I, Mondal A, Antonopoulos CG. A SIR model assumption for the spread of COVID-19 in different communities. Chaos Solitons Fractals. 2020;139:110057.CrossRef Cooper I, Mondal A, Antonopoulos CG. A SIR model assumption for the spread of COVID-19 in different communities. Chaos Solitons Fractals. 2020;139:110057.CrossRef
7.
go back to reference Cooper I, Mondal A, Antonopoulos CG. Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic. Chaos Solitons Fractals. 2020;139:110298.CrossRef Cooper I, Mondal A, Antonopoulos CG. Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic. Chaos Solitons Fractals. 2020;139:110298.CrossRef
10.
go back to reference Das A, Dhar A, Goyal S, Kundu A, Pandey S. COVID-19: analytic results for a modified SEIR model and comparison of different intervention strategies. Chaos Solitons Fractals. 2021;144:110595.CrossRef Das A, Dhar A, Goyal S, Kundu A, Pandey S. COVID-19: analytic results for a modified SEIR model and comparison of different intervention strategies. Chaos Solitons Fractals. 2021;144:110595.CrossRef
11.
go back to reference Le D. Dissipativity and global attractors for a class of quasilinear parabolic systems. Commun Partial Differ Equ. 1997;22:413–33.CrossRef Le D. Dissipativity and global attractors for a class of quasilinear parabolic systems. Commun Partial Differ Equ. 1997;22:413–33.CrossRef
12.
go back to reference Ma T, Wang S. Phase transition dynamics. Berlin: Springer Science+Business Media, LLC; 2014.CrossRef Ma T, Wang S. Phase transition dynamics. Berlin: Springer Science+Business Media, LLC; 2014.CrossRef
14.
go back to reference Paul A, Reja S, Kundu S, Bhattacharya S. COVID-19 pandemic models revisited with a new proposal: plenty of epidemiological models outcast the simple population dynamics solution. Chaos Solitons Fractals. 2021;144:110697.CrossRef Paul A, Reja S, Kundu S, Bhattacharya S. COVID-19 pandemic models revisited with a new proposal: plenty of epidemiological models outcast the simple population dynamics solution. Chaos Solitons Fractals. 2021;144:110697.CrossRef
15.
go back to reference Shahzad M, Abdel-Aty A, Attia RAM, Khoshnaw SHA, Aldila D, Ali M, Sultan F. Dynamics models for identifying the key transmission parameters of the COVID-19 disease. Alex Eng J. 2021;60:757–65.CrossRef Shahzad M, Abdel-Aty A, Attia RAM, Khoshnaw SHA, Aldila D, Ali M, Sultan F. Dynamics models for identifying the key transmission parameters of the COVID-19 disease. Alex Eng J. 2021;60:757–65.CrossRef
16.
go back to reference Thieme HR, Zhao XQ. A non-local delayed and diffusive predator-prey model. Nonlinear Anal Real World Appl. 2001;2:145–60.CrossRef Thieme HR, Zhao XQ. A non-local delayed and diffusive predator-prey model. Nonlinear Anal Real World Appl. 2001;2:145–60.CrossRef
17.
go back to reference Vrabie II. Co semigroups and application. New York: Elsevier Science BV; 2003. Vrabie II. Co semigroups and application. New York: Elsevier Science BV; 2003.
18.
go back to reference Wang CY, Yang ZG. Time-delay reaction diffusion equation and the methods of upper and lower solution. Beijing: Science Press; 2013. Wang CY, Yang ZG. Time-delay reaction diffusion equation and the methods of upper and lower solution. Beijing: Science Press; 2013.
20.
go back to reference Wu J. Theory and Applications of Partial Functional Differential Equations. New York: applied mathematical sciences; 1996. Wu J. Theory and Applications of Partial Functional Differential Equations. New York: applied mathematical sciences; 1996.
21.
go back to reference Zhu CC, Zhu J, Liu XL. Influence of spatial heterogeneous environment on long-term dynamics of a reaction-diffusion SVIR epidemic model with relapse. Math Biosci Eng. 2019;16:5897–922.CrossRef Zhu CC, Zhu J, Liu XL. Influence of spatial heterogeneous environment on long-term dynamics of a reaction-diffusion SVIR epidemic model with relapse. Math Biosci Eng. 2019;16:5897–922.CrossRef
22.
go back to reference Zhu CC, Zhu J. Spread trend of COVID-19 epidemic outbreak in China: using exponential attractor method in a spatial heterogeneous SEIQR model. Math Biosci Eng. 2020;17:3062–87.CrossRef Zhu CC, Zhu J. Spread trend of COVID-19 epidemic outbreak in China: using exponential attractor method in a spatial heterogeneous SEIQR model. Math Biosci Eng. 2020;17:3062–87.CrossRef
23.
go back to reference Zhu CC, Zhu J. Dynamic analysis of a delayed COVID-19 epidemic with home quarantine in temporal-spatial heterogeneous via global exponential attractor method. Chaos Solitons Fractals. 2021;143:110546.CrossRef Zhu CC, Zhu J. Dynamic analysis of a delayed COVID-19 epidemic with home quarantine in temporal-spatial heterogeneous via global exponential attractor method. Chaos Solitons Fractals. 2021;143:110546.CrossRef
Metadata
Title
The effect of self-limiting on the prevention and control of the diffuse COVID-19 epidemic with delayed and temporal-spatial heterogeneous
Authors
Cheng-Cheng Zhu
Jiang Zhu
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Infectious Diseases / Issue 1/2021
Electronic ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-021-06670-y

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