Modelling the impact of precaution on disease dynamics and its evolution

In this paper, we introduce the notion of practically susceptible population , which is a fraction of the biologically susceptible population. Assuming that the fraction depends on the severity of the epidemic and the public’s level of precaution (as a response of the public to the epidemic), we pro...

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Veröffentlicht in:Journal of mathematical biology 2024-07, Vol.89 (1), p.1, Article 1
Hauptverfasser: Cheng, Tianyu, Zou, Xingfu
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description In this paper, we introduce the notion of practically susceptible population , which is a fraction of the biologically susceptible population. Assuming that the fraction depends on the severity of the epidemic and the public’s level of precaution (as a response of the public to the epidemic), we propose a general framework model with the response level evolving with the epidemic. We firstly verify the well-posedness and confirm the disease’s eventual vanishing for the framework model under the assumption that the basic reproduction number R 0 < 1 . For R 0 > 1 , we study how the behavioural response evolves with epidemics and how such an evolution impacts the disease dynamics. More specifically, when the precaution level is taken to be the instantaneous best response function in literature, we show that the endemic dynamic is convergence to the endemic equilibrium; while when the precaution level is the delayed best response , the endemic dynamic can be either convergence to the endemic equilibrium, or convergence to a positive periodic solution. Our derivation offers a justification/explanation for the best response used in some literature. By replacing “adopting the best response” with “adapting toward the best response”, we also explore the adaptive long-term dynamics.
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subjects Applications of Mathematics
Basic Reproduction Number - statistics & numerical data
Biological Evolution
Communicable Diseases - epidemiology
Communicable Diseases - transmission
Computer Simulation
Convergence
Disease Susceptibility - epidemiology
Epidemics
Epidemics - prevention & control
Epidemics - statistics & numerical data
Epidemiological Models
Evolution
Humans
Mathematical and Computational Biology
Mathematical Concepts
Mathematics
Mathematics and Statistics
Models, Biological
Response functions
title Modelling the impact of precaution on disease dynamics and its evolution
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