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Mathematical Biosciences and Engineering
Article . 2023 . Peer-reviewed
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Modeling and analysis of a stochastic giving-up-smoking model with quit smoking duration

Authors: Yajuan Guo; Zijian Liu; Yuanshun Tan; Yawei Liu;

Modeling and analysis of a stochastic giving-up-smoking model with quit smoking duration

Abstract

<abstract><p>Smoking has gradually become a very common behavior, and the related situation in different groups also presents different forms. Due to the differences of individual smoking cessation time and the interference of environmental factors in the spread of smoking behavior, we establish a stochastic giving up smoking model with quit-smoking duration. We also consider the saturated incidence rate. The total population is composed of potential smokers, smokers, quitters and removed. By using Itô's formula and constructing appropriate Lyapunov functions, we first ensure the existence of a unique global positive solution of the stochastic model. In addition, a threshold condition for extinction and permanence of smoking behavior is deduced. If the intensity of white noise is small, and $ \widetilde{\mathcal{R}}_0 &lt; 1 $, smokers will eventually become extinct. If $ \widetilde{\mathcal{R}}_0 &gt; 1 $, smoking will last. Then, the sufficient condition for the existence of a unique stationary distribution of the smoking phenomenon is studied as $ R_0^s &gt; 1 $. Finally, conclusions are explained by numerical simulations.</p></abstract>

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Keywords

stochastic giving-up-smoking model, Stochastic Processes, extinction, Smoking, QA1-939, Smoking Cessation, persistence, saturated incidence rate, TP248.13-248.65, Mathematics, stationary distribution, Biotechnology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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