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电子烟对戒烟效果的定性与敏感性分析

Qualitative and Sensitivity Analysis of the Effect of Electronic Cigarettes on Smoking Cessation.

作者信息

Jung Jae Hun, Park Anna, Jung Il Hyo

机构信息

Department of Mathematics, Pusan National University, Busan 46241, Republic of Korea.

出版信息

Comput Math Methods Med. 2018 Aug 15;2018:3738584. doi: 10.1155/2018/3738584. eCollection 2018.

DOI:10.1155/2018/3738584
PMID:30186362
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6114243/
Abstract

Recently, the role of the electronic cigarettes (e-cigarettes) in a way to reduce smoking is increasing. E-cigarettes are a device that delivers only the nicotine, and its use is considered less harmful to health compared with tobacco cigarettes. Smokers frequently make use of e-cigarettes as one of the nonsmoking aid devices. In this work, we propose a mathematical model to analyze the effect of e-cigarettes on smoking cessation. The stability and the bifurcation of the model have been discussed. The parameter estimations from the observed data are drawn, and using the parameters, a reasonable smoking model has been designed. Moreover, by considering the sensitivity results depending on the basic reproduction number , the effective strategies that reduce the smokers are investigated. Numerical simulations of the model show that e-cigarettes may somewhat diminish the numbers of smokers, but it does not reduce the number of quitters ultimately.

摘要

最近,电子烟在减少吸烟方面的作用日益增强。电子烟是一种仅输送尼古丁的装置,与烟草香烟相比,其使用被认为对健康危害较小。吸烟者经常将电子烟作为戒烟辅助设备之一。在这项工作中,我们提出了一个数学模型来分析电子烟对戒烟的影响。讨论了该模型的稳定性和分岔情况。根据观测数据进行了参数估计,并利用这些参数设计了一个合理的吸烟模型。此外,通过考虑依赖于基本再生数的敏感性结果,研究了减少吸烟者数量的有效策略。该模型的数值模拟表明,电子烟可能会在一定程度上减少吸烟者的数量,但最终并不能减少戒烟者的数量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/21cd0f8df4f4/CMMM2018-3738584.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/5730906511ce/CMMM2018-3738584.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/5026743d1195/CMMM2018-3738584.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/65b564c65ea8/CMMM2018-3738584.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/14a9e090f8a3/CMMM2018-3738584.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/e734d9cd1eb9/CMMM2018-3738584.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/c64e763ef722/CMMM2018-3738584.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/21cd0f8df4f4/CMMM2018-3738584.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/5730906511ce/CMMM2018-3738584.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/5026743d1195/CMMM2018-3738584.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/65b564c65ea8/CMMM2018-3738584.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/14a9e090f8a3/CMMM2018-3738584.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/e734d9cd1eb9/CMMM2018-3738584.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/c64e763ef722/CMMM2018-3738584.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/932b/6114243/21cd0f8df4f4/CMMM2018-3738584.007.jpg

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