COVID-19传播的随机数学模型:一种新的流行病学方法。

IF 0.8 4区 数学 Q4 BIOLOGY
Ayman Mourad, Fatima Mroue, Zahraa Taha
{"title":"COVID-19传播的随机数学模型:一种新的流行病学方法。","authors":"Ayman Mourad,&nbsp;Fatima Mroue,&nbsp;Zahraa Taha","doi":"10.1093/imammb/dqab019","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, three stochastic mathematical models are developed for the spread of the coronavirus disease (COVID-19). These models take into account the known special characteristics of this disease such as the existence of infectious undetected cases and the different social and infectiousness conditions of infected people. In particular, they include a novel approach that considers the social structure, the fraction of detected cases over the real total infected cases, the influx of undetected infected people from outside the borders, as well as contact-tracing and quarantine period for travellers. Two of these models are discrete time-discrete state space models (one is simplified and the other is complete) while the third one is a continuous time-continuous state space stochastic integro-differential model obtained by a formal passing to the limit from the proposed simplified discrete model. From a numerical point of view, the particular case of Lebanon has been studied and its reported data have been used to estimate the complete discrete model parameters, which can be of interest in estimating the spread of COVID-19 in other countries. The obtained simulation results have shown a good agreement with the reported data. Moreover, a parameters' analysis is presented in order to better understand the role of some of the parameters. This may help policy makers in deciding on different social distancing measures.</p>","PeriodicalId":49863,"journal":{"name":"Mathematical Medicine and Biology-A Journal of the Ima","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2022-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Stochastic mathematical models for the spread of COVID-19: a novel epidemiological approach.\",\"authors\":\"Ayman Mourad,&nbsp;Fatima Mroue,&nbsp;Zahraa Taha\",\"doi\":\"10.1093/imammb/dqab019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this paper, three stochastic mathematical models are developed for the spread of the coronavirus disease (COVID-19). These models take into account the known special characteristics of this disease such as the existence of infectious undetected cases and the different social and infectiousness conditions of infected people. In particular, they include a novel approach that considers the social structure, the fraction of detected cases over the real total infected cases, the influx of undetected infected people from outside the borders, as well as contact-tracing and quarantine period for travellers. Two of these models are discrete time-discrete state space models (one is simplified and the other is complete) while the third one is a continuous time-continuous state space stochastic integro-differential model obtained by a formal passing to the limit from the proposed simplified discrete model. From a numerical point of view, the particular case of Lebanon has been studied and its reported data have been used to estimate the complete discrete model parameters, which can be of interest in estimating the spread of COVID-19 in other countries. The obtained simulation results have shown a good agreement with the reported data. Moreover, a parameters' analysis is presented in order to better understand the role of some of the parameters. This may help policy makers in deciding on different social distancing measures.</p>\",\"PeriodicalId\":49863,\"journal\":{\"name\":\"Mathematical Medicine and Biology-A Journal of the Ima\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematical Medicine and Biology-A Journal of the Ima\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/imammb/dqab019\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Medicine and Biology-A Journal of the Ima","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/imammb/dqab019","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 4

摘要

本文建立了冠状病毒病(COVID-19)传播的三个随机数学模型。这些模型考虑到这种疾病已知的特点,例如存在未被发现的传染性病例以及受感染者的不同社会和传染性条件。特别是,它们包括一种新方法,该方法考虑了社会结构、发现病例占实际感染病例总数的比例、未发现的感染者从境外涌入以及接触者追踪和旅行者隔离期。其中两个模型是离散时间-离散状态空间模型(一个是简化的,另一个是完全的),第三个模型是由所提出的简化离散模型通过形式传递到极限得到的连续时间-连续状态空间随机积分-微分模型。从数值角度来看,研究了黎巴嫩的具体情况,并使用其报告的数据来估计完整的离散模型参数,这可能有助于估计COVID-19在其他国家的传播情况。仿真结果与文献数据吻合较好。此外,为了更好地理解某些参数的作用,还进行了参数分析。这可能有助于决策者决定不同的社会距离措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic mathematical models for the spread of COVID-19: a novel epidemiological approach.

In this paper, three stochastic mathematical models are developed for the spread of the coronavirus disease (COVID-19). These models take into account the known special characteristics of this disease such as the existence of infectious undetected cases and the different social and infectiousness conditions of infected people. In particular, they include a novel approach that considers the social structure, the fraction of detected cases over the real total infected cases, the influx of undetected infected people from outside the borders, as well as contact-tracing and quarantine period for travellers. Two of these models are discrete time-discrete state space models (one is simplified and the other is complete) while the third one is a continuous time-continuous state space stochastic integro-differential model obtained by a formal passing to the limit from the proposed simplified discrete model. From a numerical point of view, the particular case of Lebanon has been studied and its reported data have been used to estimate the complete discrete model parameters, which can be of interest in estimating the spread of COVID-19 in other countries. The obtained simulation results have shown a good agreement with the reported data. Moreover, a parameters' analysis is presented in order to better understand the role of some of the parameters. This may help policy makers in deciding on different social distancing measures.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信