• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

一个用于研究印度新冠疫情的数学模型。

A mathematical model to study the COVID-19 pandemic in India.

作者信息

Tripathi Agraj, Tripathi Ram Naresh, Sharma Dileep

机构信息

Department of Basic Science and Humanities, Pranveer Singh Institute of Technology, Kanpur, Uttar Pradesh 209305 India.

Department of Mathematics, School of Basic and Applied Sciences, Harcourt Butler Technical University, Kanpur, Uttar Pradesh 208002 India.

出版信息

Model Earth Syst Environ. 2022;8(3):3047-3058. doi: 10.1007/s40808-021-01280-8. Epub 2021 Sep 23.

DOI:10.1007/s40808-021-01280-8
PMID:34580646
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8458050/
Abstract

In this paper, a compartmental model is proposed to study the dynamics of COVID-19 pandemic caused by the coronavirus SARS-CoV-2 and the role of media in controlling this ongoing infection. Model includes implementation of media awareness as a control measure to mitigate the spread of the disease. In the proposed model, we have divided the total human population into four sub-classes, namely susceptibles, asymtomatic infectives, aware susceptibles and symptomatic infectives (or Isolated infectives which are under treatment/hospitalized) incorporating classes representing cumulative density of virus and media alert. The important mathematical features of the model are thoroughly investigated. The endemic equilibrium is found to be locally asymptotically stable as well as non-linearly asymptotically stable with certain conditions. Numerical simulations are also carried out in support of the analytical results and to show the effects of certain key parameters.

摘要

本文提出了一个 compartmental 模型，以研究由冠状病毒 SARS-CoV-2 引起的 COVID-19 大流行的动态以及媒体在控制这种持续感染中的作用。该模型将媒体宣传作为一种控制措施来减轻疾病传播。在所提出的模型中，我们将总人口分为四个子类，即易感者、无症状感染者、有认知的易感者和有症状感染者（或正在接受治疗/住院的隔离感染者），并纳入了代表病毒累积密度和媒体警报的类别。对该模型的重要数学特征进行了深入研究。发现地方病平衡点在某些条件下是局部渐近稳定以及非线性渐近稳定的。还进行了数值模拟以支持分析结果并展示某些关键参数的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/13df1efda29e/40808_2021_1280_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/33b9e41ea9e8/40808_2021_1280_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/513a0f85de4b/40808_2021_1280_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/6c9bd62fda99/40808_2021_1280_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/77a1f05d68b0/40808_2021_1280_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/7428f10154b4/40808_2021_1280_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/f3f1a04d5748/40808_2021_1280_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/bfa73c6da161/40808_2021_1280_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/21864c12609f/40808_2021_1280_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/62b7885fc628/40808_2021_1280_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/c09338002de7/40808_2021_1280_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/e9df18e39730/40808_2021_1280_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/6b1ae92acf92/40808_2021_1280_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/b2cc4165e26a/40808_2021_1280_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/13df1efda29e/40808_2021_1280_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/33b9e41ea9e8/40808_2021_1280_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/513a0f85de4b/40808_2021_1280_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/6c9bd62fda99/40808_2021_1280_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/77a1f05d68b0/40808_2021_1280_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/7428f10154b4/40808_2021_1280_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/f3f1a04d5748/40808_2021_1280_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/bfa73c6da161/40808_2021_1280_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/21864c12609f/40808_2021_1280_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/62b7885fc628/40808_2021_1280_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/c09338002de7/40808_2021_1280_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/e9df18e39730/40808_2021_1280_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/6b1ae92acf92/40808_2021_1280_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/b2cc4165e26a/40808_2021_1280_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bce/8458050/13df1efda29e/40808_2021_1280_Fig14_HTML.jpg

相似文献

1
A mathematical model to study the COVID-19 pandemic in India.一个用于研究印度新冠疫情的数学模型。
Model Earth Syst Environ. 2022;8(3):3047-3058. doi: 10.1007/s40808-021-01280-8. Epub 2021 Sep 23.
2
Nonlinear dynamics of a time-delayed epidemic model with two explicit aware classes, saturated incidences, and treatment.具有两个明确知晓类、饱和发病率和治疗的时滞流行病模型的非线性动力学
Nonlinear Dyn. 2020;101(3):1693-1715. doi: 10.1007/s11071-020-05762-9. Epub 2020 Jul 4.
3
Modeling the effects of prosocial awareness on COVID-19 dynamics: Case studies on Colombia and India.模拟亲社会意识对新冠疫情动态的影响：哥伦比亚和印度的案例研究
Nonlinear Dyn. 2021;104(4):4681-4700. doi: 10.1007/s11071-021-06489-x. Epub 2021 May 1.
4
Mathematical Model and Analysis on the Impact of Awareness Campaign and Asymptomatic Human Immigrants in the Transmission of COVID-19.关于 COVID-19 传播中宣传活动和无症状人类移民影响的数学模型与分析。
Biomed Res Int. 2022 May 28;2022:6260262. doi: 10.1155/2022/6260262. eCollection 2022.
5
A Mathematical Model of COVID-19 Pandemic: A Case Study of Bangkok, Thailand.COVID-19 大流行的数学模型：泰国曼谷的案例研究。
Comput Math Methods Med. 2021 Mar 30;2021:6664483. doi: 10.1155/2021/6664483. eCollection 2021.
6
Unravelling the dynamics of the COVID-19 pandemic with the effect of vaccination, vertical transmission and hospitalization.揭示新冠疫情在疫苗接种、垂直传播和住院治疗影响下的动态变化。
Results Phys. 2022 Aug;39:105715. doi: 10.1016/j.rinp.2022.105715. Epub 2022 Jun 14.
7
Global stability of COVID-19 model involving the quarantine strategy and media coverage effects.涉及检疫策略和媒体报道影响的新冠疫情模型的全局稳定性
AIMS Public Health. 2020 Aug 3;7(3):587-605. doi: 10.3934/publichealth.2020047. eCollection 2020.
8
Mathematical assessment of the roles of age heterogeneity and vaccination on the dynamics and control of SARS-CoV-2.年龄异质性和疫苗接种对SARS-CoV-2动力学及控制作用的数学评估
Infect Dis Model. 2024 Apr 26;9(3):828-874. doi: 10.1016/j.idm.2024.04.007. eCollection 2024 Sep.
9
Future implications of COVID-19 through Mathematical modeling.通过数学建模探讨新冠疫情的未来影响。
Results Phys. 2022 Feb;33:105097. doi: 10.1016/j.rinp.2021.105097. Epub 2021 Dec 25.
10
Forecasting the daily and cumulative number of cases for the COVID-19 pandemic in India.预测印度 COVID-19 大流行的每日和累计病例数。
Chaos. 2020 Jul;30(7):071101. doi: 10.1063/5.0016240.

本文引用的文献

1
Operating room team safety and perioperative anesthetic management of patients with suspected or confirmed novel corona virus in resource limited settings: A systematic review.资源有限环境下疑似或确诊新型冠状病毒患者的手术室团队安全及围手术期麻醉管理：一项系统综述
Trends Anaesth Crit Care. 2020 Oct;34:14-22. doi: 10.1016/j.tacc.2020.06.011. Epub 2020 Jul 2.
2
Aye Corona! The contagion effects of being named Corona during the COVID-19 pandemic.哎呀，科罗娜！在新冠疫情期间被命名为科罗娜所产生的传染效应。
Financ Res Lett. 2021 Jan;38:101591. doi: 10.1016/j.frl.2020.101591. Epub 2020 May 20.
3
The extent of people's response to rumors and false news in light of the crisis of the Corona virus.
鉴于新冠病毒危机，人们对谣言和虚假新闻的反应程度。
Ann Med Psychol (Paris). 2020 Sep;178(7):684-689. doi: 10.1016/j.amp.2020.06.011. Epub 2020 Jun 25.
4
A SIR model assumption for the spread of COVID-19 in different communities.一种关于新冠病毒在不同社区传播的易感-感染-康复（SIR）模型假设。
Chaos Solitons Fractals. 2020 Oct;139:110057. doi: 10.1016/j.chaos.2020.110057. Epub 2020 Jun 28.
5
Modeling and forecasting the COVID-19 pandemic in India.印度新冠疫情的建模与预测
Chaos Solitons Fractals. 2020 Oct;139:110049. doi: 10.1016/j.chaos.2020.110049. Epub 2020 Jun 28.
6
A mathematical study on the spread of COVID-19 considering social distancing and rapid assessment: The case of Jakarta, Indonesia.一项考虑社交距离和快速评估的新冠肺炎传播数学研究：以印度尼西亚雅加达为例。
Chaos Solitons Fractals. 2020 Oct;139:110042. doi: 10.1016/j.chaos.2020.110042. Epub 2020 Jun 28.
7
Mathematical modelling on phase based transmissibility of Coronavirus.基于阶段的冠状病毒传播性的数学建模。
Infect Dis Model. 2020 Jun 30;5:375-385. doi: 10.1016/j.idm.2020.06.005. eCollection 2020.
8
Mathematical Model for Coronavirus Disease 2019 (COVID-19) Containing Isolation Class.含隔离类别的 2019 年冠状病毒病（COVID-19）数学模型
Biomed Res Int. 2020 Jun 25;2020:3452402. doi: 10.1155/2020/3452402. eCollection 2020.
9
Investigating the dynamics of COVID-19 pandemic in India under lockdown.调查印度在封锁措施下新冠疫情的动态。
Chaos Solitons Fractals. 2020 Sep;138:109988. doi: 10.1016/j.chaos.2020.109988. Epub 2020 Jun 10.
10
Novel Corona virus disease infection in Tunisia: Mathematical model and the impact of the quarantine strategy.突尼斯的新型冠状病毒病感染：数学模型与隔离策略的影响
Chaos Solitons Fractals. 2020 Sep;138:109969. doi: 10.1016/j.chaos.2020.109969. Epub 2020 Jun 10.