• 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

最佳疫苗接种和社交距离对新冠疫情的影响。

Impact of optimal vaccination and social distancing on COVID-19 pandemic.

作者信息

Saha Sangeeta, Samanta Guruprasad, Nieto Juan J

机构信息

Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah 711103, India.

Instituto de Matemáticas, Universidade de Santiago de Compostela, Santiago de Compostela 15782, Spain.

出版信息

Math Comput Simul. 2022 Oct;200:285-314. doi: 10.1016/j.matcom.2022.04.025. Epub 2022 Apr 30.

DOI:10.1016/j.matcom.2022.04.025
PMID:35531464
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9056068/
Abstract

The first COVID-19 case was reported at Wuhan in China at the end of December 2019 but till today the virus has caused millions of deaths worldwide. Governments of each country, observing the severity, took non-pharmaceutical interventions from the very beginning to break the chain of higher transmission. Fortunately, vaccines are available now in most countries and people are asked to take recommended vaccines as precautionary measures. In this work, an epidemiological model on COVID-19 is proposed where people from the susceptible and asymptomatically infected phase move to the vaccinated class after a full two-dose vaccination. The overall analysis says that the disease transmission rate from symptomatically infected people is most sensitive on the disease prevalence. Moreover, better disease control can be achieved by vaccination of the susceptible class. In the later part of the work, a corresponding optimal control problem is considered where maintaining social distancing and vaccination procedure change with time. The result says that even in absence of social distancing, only the vaccination to people can significantly reduce the overall infected population. From the analysis, it is observed that maintaining physical distancing and taking vaccines at an early stage decreases the infection level significantly in the environment by reducing the probability of becoming infected.

摘要

2019年12月底,中国武汉报告了首例新冠病毒病例,但截至目前,该病毒已在全球造成数百万人死亡。各国政府鉴于其严重性,从一开始就采取了非药物干预措施,以阻断更高传播链。幸运的是,现在大多数国家都有疫苗可供使用,人们被要求接种推荐的疫苗作为预防措施。在这项工作中,提出了一个关于新冠病毒的流行病学模型,处于易感和无症状感染阶段的人在完成两剂疫苗接种后进入接种疫苗类别。总体分析表明,有症状感染者的疾病传播率对疾病流行率最为敏感。此外,通过对易感人群进行疫苗接种可以实现更好的疾病控制。在工作的后期,考虑了一个相应的最优控制问题,其中保持社交距离和疫苗接种程序随时间变化。结果表明,即使没有社交距离,仅对人们进行疫苗接种也能显著减少总体感染人群。从分析中可以看出,保持身体距离并在早期接种疫苗,通过降低感染概率,可显著降低环境中的感染水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/52e5abfb4c46/gr24_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/c29d4c67d3ab/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/49805e0cdc9e/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/3c833d584d6a/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/79d6c3d0259b/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/f2d036981ceb/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/9b66f41bd2a3/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/d5690737e52e/gr7_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/d6bfc32d4f0b/gr8_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/f06343a6ecf4/gr9_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/4a14b857e874/gr10_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/824fb0a7845a/gr11_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/d1a7dad17e03/gr12_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/9c4bb0212fac/gr13_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/514e7b4dccb9/gr14_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/3257ff5b3b5b/gr15_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/6813b7e18c53/gr16_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/06f2c97485d6/gr17_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/5e894b4a3a11/gr18_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/32be48e749dc/gr19_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/216b04786ecd/gr20_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/04b1af36ef54/gr21_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/d9edaef6a573/gr22_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/c1b076c819cb/gr23_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/52e5abfb4c46/gr24_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/c29d4c67d3ab/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/49805e0cdc9e/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/3c833d584d6a/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/79d6c3d0259b/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/f2d036981ceb/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/9b66f41bd2a3/gr6_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/d5690737e52e/gr7_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/d6bfc32d4f0b/gr8_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/f06343a6ecf4/gr9_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/4a14b857e874/gr10_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/824fb0a7845a/gr11_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/d1a7dad17e03/gr12_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/9c4bb0212fac/gr13_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/514e7b4dccb9/gr14_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/3257ff5b3b5b/gr15_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/6813b7e18c53/gr16_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/06f2c97485d6/gr17_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/5e894b4a3a11/gr18_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/32be48e749dc/gr19_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/216b04786ecd/gr20_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/04b1af36ef54/gr21_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/d9edaef6a573/gr22_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/c1b076c819cb/gr23_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb39/9056068/52e5abfb4c46/gr24_lrg.jpg

相似文献

1
Impact of optimal vaccination and social distancing on COVID-19 pandemic.最佳疫苗接种和社交距离对新冠疫情的影响。
Math Comput Simul. 2022 Oct;200:285-314. doi: 10.1016/j.matcom.2022.04.025. Epub 2022 Apr 30.
2
Modelling the role of optimal social distancing on disease prevalence of COVID-19 epidemic.模拟最佳社交距离对新冠疫情疾病流行率的作用。
Int J Dyn Control. 2021;9(3):1053-1077. doi: 10.1007/s40435-020-00721-z. Epub 2020 Nov 9.
3
Tuberculosis结核病
4
The economic impact of COVID-19 interventions: A mathematical modeling approach.COVID-19 干预措施的经济影响:一种数学建模方法。
Front Public Health. 2022 Sep 12;10:993745. doi: 10.3389/fpubh.2022.993745. eCollection 2022.
5
Communicable disease pandemic: a simulation model based on community transmission and social distancing.传染病大流行:基于社区传播和社交距离的模拟模型
Soft comput. 2023;27(5):2717-2727. doi: 10.1007/s00500-021-06168-4. Epub 2021 Aug 31.
6
Modeling the effects of preventive measures and vaccination on the COVID-19 spread in Benin Republic with optimal control.运用最优控制方法模拟预防措施和疫苗接种对贝宁共和国新冠疫情传播的影响。
Results Phys. 2021 Dec;31:104969. doi: 10.1016/j.rinp.2021.104969. Epub 2021 Nov 16.
7
Nonlinear dynamics for the spread of pathogenesis of COVID-19 pandemic.COVID-19 大流行发病机制传播的非线性动力学。
J Infect Public Health. 2021 Jul;14(7):817-831. doi: 10.1016/j.jiph.2021.04.001. Epub 2021 Apr 20.
8
Optimal timing and effectiveness of COVID-19 outbreak responses in China: a modelling study.中国 COVID-19 疫情应对的最佳时机和效果:建模研究。
BMC Public Health. 2022 Apr 7;22(1):679. doi: 10.1186/s12889-022-12659-2.
9
Integrated vaccination and physical distancing interventions to prevent future COVID-19 waves in Chinese cities.综合疫苗接种和身体距离干预措施,以预防中国城市未来的 COVID-19 浪潮。
Nat Hum Behav. 2021 Jun;5(6):695-705. doi: 10.1038/s41562-021-01063-2. Epub 2021 Feb 18.
10
Optimal strategies of social distancing and vaccination against seasonal influenza.季节性流感的社交隔离和疫苗接种的最优策略。
Math Biosci Eng. 2013 Oct-Dec;10(5-6):1615-34. doi: 10.3934/mbe.2013.10.1615.

引用本文的文献

1
A network-based model to assess vaccination strategies for the COVID-19 pandemic by using Bayesian optimization.一种基于网络的模型,用于通过贝叶斯优化评估针对新冠疫情的疫苗接种策略。
Chaos Solitons Fractals. 2024 Apr;181. doi: 10.1016/j.chaos.2024.114695. Epub 2024 Mar 14.
2
Population Behavior Regarding the Use of Face Masks to Prevent the Transmission of Respiratory Infections: Lessons to Be Learned from the COVID-19 Pandemic.关于使用口罩预防呼吸道感染传播的人群行为:从新冠疫情中吸取的教训
Int J Environ Res Public Health. 2025 Jan 22;22(2):147. doi: 10.3390/ijerph22020147.
3
Beyond six feet: The collective behavior of social distancing.

本文引用的文献

1
Modeling Vaccine Efficacy for COVID-19 Outbreak in New York City.纽约市新冠疫情疫苗效力建模
Biology (Basel). 2022 Feb 22;11(3):345. doi: 10.3390/biology11030345.
2
COVID-19 underreporting and its impact on vaccination strategies.COVID-19 漏报及其对疫苗接种策略的影响。
BMC Infect Dis. 2021 Oct 28;21(1):1111. doi: 10.1186/s12879-021-06780-7.
3
The impact of COVID-19 vaccination delay: A data-driven modeling analysis for Chicago and New York City.**译文**:COVID-19 疫苗接种延迟的影响:基于数据的芝加哥和纽约市建模分析。
超越六英尺:社交距离的集体行为。
PLoS One. 2024 Sep 13;19(9):e0293489. doi: 10.1371/journal.pone.0293489. eCollection 2024.
4
On optimal control at the onset of a new viral outbreak.关于新病毒爆发初期的最优控制
Infect Dis Model. 2024 May 15;9(4):995-1006. doi: 10.1016/j.idm.2024.05.006. eCollection 2024 Dec.
5
Factors Affecting Adherence to Social Distancing among Adults Aged 19-44 Years: Insights from a Nationwide Survey during COVID-19 Pandemic.影响 19-44 岁成年人遵守社交距离的因素:COVID-19 大流行期间全国性调查的启示。
Medicina (Kaunas). 2024 May 17;60(5):827. doi: 10.3390/medicina60050827.
6
The relationship between compartment models and their stochastic counterparts: A comparative study with examples of the COVID-19 epidemic modeling.compartment模型与其随机对应模型之间的关系:以COVID-19疫情建模为例的比较研究
J Biomed Res. 2024 Mar 5;38(2):175-188. doi: 10.7555/JBR.37.20230137.
7
Risk factors for COVID-19 outbreaks in livestock slaughtering and processing facilities in Republic of Korea.韩国牲畜屠宰和加工设施中新冠疫情的风险因素。
Osong Public Health Res Perspect. 2023 Jun;14(3):207-218. doi: 10.24171/j.phrp.2023.0035. Epub 2023 Jun 8.
8
Study of optimal vaccination strategies for early COVID-19 pandemic using an age-structured mathematical model: A case study of the USA.基于年龄结构的数学模型对 COVID-19 早期大流行最优接种策略的研究:以美国为例。
Math Biosci Eng. 2023 Apr 19;20(6):10828-10865. doi: 10.3934/mbe.2023481.
9
Modeling the competitive transmission of the Omicron strain and Delta strain of COVID-19.新冠病毒奥密克戎毒株与德尔塔毒株的竞争性传播建模
J Math Anal Appl. 2023 Oct 15;526(2):127283. doi: 10.1016/j.jmaa.2023.127283. Epub 2023 Mar 31.
10
A time-delayed model for the spread of COVID-19 with vaccination.具有疫苗接种的 COVID-19 传播的时滞模型。
Sci Rep. 2022 Nov 13;12(1):19435. doi: 10.1038/s41598-022-23822-5.
Vaccine. 2021 Oct 1;39(41):6088-6094. doi: 10.1016/j.vaccine.2021.08.098. Epub 2021 Aug 31.
4
Will achieving herd immunity be a road to success to end the COVID-19 pandemic?实现群体免疫是否会成为终结 COVID-19 大流行的成功之路?
J Infect. 2021 Sep;83(3):381-412. doi: 10.1016/j.jinf.2021.06.007. Epub 2021 Jun 10.
5
Modeling the Epidemic Trend of the 2019 Novel Coronavirus Outbreak in China.中国2019新型冠状病毒疫情流行趋势建模
Innovation (Camb). 2020 Nov 25;1(3):100048. doi: 10.1016/j.xinn.2020.100048. Epub 2020 Sep 28.
6
Modelling the role of optimal social distancing on disease prevalence of COVID-19 epidemic.模拟最佳社交距离对新冠疫情疾病流行率的作用。
Int J Dyn Control. 2021;9(3):1053-1077. doi: 10.1007/s40435-020-00721-z. Epub 2020 Nov 9.
7
Epidemic model of COVID-19 outbreak by inducing behavioural response in population.通过引发人群行为反应构建的新冠疫情流行模型。
Nonlinear Dyn. 2020;102(1):455-487. doi: 10.1007/s11071-020-05896-w. Epub 2020 Aug 26.
8
Sex differential in COVID-19 mortality varies markedly by age.新冠病毒疾病(COVID-19)死亡率的性别差异在不同年龄段中有显著变化。
Lancet. 2020 Aug 22;396(10250):532-533. doi: 10.1016/S0140-6736(20)31748-7. Epub 2020 Aug 13.
9
A COVID-19 epidemic model with latency period.一种具有潜伏期的新冠疫情模型。
Infect Dis Model. 2020 Apr 28;5:323-337. doi: 10.1016/j.idm.2020.03.003. eCollection 2020.
10
Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan.基于武汉案例研究的新冠病毒传播动力学数学建模
Chaos Solitons Fractals. 2020 Jun;135:109846. doi: 10.1016/j.chaos.2020.109846. Epub 2020 Apr 27.