• 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

建模拼车网络中的病毒传播。

Modelling virus spreading in ride-pooling networks.

机构信息

Department of Transport and Planning, Delft University of Technology, Delft, The Netherlands.

Department of Transport Systems, Cracow University of Technology, Cracow, Poland.

出版信息

Sci Rep. 2021 Mar 30;11(1):7201. doi: 10.1038/s41598-021-86704-2.

DOI:10.1038/s41598-021-86704-2
PMID:33785865
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8010089/
Abstract

Urban mobility needs alternative sustainable travel modes to keep our pandemic cities in motion. Ride-pooling, where a single vehicle is shared by more than one traveller, is not only appealing for mobility platforms and their travellers, but also for promoting the sustainability of urban mobility systems. Yet, the potential of ride-pooling rides to serve as a safe and effective alternative given the personal and public health risks considerations associated with the COVID-19 pandemic is hitherto unknown. To answer this, we combine epidemiological and behavioural shareability models to examine spreading among ride-pooling travellers, with an application for Amsterdam. Findings are at first sight devastating, with only few initially infected travellers needed to spread the virus to hundreds of ride-pooling users. Without intervention, ride-pooling system may substantially contribute to virus spreading. Notwithstanding, we identify an effective control measure allowing to halt the spreading before the outbreaks (at 50 instead of 800 infections) without sacrificing the efficiency achieved by pooling. Fixed matches among co-travellers disconnect the otherwise dense contact network, encapsulating the virus in small communities and preventing the outbreaks.

摘要

城市交通需要替代可持续的出行方式,以保持我们的“后疫情时代城市”继续运转。拼车,即一辆车由不止一名乘客共享,不仅对出行平台及其乘客具有吸引力,还有助于促进城市交通系统的可持续性。然而,鉴于与 COVID-19 大流行相关的个人和公共卫生风险,拼车出行作为一种安全有效的替代方式的潜力目前尚不清楚。为了回答这个问题,我们结合了流行病学和行为可共享性模型,以检查拼车旅行者之间的传播情况,并以阿姆斯特丹为例进行了应用。研究结果乍一看是毁灭性的,只需少数最初感染的旅行者就足以将病毒传播给数百名拼车用户。如果不进行干预,拼车系统可能会大大促进病毒的传播。尽管如此,我们还是确定了一种有效的控制措施,可以在疫情爆发之前(从 800 例感染减少到 50 例)阻止病毒传播,同时不会牺牲拼车带来的效率。同车旅行者之间的固定匹配会断开原本密集的接触网络,将病毒隔离在小社区中,从而防止疫情爆发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/c26502749904/41598_2021_86704_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/59a7964f79b1/41598_2021_86704_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/37404a13f2ef/41598_2021_86704_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/b433fd917b6c/41598_2021_86704_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/487b06d46bec/41598_2021_86704_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/98764dcc91f8/41598_2021_86704_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/c26502749904/41598_2021_86704_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/59a7964f79b1/41598_2021_86704_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/37404a13f2ef/41598_2021_86704_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/b433fd917b6c/41598_2021_86704_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/487b06d46bec/41598_2021_86704_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/98764dcc91f8/41598_2021_86704_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1a/8010089/c26502749904/41598_2021_86704_Fig6_HTML.jpg

相似文献

1
Modelling virus spreading in ride-pooling networks.建模拼车网络中的病毒传播。
Sci Rep. 2021 Mar 30;11(1):7201. doi: 10.1038/s41598-021-86704-2.
2
The shareability potential of ride-pooling under alternative spatial demand patterns.拼车在不同空间需求模式下的可共享潜力。
Transportmetr A Transp Sci. 2022 Nov 11;20(2):2140022. doi: 10.1080/23249935.2022.2140022. eCollection 2024.
3
Hyper pooling private trips into high occupancy transit like attractive shared rides.将私人出行过度集中到高载客量的公共交通中,比如吸引人的拼车服务。
NPJ Sustain Mobil Transp. 2024;1(1):6. doi: 10.1038/s44333-024-00006-4. Epub 2024 Sep 13.
4
Travel-related control measures to contain the COVID-19 pandemic: a rapid review.旅行相关的控制措施以遏制 COVID-19 大流行:快速综述。
Cochrane Database Syst Rev. 2020 Oct 5;10:CD013717. doi: 10.1002/14651858.CD013717.
5
International travel-related control measures to contain the COVID-19 pandemic: a rapid review.国际旅行相关防控措施以遏制 COVID-19 大流行:快速综述。
Cochrane Database Syst Rev. 2021 Mar 25;3(3):CD013717. doi: 10.1002/14651858.CD013717.pub2.
6
Universal screening for SARS-CoV-2 infection: a rapid review.SARS-CoV-2 感染的普遍筛查:快速综述。
Cochrane Database Syst Rev. 2020 Sep 15;9(9):CD013718. doi: 10.1002/14651858.CD013718.
7
What effect might border screening have on preventing the importation of COVID-19 compared with other infections? A modelling study.边境筛查对预防 COVID-19 与其他感染相比可能产生何种影响?建模研究。
Epidemiol Infect. 2021 Nov 4;149:e238. doi: 10.1017/S0950268821002387.
8
Two complementary model-based methods for calculating the risk of international spreading of a novel virus from the outbreak epicentre. The case of COVID-19.两种互补的基于模型的方法,用于计算新型病毒从疫情中心向国际传播的风险。以 COVID-19 为例。
Epidemiol Infect. 2020 Jun 9;148:e109. doi: 10.1017/S0950268820001223.
9
The impact of travelling on the COVID-19 infection cases in Germany.旅行对德国 COVID-19 感染病例的影响。
BMC Infect Dis. 2022 May 12;22(1):455. doi: 10.1186/s12879-022-07396-1.
10
Trade-offs between mobility restrictions and transmission of SARS-CoV-2.移动限制与 SARS-CoV-2 传播之间的权衡。
J R Soc Interface. 2021 Feb;18(175):20200936. doi: 10.1098/rsif.2020.0936. Epub 2021 Feb 24.

引用本文的文献

1
The Promotion of Preventive Behaviours in Healthcare Services: A Quantitative Study Among Older Adults in Spain.医疗保健服务中预防行为的促进:西班牙老年人的一项定量研究。
J Eval Clin Pract. 2025 Jun;31(4):e70108. doi: 10.1111/jep.70108.
2
Role of Time Scales in the Coupled Epidemic-Opinion Dynamics on Multiplex Networks.时间尺度在多重网络上耦合的疫情-舆论动态中的作用
Entropy (Basel). 2022 Jan 9;24(1):105. doi: 10.3390/e24010105.

本文引用的文献

1
COVID-19 and Public Transportation: Current Assessment, Prospects, and Research Needs.新冠疫情与公共交通:当前评估、前景及研究需求
J Public Trans. 2020 Jan;22(1):1-21. doi: 10.5038/2375-0901.22.1.1. Epub 2022 Sep 13.
2
What are the determinants of the willingness to share rides in pooled on-demand services?拼车按需服务中拼车意愿的决定因素有哪些?
Transportation (Amst). 2021;48(4):1733-1765. doi: 10.1007/s11116-020-10110-2. Epub 2020 May 14.
3
Scaling Laws of Collective Ride-Sharing Dynamics.集体拼车动力学的标度律。
Phys Rev Lett. 2020 Dec 11;125(24):248302. doi: 10.1103/PhysRevLett.125.248302.
4
Spatial interactions in urban scaling laws.城市标度律中的空间相互作用。
PLoS One. 2020 Dec 7;15(12):e0243390. doi: 10.1371/journal.pone.0243390. eCollection 2020.
5
Near-real-time monitoring of global CO emissions reveals the effects of the COVID-19 pandemic.近实时全球 CO 排放监测揭示了 COVID-19 大流行的影响。
Nat Commun. 2020 Oct 14;11(1):5172. doi: 10.1038/s41467-020-18922-7.
6
A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic.意大利的一个网络模型显示,间歇性的区域性策略可以缓解 COVID-19 疫情。
Nat Commun. 2020 Oct 9;11(1):5106. doi: 10.1038/s41467-020-18827-5.
7
Developing infectious disease surveillance systems.开发传染病监测系统。
Nat Commun. 2020 Sep 30;11(1):4962. doi: 10.1038/s41467-020-18798-7.
8
Second wave COVID-19 pandemics in Europe: a temporal playbook.欧洲的第二波 COVID-19 大流行:时间安排手册。
Sci Rep. 2020 Sep 23;10(1):15514. doi: 10.1038/s41598-020-72611-5.
9
Estimation of the shared mobility demand based on the daily regularity of the urban mobility and the similarity of individual trips.基于城市出行的日常规律性和个体出行的相似性估算共享出行需求。
PLoS One. 2020 Sep 17;15(9):e0238143. doi: 10.1371/journal.pone.0238143. eCollection 2020.
10
Analysis of the outbreak of COVID-19 in Japan by SIQR model.基于SIQR模型对日本新冠肺炎疫情的分析。
Infect Dis Model. 2020;5:691-698. doi: 10.1016/j.idm.2020.08.013. Epub 2020 Sep 11.