Skip to main content
CenXiv.org
This website is in trial operation, support us!
We gratefully acknowledge support from all contributors.
Contribute
Donate
cenxiv logo > q-bio > arXiv:2106.10313

Help | Advanced Search

Quantitative Biology > Populations and Evolution

arXiv:2106.10313 (q-bio)
[Submitted on 18 Jun 2021 ]

Title: Identifying Mitigation Strategies for COVID-19 Superspreading on Flights using Models that Account for Passenger Movement

Title: 使用考虑乘客移动的模型识别航班上新冠超级传播的缓解策略

Authors:Sirish Namilae, Yuxuan Wu, Anuj Mubayi, Ashok Srinivasan, Matthew Scotch
Abstract: Despite commercial airlines mandating masks, there have been multiple documented events of COVID-19 superspreading on flights. We used available data from three flights, including cabin layout and seat locations of infected and uninfected passengers, to suggest interventions to mitigate COVID-19 superspreading events during air travel. Specifically, we studied: 1) London to Hanoi with 201 passengers, including 13 secondary infections among passengers; 2) Singapore to Hangzhou with 321 passengers, including 12 to 14 secondary infections; 3) a non-superspreading event on a private jet in Japan with 9 passengers and no secondary infections. We show that inclusion of passenger movement better explains the infection spread patterns than conventional models do. We also found that FFP2/N95 mask usage would have reduced infection by 95-100%, while cloth masks would have reduced it by only 40-80%. This suggests the need for more stringent guidelines to reduce aviation-related superspreading events of COVID-19.
Abstract: 尽管商业航空公司要求佩戴口罩,但已有多个记录在案的事件表明,在航班上发生了新冠病毒超级传播。 我们使用了三架航班的可用数据,包括客舱布局和感染乘客与未感染乘客的座位位置,以提出干预措施,以减轻航空旅行中的新冠病毒超级传播事件。 具体来说,我们研究了:1)伦敦至河内的航班,有201名乘客,其中13人出现次级感染; 2)新加坡至杭州的航班,有321名乘客,其中12至14人出现次级感染;3)日本一架私人喷气式飞机上的一次非超级传播事件,有9名乘客且没有次级感染。 我们表明,将乘客移动纳入考虑能比传统模型更好地解释感染传播模式。 我们还发现,使用FFP2/N95口罩可以将感染减少95-100%,而布料口罩仅能减少40-80%。 这表明需要更严格的指南来减少与航空相关的新冠病毒超级传播事件。
Subjects: Populations and Evolution (q-bio.PE) ; Physics and Society (physics.soc-ph); Quantitative Methods (q-bio.QM)
Cite as: arXiv:2106.10313 [q-bio.PE]
  (or arXiv:2106.10313v1 [q-bio.PE] for this version)
  https://doi.org/10.48550/arXiv.2106.10313
arXiv-issued DOI via DataCite

Submission history

From: Ashok Srinivasan [view email]
[v1] Fri, 18 Jun 2021 18:55:23 UTC (3,877 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled
  • View Chinese PDF
  • View PDF
  • Other Formats
license icon view license
Current browse context:
q-bio.PE
< prev   |   next >
new | recent | 2021-06
Change to browse by:
physics
physics.soc-ph
q-bio
q-bio.QM

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar
a export BibTeX citation Loading...

BibTeX formatted citation

×
Data provided by:

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender (What is IArxiv?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
  • About
  • Help
  • contact arXivClick here to contact arXiv Contact
  • subscribe to arXiv mailingsClick here to subscribe Subscribe
  • Copyright
  • Privacy Policy
  • Web Accessibility Assistance
  • arXiv Operational Status
    Get status notifications via email or slack

京ICP备2025123034号