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 > physics > arXiv:2501.01395v1

Help | Advanced Search

Physics > Physics and Society

arXiv:2501.01395v1 (physics)
[Submitted on 2 Jan 2025 ]

Title: Impact of inter-city interactions on disease scaling

Title: 城市间相互作用对疾病规模的影响

Authors:Nathalia A. Loureiro, Camilo R. Neto, Jack Sutton, Matjaz Perc, Haroldo V. Ribeiro
Abstract: Inter-city interactions are critical for the transmission of infectious diseases, yet their effects on the scaling of disease cases remain largely underexplored. Here, we use the commuting network as a proxy for inter-city interactions, integrating it with a general scaling framework to describe the incidence of seven infectious diseases across Brazilian cities as a function of population size and the number of commuters. Our models significantly outperform traditional urban scaling approaches, revealing that the relationship between disease cases and a combination of population and commuters varies across diseases and is influenced by both factors. Although most cities exhibit a less-than-proportional increase in disease cases with changes in population and commuters, more-than-proportional responses are also observed across all diseases. Notably, in some small and isolated cities, proportional rises in population and commuters correlate with a reduction in disease cases. These findings suggest that such towns may experience improved health outcomes and socioeconomic conditions as they grow and become more connected. However, as growth and connectivity continue, these gains diminish, eventually giving way to challenges typical of larger urban areas - such as socioeconomic inequality and overcrowding - that facilitate the spread of infectious diseases. Our study underscores the interconnected roles of population size and commuter dynamics in disease incidence while highlighting that changes in population size exert a greater influence on disease cases than variations in the number of commuters.
Abstract: 城市间互动对于传染病的传播至关重要,但它们对疾病病例规模的影响仍大多未被深入研究。 在这里,我们使用通勤网络作为城市间互动的代理,将其与一般的规模框架相结合,以人口规模和通勤人数为函数,描述巴西城市中七种传染病的发生率。 我们的模型显著优于传统的城市规模方法,揭示了疾病病例与人口和通勤者组合之间的关系因疾病而异,并受到这两个因素的影响。 尽管大多数城市在人口和通勤者变化时表现出疾病病例的非比例增长,但在所有疾病中也观察到了超比例反应。 值得注意的是,在一些小型和孤立的城市中,人口和通勤者的比例增加与疾病病例的减少相关。 这些发现表明,随着这些城镇的增长和连接性的增强,它们可能会经历更好的健康结果和社会经济状况。 然而,随着增长和连通性的持续,这些收益会减少,最终让位于大型城市常见的挑战——如社会经济不平等和拥挤——这些因素会促进传染病的传播。 我们的研究强调了人口规模和通勤动态在疾病发生中的相互关联作用,同时指出人口规模的变化对疾病病例的影响大于通勤人数变化的影响。
Comments: 13 pages, 6 figures, supplementary information; accepted for publication in Scientific Reports
Subjects: Physics and Society (physics.soc-ph) ; Populations and Evolution (q-bio.PE)
Cite as: arXiv:2501.01395 [physics.soc-ph]
  (or arXiv:2501.01395v1 [physics.soc-ph] for this version)
  https://doi.org/10.48550/arXiv.2501.01395
arXiv-issued DOI via DataCite
Journal reference: Sci. Rep. 15, 498 (2025)
Related DOI: https://doi.org/10.1038/s41598-024-84252-z
DOI(s) linking to related resources

Submission history

From: Haroldo Ribeiro [view email]
[v1] Thu, 2 Jan 2025 18:14:24 UTC (3,688 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled
  • View Chinese PDF
  • View PDF
  • HTML (experimental)
  • TeX Source
view license
Current browse context:
physics.soc-ph
< prev   |   next >
new | recent | 2025-01
Change to browse by:
physics
q-bio
q-bio.PE

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