IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v596y2022ics0378437122001315.html
   My bibliography  Save this article

Community-distributed compartmental models

Author

Listed:
  • Hernández, G.
  • Martín del Rey, A.

Abstract

A framework that allows the incorporation of community structure into epidemiological compartmental models has been developed. The models resulting from this process are compartmental models as well, which are related to the base models. This work includes an existence and uniqueness theorem, showing that, under certain conditions on the mobility, epidemiological models in which f(t,X) is continuous in time and Lipschitz continuous on the compartments induce unique community models; and a homogeneous mixing limit, showing that under high mobility conditions the base model is recovered in the global population. Applications of the SIR model and the impact of the community structure on the estimation of their effective parameters are discussed in detail. An open computational implementation of this framework is available to the scientific community. It allows modeling community distribution using mobility data, as shown with Spain data during the 2020 state of alarm.

Suggested Citation

  • Hernández, G. & Martín del Rey, A., 2022. "Community-distributed compartmental models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
  • Handle: RePEc:eee:phsmap:v:596:y:2022:i:c:s0378437122001315
    DOI: 10.1016/j.physa.2022.127092
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122001315
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2022.127092?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ding Chen, 2020. "On the Integrability of the SIR Epidemic Model with Vital Dynamics," Advances in Mathematical Physics, Hindawi, vol. 2020, pages 1-10, July.
    2. Wu, Xiaoyan & Liu, Zonghua, 2008. "How community structure influences epidemic spread in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 623-630.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2016. "Targeted revision: A learning-based approach for incremental community detection in dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 70-85.
    2. Kotnis, Bhushan & Kuri, Joy, 2016. "Cost effective campaigning in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 670-681.
    3. Gong Kai & Kang Li, 2018. "A New K-Shell Decomposition Method for Identifying Influential Spreaders of Epidemics on Community Networks," Journal of Systems Science and Information, De Gruyter, vol. 6(4), pages 366-375, August.
    4. González-Parra, Gilberto & Acedo, L. & Villanueva Micó, Rafael-J. & Arenas, Abraham J., 2010. "Modeling the social obesity epidemic with stochastic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3692-3701.
    5. Chakir, Yassine, 2023. "Global approximate solution of SIR epidemic model with constant vaccination strategy," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    6. Han, Dun & Sun, Mei & Li, Dandan, 2015. "Epidemic process on activity-driven modular networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 354-362.
    7. Tung Manh Ho & Hong Kong Nguyen-To & Thu-Trang Vuong & Quan-Hoang Vuong, 2017. "Social Network Sustainability Metrics: A Study of Co-authoring Behaviors in the Social Sciences, Using 2008-2017 Scopus Data for Vietnam," Working Papers CEB 17-027, ULB -- Universite Libre de Bruxelles.
    8. Tung Manh Ho & Hong Kong T. Nguyen & Thu-Trang Vuong & Quan-Hoang Vuong, 2017. "On the Sustainability of Co-Authoring Behaviors in Vietnamese Social Sciences: A Preliminary Analysis of Network Data," Sustainability, MDPI, vol. 9(11), pages 1-21, November.
    9. Colman, E.R. & Rodgers, G.J., 2013. "Complex scale-free networks with tunable power-law exponent and clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5501-5510.
    10. Chen, Peng & Qi, Mingze & Yan, Liang & Duan, Xiaojun, 2024. "Diffusion capacity analysis of complex network based on the cluster distribution," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    11. Guan, Yuan-Pan & You, Zhi-Qiang & Han, Xiao-Pu, 2016. "Reconstruction of social group networks from friendship networks using a tag-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 485-492.
    12. Jia, Peng & Liu, Jiayong & Fang, Yong & Liu, Liang & Liu, Luping, 2018. "Modeling and analyzing malware propagation in social networks with heterogeneous infection rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 240-254.
    13. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Qiu, Tian & Shi, Yong-Dong & Zhong, Chen-Yang, 2015. "Coupled effects of local movement and global interaction on contagion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 482-491.
    14. Medvedev, Alexey & Kertesz, Janos, 2017. "Empirical study of the role of the topology in spreading on communication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 12-19.
    15. Zhang, Ruixia & Li, Deyu, 2017. "Rumor propagation on networks with community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 375-385.
    16. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2015. "Epidemic spreading on complex networks with overlapping and non-overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 171-182.
    17. Prasha Shrestha & Arun Sathanur & Suraj Maharjan & Emily Saldanha & Dustin Arendt & Svitlana Volkova, 2020. "Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-28, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:596:y:2022:i:c:s0378437122001315. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.