IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v355y2019icp161-172.html
   My bibliography  Save this article

Disease persistence and serotype coexistence: An expected feature of human mobility

Author

Listed:
  • Vilches, T.N.
  • Esteva, L.
  • Ferreira, C.P.

Abstract

We present a stochastic model that mimics dengue transmission when two serotypes of the virus are circulating in a human population connected by a Watts–Strogatz complex network that reflects social interactions (human mobility). The influence of the number of connections per vertex and the network topology on the epidemics is analyzed. The first relation displays a sigmoid curve, while the second one shows that the increase in the network disorder facilitates disease spreading and serotype coexistence. The disease transmission thresholds for three network topology (regular, small-world and random) were obtained. Numerical results show that when coexistence of serotypes is a feasible outcome, negative correlation between the temporal evolution of the two serotype is more likely to occur. This could explain serotype dominance in consecutive epidemics.

Suggested Citation

  • Vilches, T.N. & Esteva, L. & Ferreira, C.P., 2019. "Disease persistence and serotype coexistence: An expected feature of human mobility," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 161-172.
  • Handle: RePEc:eee:apmaco:v:355:y:2019:i:c:p:161-172
    DOI: 10.1016/j.amc.2019.02.061
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300319301651
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2019.02.061?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. Cristopher Moore & M. E. J. Newman, 2000. "Epidemics and Percolation in Small-World Networks," Working Papers 00-01-002, Santa Fe Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nie, Wei-Peng & Cai, Shi-Min & Zhao, Zhi-Dan & Zhou, Tao, 2022. "Revealing mobility pattern of taxi movements with its travel trajectory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).

    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. Ganjeh-Ghazvini, Mostafa & Masihi, Mohsen & Ghaedi, Mojtaba, 2014. "Random walk–percolation-based modeling of two-phase flow in porous media: Breakthrough time and net to gross ratio estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 214-221.
    2. Pan, Ya-Nan & Lou, Jing-Jing & Han, Xiao-Pu, 2014. "Outbreak patterns of the novel avian influenza (H7N9)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 265-270.
    3. Greg Morrison & L Mahadevan, 2012. "Discovering Communities through Friendship," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    4. Floortje Alkemade & Carolina Castaldi, 2005. "Strategies for the Diffusion of Innovations on Social Networks," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 3-23, February.
    5. Qin, Yang & Zhong, Xiaoxiong & Jiang, Hao & Ye, Yibin, 2015. "An environment aware epidemic spreading model and immune strategy in complex networks," Applied Mathematics and Computation, Elsevier, vol. 261(C), pages 206-215.
    6. Velarde, Carlos & Robledo, Alberto, 2021. "Statistical mechanical model for growth and spread of contagions under gauged population confinement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    7. I. Vieira & R. Cheng & P. Harper & V. Senna, 2010. "Small world network models of the dynamics of HIV infection," Annals of Operations Research, Springer, vol. 178(1), pages 173-200, July.
    8. Sáenz-Royo, Carlos & Lozano-Rojo, Álvaro, 2023. "Authoritarianism versus participation in innovation decisions," Technovation, Elsevier, vol. 124(C).
    9. Tomovski, Igor & Kocarev, Ljupčo, 2015. "Network topology inference from infection statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 272-285.
    10. Li, Xun & Cao, Lang, 2016. "Diffusion processes of fragmentary information on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 624-634.
    11. Foti, Nicholas J. & Pauls, Scott & Rockmore, Daniel N., 2013. "Stability of the World Trade Web over time – An extinction analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1889-1910.
    12. Kumar, Ajay & Swarnakar, Pradip & Jaiswal, Kamya & Kurele, Ritika, 2020. "SMIR model for controlling the spread of information in social networking sites," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    13. Yang, Dingda & Liao, Xiangwen & Shen, Huawei & Cheng, Xueqi & Chen, Guolong, 2018. "Modeling the reemergence of information diffusion in social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1493-1500.
    14. Ramos, A.B.M. & Schimit, P.H.T., 2019. "Disease spreading on populations structured by groups," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 265-273.
    15. Ball, Frank & Neal, Peter, 2003. "The great circle epidemic model," Stochastic Processes and their Applications, Elsevier, vol. 107(2), pages 233-268, October.
    16. Mahendra Piraveenan & Mikhail Prokopenko & Liaquat Hossain, 2013. "Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-14, January.
    17. Zhao Zhang & Wen Xu & Weili Wu & Ding-Zhu Du, 2017. "A novel approach for detecting multiple rumor sources in networks with partial observations," Journal of Combinatorial Optimization, Springer, vol. 33(1), pages 132-146, January.
    18. Dassisti, M. & Carnimeo, L., 2013. "A small-world methodology of analysis of interchange energy-networks: The European behaviour in the economical crisis," Energy Policy, Elsevier, vol. 63(C), pages 887-899.
    19. Yang, Yang & Sun, Peng Gang & Hu, Xia & Li, Zhou Jun, 2014. "Closed walks for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 397(C), pages 129-143.
    20. Caccioli, Fabio & Farmer, J. Doyne & Foti, Nick & Rockmore, Daniel, 2015. "Overlapping portfolios, contagion, and financial stability," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 50-63.

    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:apmaco:v:355:y:2019:i:c:p:161-172. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.