IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v77y2010i1p71-75.html
   My bibliography  Save this article

The impact of network clustering and assortativity on epidemic behaviour

Author

Listed:
  • Badham, Jennifer
  • Stocker, Rob

Abstract

Epidemic models have successfully included many aspects of the complex contact structure apparent in real-world populations. However, it is difficult to accommodate variations in the number of contacts, clustering coefficient and assortativity. Investigations of the relationship between these properties and epidemic behaviour have led to inconsistent conclusions and have not accounted for their interrelationship. In this study, simulation is used to estimate the impact of social network structure on the probability of an SIR (susceptible-infective-removed) epidemic occurring and, if it does, the final size. Increases in assortativity and clustering coefficient are associated with smaller epidemics and the impact is cumulative. Derived values of the basic reproduction ratio (R0) over networks with the highest property values are more than 20% lower than those derived from simulations with zero values of these network properties.

Suggested Citation

  • Badham, Jennifer & Stocker, Rob, 2010. "The impact of network clustering and assortativity on epidemic behaviour," Theoretical Population Biology, Elsevier, vol. 77(1), pages 71-75.
    • Handle: RePEc:eee:thpobi:v:77:y:2010:i:1:p:71-75
    DOI: 10.1016/j.tpb.2009.11.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580909001270
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tpb.2009.11.003?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. Jennifer Badham & Rob Stocker, 2010. "A Spatial Approach to Network Generation for Three Properties: Degree Distribution, Clustering Coefficient and Degree Assortativity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-11.
    2. Neil M. Ferguson & Matt J. Keeling & W. John Edmunds & Raymond Gani & Bryan T. Grenfell & Roy M. Anderson & Steve Leach, 2003. "Planning for smallpox outbreaks," Nature, Nature, vol. 425(6959), pages 681-685, October.
    3. Badham, Jennifer & Abbass, Hussein & Stocker, Rob, 2008. "Parameterisation of Keeling’s network generation algorithm," Theoretical Population Biology, Elsevier, vol. 74(2), pages 161-166.
    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. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
    2. 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.
    3. Jeong, Wonhee & Yu, Unjong, 2022. "Effects of quadrilateral clustering on complex contagion," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    4. Chen, Jie & Tan, Xuegang & Cao, Jinde & Li, Ming, 2022. "Effect of coupling structure on traffic-driven epidemic spreading in interconnected networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    5. Sheryl Le Chang & Mahendra Piraveenan & Mikhail Prokopenko, 2019. "The Effects of Imitation Dynamics on Vaccination Behaviours in SIR-Network Model," IJERPH, MDPI, vol. 16(14), pages 1-31, July.
    6. Li, Yinwei & Jiang, Guo-Ping & Wu, Meng & Song, Yu-Rong & Wang, Haiyan, 2021. "Undirected Congruence Model: Topological characteristics and epidemic spreading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    7. Nunner, Hendrik & Buskens, Vincent & Teslya, Alexandra & Kretzschmar, Mirjam, 2022. "Health behavior homophily can mitigate the spread of infectious diseases in small-world networks," Social Science & Medicine, Elsevier, vol. 312(C).
    8. Shams, Bita & Khansari, Mohammad, 2015. "On the impact of epidemic severity on network immunization algorithms," Theoretical Population Biology, Elsevier, vol. 106(C), pages 83-93.
    9. Duncan, A.J. & Gunn, G.J. & Umstatter, C. & Humphry, R.W., 2014. "Replicating disease spread in empirical cattle networks by adjusting the probability of infection in random networks," Theoretical Population Biology, Elsevier, vol. 98(C), pages 11-18.

    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. Wijesundera, Isuri & Halgamuge, Malka N. & Nirmalathas, Ampalavanapillai & Nanayakkara, Thrishantha, 2016. "MFPT calculation for random walks in inhomogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 986-1002.
    2. Shams, Bita & Khansari, Mohammad, 2015. "On the impact of epidemic severity on network immunization algorithms," Theoretical Population Biology, Elsevier, vol. 106(C), pages 83-93.
    3. Chengcheng Bei & Shiping Liu & Yin Liao & Gaoliang Tian & Zichen Tian, 2021. "Predicting new cases of COVID‐19 and the application to population sustainability analysis," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4859-4884, September.
    4. Reppas, Andreas I. & Spiliotis, Konstantinos & Siettos, Constantinos I., 2015. "Tuning the average path length of complex networks and its influence to the emergent dynamics of the majority-rule model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 109(C), pages 186-196.
    5. Dunia López-Pintado & Duncan J. Watts, 2008. "Social Influence, Binary Decisions and Collective Dynamics," Rationality and Society, , vol. 20(4), pages 399-443, November.
    6. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
    7. Jose Angulo & Hwa-Lung Yu & Andrea Langousis & Alexander Kolovos & Jinfeng Wang & Ana Esther Madrid & George Christakos, 2013. "Spatiotemporal Infectious Disease Modeling: A BME-SIR Approach," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-12, September.
    8. Rezapour, Shabnam & Baghaian, Atefe & Naderi, Nazanin & Sarmiento, Juan P., 2023. "Infection transmission and prevention in metropolises with heterogeneous and dynamic populations," European Journal of Operational Research, Elsevier, vol. 304(1), pages 113-138.
    9. Duncan, A.J. & Gunn, G.J. & Umstatter, C. & Humphry, R.W., 2014. "Replicating disease spread in empirical cattle networks by adjusting the probability of infection in random networks," Theoretical Population Biology, Elsevier, vol. 98(C), pages 11-18.
    10. Ali Ekici & Pınar Keskinocak & Julie L. Swann, 2014. "Modeling Influenza Pandemic and Planning Food Distribution," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 11-27, February.
    11. George Miller & Stephen Randolph & Jan E. Patterson, 2006. "Responding to Bioterrorist Smallpox in San Antonio," Interfaces, INFORMS, vol. 36(6), pages 580-590, December.
    12. Colo, Philippe, 2021. "Expert-based Knowledge: Communicating over Scientific Models," MPRA Paper 110434, University Library of Munich, Germany.
    13. Robin N Thompson & Christopher A Gilligan & Nik J Cunniffe, 2018. "Control fast or control smart: When should invading pathogens be controlled?," PLOS Computational Biology, Public Library of Science, vol. 14(2), pages 1-21, February.
    14. Robert Axtell & Joseph A. E. Shaheen, 2021. "Agent‐based models with qualitative data are thought experiments, not policy engines: A commentary on Lustick and Tetlock 2021," Futures & Foresight Science, John Wiley & Sons, vol. 3(2), June.
    15. Büyüktahtakın, İ. Esra & des-Bordes, Emmanuel & Kıbış, Eyyüb Y., 2018. "A new epidemics–logistics model: Insights into controlling the Ebola virus disease in West Africa," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1046-1063.
    16. Xiaolei Gao & Jianjian Wei & Hao Lei & Pengcheng Xu & Benjamin J Cowling & Yuguo Li, 2016. "Building Ventilation as an Effective Disease Intervention Strategy in a Dense Indoor Contact Network in an Ideal City," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-20, September.
    17. Chung‐Min Liao & Yi‐Hsien Cheng & Yi‐Jun Lin & Nan‐Hung Hsieh & Tang‐Luen Huang & Chia‐Pin Chio & Szu‐Chieh Chen & Min‐Pei Ling, 2012. "A Probabilistic Transmission and Population Dynamic Model to Assess Tuberculosis Infection Risk," Risk Analysis, John Wiley & Sons, vol. 32(8), pages 1420-1432, August.
    18. repec:jss:jstsof:36:i06 is not listed on IDEAS
    19. Tom Lindström & Michael Tildesley & Colleen Webb, 2015. "A Bayesian Ensemble Approach for Epidemiological Projections," PLOS Computational Biology, Public Library of Science, vol. 11(4), pages 1-30, April.
    20. Arazi, R. & Feigel, A., 2021. "Discontinuous transitions of social distancing in the SIR model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    21. Daniel Merl & Leah R Johnson & Robert B Gramacy & Marc Mangel, 2009. "A Statistical Framework for the Adaptive Management of Epidemiological Interventions," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-9, June.

    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:thpobi:v:77:y:2010:i:1:p:71-75. 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/intelligence .

    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.