IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v35y2008i1p80-99.html
   My bibliography  Save this article

Individual Space – Time Activity-Based Model: A Model for the Simulation of Airborne Infectious-Disease Transmission by Activity-Bundle Simulation

Author

Listed:
  • Yong Yang
  • Peter M Atkinson

Abstract

Activity bundle (AB) simulation is a method for obtaining a specific contact network (specific to target infectious disease) from the space–time dynamics of individuals constrained both by their social activity and by the physical condition of the space. Taking advantage of AB simulation, an individual space–time activity-based model (ISTAM) is presented which integrates the infectious-disease evolution process, individual activity patterns, and stochastic infection model. ISTAM was applied to the University of Southampton in order to simulate a hypothetical influenza epidemic. The results show that the model behaviour is approximately consistent with expectations.

Suggested Citation

  • Yong Yang & Peter M Atkinson, 2008. "Individual Space – Time Activity-Based Model: A Model for the Simulation of Airborne Infectious-Disease Transmission by Activity-Bundle Simulation," Environment and Planning B, , vol. 35(1), pages 80-99, February.
    • Handle: RePEc:sae:envirb:v:35:y:2008:i:1:p:80-99
    DOI: 10.1068/b32162
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/b32162
    Download Restriction: no
    File URL: https://libkey.io/10.1068/b32162?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
    ---><---

    References listed on IDEAS

    as
    1. Michael Batty, 2005. "Agents, Cells, and Cities: New Representational Models for Simulating Multiscale Urban Dynamics," Environment and Planning A, , vol. 37(8), pages 1373-1394, August.
    2. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
    3. Chung-Yuan Huang & Chuen-Tsai Sun & Ji-Lung Hsieh & Holin Lin, 2004. "Simulating SARS: Small-World Epidemiological Modeling and Public Health Policy Assessments," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 7(4), pages 1-2.
    4. Stephen Eubank & Hasan Guclu & V. S. Anil Kumar & Madhav V. Marathe & Aravind Srinivasan & Zoltán Toroczkai & Nan Wang, 2004. "Modelling disease outbreaks in realistic urban social networks," Nature, Nature, vol. 429(6988), pages 180-184, May.
    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. An, Li, 2012. "Modeling human decisions in coupled human and natural systems: Review of agent-based models," Ecological Modelling, Elsevier, vol. 229(C), pages 25-36.
    2. Wang, W.L. & Tsui, K.L. & Lo, S.M. & Liu, S.B., 2018. "Computational modeling and statistical analyses on individual contact rate and exposure to disease in complex and confined transportation hubs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1461-1470.

    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. D'Acci, Luca, 2013. "A Modern Postmodern Urbanism The Systemic Retroactive game (SyR) between Bottom-up and Top-down," MPRA Paper 48991, University Library of Munich, Germany.
    2. An, Li, 2012. "Modeling human decisions in coupled human and natural systems: Review of agent-based models," Ecological Modelling, Elsevier, vol. 229(C), pages 25-36.
    3. Luís de Sousa & Alberto Rodrigues da Silva, 2015. "Showcasing a Domain Specific Language for Spatial Simulation Scenarios with case studies," ERSA conference papers ersa15p1044, European Regional Science Association.
    4. Eugenio Caverzasi & Antoine Godin, 2013. "Stock-flow Consistent Modeling through the Ages," Economics Working Paper Archive wp_745, Levy Economics Institute.
    5. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    6. Michael J. Radzicki, 2003. "Mr. Hamilton, Mr. Forrester, and a Foundation for Evolutionary Economics," Journal of Economic Issues, Taylor & Francis Journals, vol. 37(1), pages 133-173, March.
    7. Kazuya Yamamoto, 2015. "Mobilization, Flexibility of Identity, and Ethnic Cleavage," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-8.
    8. Mehdi Sheikh Goodarzi & Yousef Sakieh & Shabnam Navardi, 2017. "Scenario-based urban growth allocation in a rapidly developing area: a modeling approach for sustainability analysis of an urban-coastal coupled system," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(3), pages 1103-1126, June.
    9. Dirk Helbing & Thomas U. Grund, 2013. "Editorial: Agent-Based Modeling And Techno-Social Systems," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 16(04n05), pages 1-3.
    10. Floriana Gargiulo & Sônia Ternes & Sylvie Huet & Guillaume Deffuant, 2010. "An Iterative Approach for Generating Statistically Realistic Populations of Households," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-9, January.
    11. Saturnino Luz & Masood Masoodian, 2022. "Exploring Environmental and Geographical Factors Influencing the Spread of Infectious Diseases with Interactive Maps," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    12. Ross Richardson & Matteo G. Richiardi & Michael Wolfson, 2015. "We ran one billion agents. Scaling in simulation models," LABORatorio R. Revelli Working Papers Series 142, LABORatorio R. Revelli, Centre for Employment Studies.
    13. Roberto Veneziani & Luca Zamparelli & Michalis Nikiforos & Gennaro Zezza, 2017. "Stock-Flow Consistent Macroeconomic Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1204-1239, December.
    14. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
    15. Teruhiko Yoneyama & Sanmay Das & Mukkai Krishnamoorthy, 2012. "A Hybrid Model for Disease Spread and an Application to the SARS Pandemic," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(1), pages 1-5.
    16. Cincotti, Silvano & Raberto, Marco & Teglio, Andrea, 2010. "Credit money and macroeconomic instability in the agent-based model and simulator Eurace," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-32.
    17. Khalil, Elias L., 2010. "The Bayesian fallacy: Distinguishing internal motivations and religious beliefs from other beliefs," Journal of Economic Behavior & Organization, Elsevier, vol. 75(2), pages 268-280, August.
    18. Jakub Bijak & Jason D. Hilton & Eric Silverman & Viet Dung Cao, 2013. "Reforging the Wedding Ring," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(27), pages 729-766.
    19. Pablo D. Fajgelbaum & Amit Khandelwal & Wookun Kim & Cristiano Mantovani & Edouard Schaal, 2021. "Optimal Lockdown in a Commuting Network," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 503-522, December.
    20. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.

    More about this item

    Statistics

    Access and download statistics

    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:sae:envirb:v:35:y:2008:i:1:p:80-99. 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: SAGE Publications (email available below). General contact details of provider: .

    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.