IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0001519.html
   My bibliography  Save this article

The Impact of the Unstructured Contacts Component in Influenza Pandemic Modeling

Author

Listed:
  • Marco Ajelli
  • Stefano Merler

Abstract

Background: Individual based models have become a valuable tool for modeling the spatiotemporal dynamics of epidemics, e.g. influenza pandemic, and for evaluating the effectiveness of intervention strategies. While specific contacts among individuals into diverse environments (family, school/workplace) can be modeled in a standard way by employing available socio-demographic data, all the other (unstructured) contacts can be dealt with by adopting very different approaches. This can be achieved for instance by employing distance-based models or by choosing unstructured contacts in the local communities or by employing commuting data. Methods/Results: Here we show how diverse choices can lead to different model outputs and thus to a different evaluation of the effectiveness of the containment/mitigation strategies. Sensitivity analysis has been conducted for different values of the first generation index G0 , which is the average number of secondary infections generated by the first infectious individual in a completely susceptible population and by varying the seeding municipality. Among the different considered models, attack rate ranges from 19.1% to 25.7% for G0 = 1.1, from 47.8% to 50.7% for G0 = 1.4 and from 62.4% to 67.8% for G0 = 1.7. Differences of about 15 to 20 days in the peak day have been observed. As regards spatial diffusion, a difference of about 100 days to cover 200 km for different values of G0 has been observed. Conclusion: To reduce uncertainty in the models it is thus important to employ data, which start being available, on contacts on neglected but important activities (leisure time, sport mall, restaurants, etc.) and time-use data for improving the characterization of the unstructured contacts. Moreover, all the possible effects of different assumptions should be considered for taking public health decisions: not only sensitivity analysis to various model parameters should be performed, but intervention options should be based on the analysis and comparison of different modeling choices.

Suggested Citation

  • Marco Ajelli & Stefano Merler, 2008. "The Impact of the Unstructured Contacts Component in Influenza Pandemic Modeling," PLOS ONE, Public Library of Science, vol. 3(1), pages 1-10, January.
  • Handle: RePEc:plo:pone00:0001519
    DOI: 10.1371/journal.pone.0001519
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0001519
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0001519&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0001519?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. Neil M. Ferguson & Derek A. T. Cummings & Christophe Fraser & James C. Cajka & Philip C. Cooley & Donald S. Burke, 2006. "Strategies for mitigating an influenza pandemic," Nature, Nature, vol. 442(7101), pages 448-452, July.
    2. Cécile Viboud & Mark A Miller & Bryan T Grenfell & Ottar N Bjørnstad & Lone Simonsen, 2006. "Air Travel and the Spread of Influenza: Important Caveats," PLOS Medicine, Public Library of Science, vol. 3(11), pages 1-2, November.
    3. Neil M. Ferguson & Derek A.T. Cummings & Simon Cauchemez & Christophe Fraser & Steven Riley & Aronrag Meeyai & Sopon Iamsirithaworn & Donald S. Burke, 2005. "Strategies for containing an emerging influenza pandemic in Southeast Asia," Nature, Nature, vol. 437(7056), pages 209-214, September.
    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. Jeremy Hadidjojo & Siew Ann Cheong, 2011. "Equal Graph Partitioning on Estimated Infection Network as an Effective Epidemic Mitigation Measure," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-10, July.
    2. Moshe B Hoshen & Anthony H Burton & Themis J V Bowcock, 2007. "Simulating disease transmission dynamics at a multi-scale level," International Journal of Microsimulation, International Microsimulation Association, vol. 1(1), pages 26-34.
    3. James Truscott & Neil M Ferguson, 2012. "Evaluating the Adequacy of Gravity Models as a Description of Human Mobility for Epidemic Modelling," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-12, October.
    4. Eva K. Lee & Chien-Hung Chen & Ferdinand Pietz & Bernard Benecke, 2009. "Modeling and Optimizing the Public-Health Infrastructure for Emergency Response," Interfaces, INFORMS, vol. 39(5), pages 476-490, October.
    5. Eva K. Lee & Ferdinand Pietz & Bernard Benecke & Jacquelyn Mason & Greg Burel, 2013. "Advancing Public Health and Medical Preparedness with Operations Research," Interfaces, INFORMS, vol. 43(1), pages 79-98, February.
    6. Akira Watanabe & Hiroyuki Matsuda, 2023. "Effectiveness of feedback control and the trade-off between death by COVID-19 and costs of countermeasures," Health Care Management Science, Springer, vol. 26(1), pages 46-61, March.
    7. Andy Hong & Sandip Chakrabarti, 2023. "Compact living or policy inaction? Effects of urban density and lockdown on the COVID-19 outbreak in the US," Urban Studies, Urban Studies Journal Limited, vol. 60(9), pages 1588-1609, July.
    8. Rakowski, Franciszek & Gruziel, Magdalena & Bieniasz-Krzywiec, Łukasz & Radomski, Jan P., 2010. "Influenza epidemic spread simulation for Poland — a large scale, individual based model study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3149-3165.
    9. van der Weijden, Charlie P. & Stein, Mart L. & Jacobi, André J. & Kretzschmar, Mirjam E.E. & Reintjes, Ralf & van Steenbergen, Jim E. & Timen, Aura, 2013. "Choosing pandemic parameters for pandemic preparedness planning: A comparison of pandemic scenarios prior to and following the influenza A(H1N1) 2009 pandemic," Health Policy, Elsevier, vol. 109(1), pages 52-62.
    10. Lawrence M. Wein & Michael P. Atkinson, 2009. "Assessing Infection Control Measures for Pandemic Influenza," Risk Analysis, John Wiley & Sons, vol. 29(7), pages 949-962, July.
    11. Marco Ajelli & Stefano Merler, 2012. "Transmission Potential and Design of Adequate Control Measures for Marburg Hemorrhagic Fever," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-8, December.
    12. Savachkin, Alex & Uribe, Andrés, 2012. "Dynamic redistribution of mitigation resources during influenza pandemics," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 33-45.
    13. T Déirdre Hollingsworth & Don Klinkenberg & Hans Heesterbeek & Roy M Anderson, 2011. "Mitigation Strategies for Pandemic Influenza A: Balancing Conflicting Policy Objectives," PLOS Computational Biology, Public Library of Science, vol. 7(2), pages 1-11, February.
    14. Dionne M. Aleman & Theodorus G. Wibisono & Brian Schwartz, 2011. "A Nonhomogeneous Agent-Based Simulation Approach to Modeling the Spread of Disease in a Pandemic Outbreak," Interfaces, INFORMS, vol. 41(3), pages 301-315, June.
    15. Jeffrey Shaman & Virginia E Pitzer & Cécile Viboud & Bryan T Grenfell & Marc Lipsitch, 2010. "Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States," PLOS Biology, Public Library of Science, vol. 8(2), pages 1-13, February.
    16. Warren Jochem & Kelly Sims & Edward Bright & Marie Urban & Amy Rose & Phillip Coleman & Budhendra Bhaduri, 2013. "Estimating traveler populations at airport and cruise terminals for population distribution and dynamics," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 68(3), pages 1325-1342, September.
    17. Marcel Salathé & James H Jones, 2010. "Dynamics and Control of Diseases in Networks with Community Structure," PLOS Computational Biology, Public Library of Science, vol. 6(4), pages 1-11, April.
    18. Masaya M Saito & Seiya Imoto & Rui Yamaguchi & Masaharu Tsubokura & Masahiro Kami & Haruka Nakada & Hiroki Sato & Satoru Miyano & Tomoyuki Higuchi, 2013. "Enhancement of Collective Immunity in Tokyo Metropolitan Area by Selective Vaccination against an Emerging Influenza Pandemic," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-9, September.
    19. Solen Kernéis & Rebecca F Grais & Pierre-Yves Boëlle & Antoine Flahault & Elisabeta Vergu, 2008. "Does the Effectiveness of Control Measures Depend on the Influenza Pandemic Profile?," PLOS ONE, Public Library of Science, vol. 3(1), pages 1-12, January.
    20. Cuñat, Alejandro & Zymek, Robert, 2022. "The (structural) gravity of epidemics," European Economic Review, Elsevier, vol. 144(C).

    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:plo:pone00:0001519. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.