IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0024706.html
   My bibliography  Save this article

Evaluating the Combined Effectiveness of Influenza Control Strategies and Human Preventive Behavior

Author

Listed:
  • Liang Mao

Abstract

Control strategies enforced by health agencies are a major type of practice to contain influenza outbreaks. Another type of practice is the voluntary preventive behavior of individuals, such as receiving vaccination, taking antiviral drugs, and wearing face masks. These two types of practices take effects concurrently in influenza containment, but little attention has been paid to their combined effectiveness. This article estimates this combined effectiveness using established simulation models in the urbanized area of Buffalo, NY, USA. Three control strategies are investigated, including: Targeted Antiviral Prophylaxis (TAP), workplace/school closure, community travel restriction, as well as the combination of the three. All control strategies are simulated with and without regard to individual preventive behavior, and the resulting effectiveness are compared. The simulation outcomes suggest that weaker control strategies could suffice to contain influenza epidemics, because individuals voluntarily adopt preventive behavior, rendering these weaker strategies more effective than would otherwise have been expected. The preventive behavior of individuals could save medical resources for control strategies and avoid unnecessary socio-economic interruptions. This research adds a human behavioral dimension into the simulation of control strategies and offers new insights into disease containment. Health policy makers are recommended to review current control strategies and comprehend preventive behavior patterns of local populations before making decisions on influenza containment.

Suggested Citation

  • Liang Mao, 2011. "Evaluating the Combined Effectiveness of Influenza Control Strategies and Human Preventive Behavior," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-8, October.
    • Handle: RePEc:plo:pone00:0024706
    DOI: 10.1371/journal.pone.0024706
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0024706
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0024706&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0024706?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. Neil Ferguson, 2007. "Capturing human behaviour," Nature, Nature, vol. 446(7137), pages 733-733, April.
    3. Gabriele Neumann & Takeshi Noda & Yoshihiro Kawaoka, 2009. "Emergence and pandemic potential of swine-origin H1N1 influenza virus," Nature, Nature, vol. 459(7249), pages 931-939, June.
    4. 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.
    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. 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.
    2. Lee, Choong-Ki & Song, Hak-Jun & Bendle, Lawrence J. & Kim, Myung-Ja & Han, Heesup, 2012. "The impact of non-pharmaceutical interventions for 2009 H1N1 influenza on travel intentions: A model of goal-directed behavior," Tourism Management, Elsevier, vol. 33(1), pages 89-99.
    3. 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.
    4. Stephan Kitchovitch & Pietro Liò, 2011. "Community Structure in Social Networks: Applications for Epidemiological Modelling," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-17, July.
    5. 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.
    6. 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).
    7. 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.
    8. Yang-chih Fu & Da-Wei Wang & Jen-Hsiang Chuang, 2012. "Representative Contact Diaries for Modeling the Spread of Infectious Diseases in Taiwan," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-7, October.
    9. Catalina Amuedo-Dorantes & Neeraj Kaushal & Ashley N. Muchow, 2021. "Timing of social distancing policies and COVID-19 mortality: county-level evidence from the U.S," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1445-1472, October.
    10. 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.
    11. Susan M. Rogers & James Rineer & Matthew D. Scruggs & William D. Wheaton & Phillip C. Cooley & Douglas J. Roberts & Diane K. Wagener, 2014. "A Geospatial Dynamic Microsimulation Model for Household Population Projections," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 119-146.
    12. Antonio Diez de los Rios, 2022. "A macroeconomic model of an epidemic with silent transmission and endogenous self‐isolation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 581-625, February.
    13. 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.
    14. Elisa Giannone & Nuno Paixao & Xinle Pang, 2021. "The Geography of Pandemic Containment," Staff Working Papers 21-26, Bank of Canada.
    15. Ricardo Aguas & Neil M Ferguson, 2013. "Feature Selection Methods for Identifying Genetic Determinants of Host Species in RNA Viruses," PLOS Computational Biology, Public Library of Science, vol. 9(10), pages 1-10, October.
    16. Mugnaine, Michele & Gabrick, Enrique C. & Protachevicz, Paulo R. & Iarosz, Kelly C. & de Souza, Silvio L.T. & Almeida, Alexandre C.L. & Batista, Antonio M. & Caldas, Iberê L. & Szezech Jr, José D. & V, 2022. "Control attenuation and temporary immunity in a cellular automata SEIR epidemic model," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    17. Wiriya Mahikul & Somkid Kripattanapong & Piya Hanvoravongchai & Aronrag Meeyai & Sopon Iamsirithaworn & Prasert Auewarakul & Wirichada Pan-ngum, 2020. "Contact Mixing Patterns and Population Movement among Migrant Workers in an Urban Setting in Thailand," IJERPH, MDPI, vol. 17(7), pages 1-11, March.
    18. Carnehl, Christoph & Fukuda, Satoshi & Kos, Nenad, 2023. "Epidemics with behavior," Journal of Economic Theory, Elsevier, vol. 207(C).
    19. Andrew G. Atkeson & Karen A. Kopecky & Tao Zha, 2024. "Four Stylized Facts About Covid‐19," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(1), pages 3-42, February.
    20. Michael George Roberts & Hiroshi Nishiura, 2011. "Early Estimation of the Reproduction Number in the Presence of Imported Cases: Pandemic Influenza H1N1-2009 in New Zealand," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-9, May.

    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:pone00:0024706. 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.