IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0128070.html
   My bibliography  Save this article

School’s Out: Seasonal Variation in the Movement Patterns of School Children

Author

Listed:
  • Adam J Kucharski
  • Andrew J K Conlan
  • Ken T D Eames

Abstract

School children are core groups in the transmission of many common infectious diseases, and are likely to play a key role in the spatial dispersal of disease across multiple scales. However, there is currently little detailed information about the spatial movements of this epidemiologically important age group. To address this knowledge gap, we collaborated with eight secondary schools to conduct a survey of movement patterns of school pupils in primary and secondary schools in the United Kingdom. We found evidence of a significant change in behaviour between term time and holidays, with term time weekdays characterised by predominately local movements, and holidays seeing much broader variation in travel patterns. Studies that use mathematical models to examine epidemic transmission and control often use adult commuting data as a proxy for population movements. We show that while these data share some features with the movement patterns reported by school children, there are some crucial differences between the movements of children and adult commuters during both term-time and holidays.

Suggested Citation

  • Adam J Kucharski & Andrew J K Conlan & Ken T D Eames, 2015. "School’s Out: Seasonal Variation in the Movement Patterns of School Children," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-10, June.
    • Handle: RePEc:plo:pone00:0128070
    DOI: 10.1371/journal.pone.0128070
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0128070
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0128070&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0128070?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. Adam J Kucharski & Kin O Kwok & Vivian W I Wei & Benjamin J Cowling & Jonathan M Read & Justin Lessler & Derek A Cummings & Steven Riley, 2014. "The Contribution of Social Behaviour to the Transmission of Influenza A in a Human Population," PLOS Pathogens, Public Library of Science, vol. 10(6), pages 1-8, June.
    3. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    4. Joël Mossong & Niel Hens & Mark Jit & Philippe Beutels & Kari Auranen & Rafael Mikolajczyk & Marco Massari & Stefania Salmaso & Gianpaolo Scalia Tomba & Jacco Wallinga & Janneke Heijne & Malgorzata Sa, 2008. "Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases," PLOS Medicine, Public Library of Science, vol. 5(3), pages 1-1, March.
    5. Vittoria Colizza & Alain Barrat & Marc Barthelemy & Alain-Jacques Valleron & Alessandro Vespignani, 2007. "Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions," PLOS Medicine, Public Library of Science, vol. 4(1), pages 1-16, January.
    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. 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.
    2. 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.
    3. Ken T D Eames & Natasha L Tilston & Ellen Brooks-Pollock & W John Edmunds, 2012. "Measured Dynamic Social Contact Patterns Explain the Spread of H1N1v Influenza," PLOS Computational Biology, Public Library of Science, vol. 8(3), pages 1-8, March.
    4. Christopher Bronk Ramsey, 2020. "Human agency and infection rates: Implications for social distancing during epidemics," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-17, December.
    5. Brotherhood, Luiz & Kircher, Philipp & Santos, Cezar & Tertilt, Michèle, 2023. "Optimal Age-based Policies for Pandemics: An Economic Analysis of Covid-19 and Beyond," IDB Publications (Working Papers) 13295, Inter-American Development Bank.
    6. 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.
    7. 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.
    8. Savachkin, Alex & Uribe, Andrés, 2012. "Dynamic redistribution of mitigation resources during influenza pandemics," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 33-45.
    9. 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.
    10. Janiak, Alexandre & Machado, Caio & Turén, Javier, 2021. "Covid-19 contagion, economic activity and business reopening protocols," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 264-284.
    11. Brotherhood, Luiz & Kircher, Philipp & Santos, Cezar & Tertilt, Michele, 2024. "Optimal Age-based Policies for Pandemics: An Economic Analysis of Covid-19 and Beyond," LIDAM Discussion Papers CORE 2024012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Christian Thiemann & Fabian Theis & Daniel Grady & Rafael Brune & Dirk Brockmann, 2010. "The Structure of Borders in a Small World," PLOS ONE, Public Library of Science, vol. 5(11), pages 1-7, November.
    13. Heinrich, Torsten, 2021. "Epidemics in modern economies," MPRA Paper 107578, University Library of Munich, Germany.
    14. Catherine Z. Worsnop, 2017. "Domestic politics and the WHO’s International Health Regulations: Explaining the use of trade and travel barriers during disease outbreaks," The Review of International Organizations, Springer, vol. 12(3), pages 365-395, September.
    15. Michael A Johansson & Neysarí Arana-Vizcarrondo & Brad J Biggerstaff & J Erin Staples & Nancy Gallagher & Nina Marano, 2011. "On the Treatment of Airline Travelers in Mathematical Models," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-7, July.
    16. 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.
    17. Sangwon Chae & Sungjun Kwon & Donghyun Lee, 2018. "Predicting Infectious Disease Using Deep Learning and Big Data," IJERPH, MDPI, vol. 15(8), pages 1-20, July.
    18. Chun-Hsiang Chan & Tzai-Hung Wen, 2021. "Revisiting the Effects of High-Speed Railway Transfers in the Early COVID-19 Cross-Province Transmission in Mainland China," IJERPH, MDPI, vol. 18(12), pages 1-17, June.
    19. David Fajardo & Lauren Gardner, 2013. "Inferring Contagion Patterns in Social Contact Networks with Limited Infection Data," Networks and Spatial Economics, Springer, vol. 13(4), pages 399-426, December.
    20. Paolo Bajardi & Chiara Poletto & Jose J Ramasco & Michele Tizzoni & Vittoria Colizza & Alessandro Vespignani, 2011. "Human Mobility Networks, Travel Restrictions, and the Global Spread of 2009 H1N1 Pandemic," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-8, January.

    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:pone00:0128070. 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.