IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v37y2017i8p871-881.html
   My bibliography  Save this article

The Effect of Individual Movements and Interventions on the Spread of Influenza in Long-Term Care Facilities

Author

Listed:
  • Mehdi Najafi
  • Marek Laskowski
  • Pieter T. de Boer
  • Evelyn Williams
  • Ayman Chit
  • Seyed M. Moghadas

Abstract

Background. Nosocomial influenza poses a serious risk among residents of long-term care facilities (LTCFs). Objective. We sought to evaluate the effect of resident and staff movements and contact patterns on the outcomes of various intervention strategies for influenza control in an LTCF. Methods. We collected contact frequency data in Canada’s largest veterans’ LTCF by enroling residents and staff into a study that tracked their movements through wireless tags and signal receivers. We analyzed and fitted the data to an agent-based simulation model of influenza infection, and performed Monte-Carlo simulations to evaluate the benefit of antiviral prophylaxis and patient isolation added to standard (baseline) infection control practice (i.e., vaccination of residents and staff, plus antiviral treatment of residents with symptomatic infection). Results. We calibrated the model to attack rates of 20%, 40%, and 60% for the baseline scenario. For data-driven movements, we found that the largest reduction in attack rates (12.5% to 27%; ANOVA P 0.2) among residents. In contrast, parameterizing the model with random movements yielded different results, suggesting that the highest benefit was achieved through patient isolation (69.6% to 79.6%; ANOVA P

Suggested Citation

  • Mehdi Najafi & Marek Laskowski & Pieter T. de Boer & Evelyn Williams & Ayman Chit & Seyed M. Moghadas, 2017. "The Effect of Individual Movements and Interventions on the Spread of Influenza in Long-Term Care Facilities," Medical Decision Making, , vol. 37(8), pages 871-881, November.
    • Handle: RePEc:sae:medema:v:37:y:2017:i:8:p:871-881
    DOI: 10.1177/0272989X17708564
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X17708564
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X17708564?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. Yang Yang & Ira M. Longini & M. Elizabeth Halloran, 2006. "Design and evaluation of prophylactic interventions using infectious disease incidence data from close contact groups," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(3), pages 317-330, May.
    2. Sean Barnes & Bruce Golden & Edward Wasil, 2010. "MRSA Transmission Reduction Using Agent-Based Modeling and Simulation," INFORMS Journal on Computing, INFORMS, vol. 22(4), pages 635-646, November.
    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. Ali Asgary & Hudson Blue & Adriano O. Solis & Zachary McCarthy & Mahdi Najafabadi & Mohammad Ali Tofighi & Jianhong Wu, 2022. "Modeling COVID-19 Outbreaks in Long-Term Care Facilities Using an Agent-Based Modeling and Simulation Approach," IJERPH, MDPI, vol. 19(5), pages 1-16, February.

    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. Sean L. Barnes & Miranda Myers & Clare Rock & Daniel J. Morgan & Lisa Pineles & Kerri A. Thom & Anthony D. Harris, 2020. "Evaluating a Prediction-Driven Targeting Strategy for Reducing the Transmission of Multidrug-Resistant Organisms," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 912-929, October.
    2. Aaron T. Porter & Jacob J. Oleson, 2013. "A Path-Specific SEIR Model for use with General Latent and Infectious Time Distributions," Biometrics, The International Biometric Society, vol. 69(1), pages 101-108, March.
    3. Peng Sun & Liu Yang & Francis de Véricourt, 2009. "Selfish Drug Allocation for Containing an International Influenza Pandemic at the Onset," Operations Research, INFORMS, vol. 57(6), pages 1320-1332, December.
    4. Yang, Yang & Longini Jr., Ira M. & Elizabeth Halloran, M., 2007. "A data-augmentation method for infectious disease incidence data from close contact groups," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6582-6595, August.
    5. Emanuele Borgonovo & Marco Pangallo & Jan Rivkin & Leonardo Rizzo & Nicolaj Siggelkow, 2022. "Sensitivity analysis of agent-based models: a new protocol," Computational and Mathematical Organization Theory, Springer, vol. 28(1), pages 52-94, March.
    6. George J Milne & Nilimesh Halder & Joel K Kelso, 2013. "The Cost Effectiveness of Pandemic Influenza Interventions: A Pandemic Severity Based Analysis," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-16, April.
    7. Qu, Leilei & Gao, Xubin & Kang, Baolin & He, Mingfeng & Pan, Qiuhui, 2019. "Population dynamics models based on the transmission mechanism of MCR-1," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 310-323.
    8. Cai Xiaoxuan & Loh Wen Wei & Crawford Forrest W., 2021. "Identification of causal intervention effects under contagion," Journal of Causal Inference, De Gruyter, vol. 9(1), pages 9-38, January.
    9. Eunha Shim & Gretchen B. Chapman & Alison P. Galvani, 2010. "Decision Making with Regard to Antiviral Intervention during an Influenza Pandemic," Medical Decision Making, , vol. 30(4), pages 64-81, July.

    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:medema:v:37:y:2017:i:8:p:871-881. 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.