IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0258710.html
   My bibliography  Save this article

An operationally implementable model for predicting the effects of an infectious disease on a comprehensive regional healthcare system

Author

Listed:
  • Daniel Chertok
  • Chad Konchak
  • Nirav Shah
  • Kamaljit Singh
  • Loretta Au
  • Jared Hammernik
  • Brian Murray
  • Anthony Solomonides
  • Ernest Wang
  • Lakshmi Halasyamani

Abstract

An operationally implementable predictive model has been developed to forecast the number of COVID-19 infections in the patient population, hospital floor and ICU censuses, ventilator and related supply chain demand. The model is intended for clinical, operational, financial and supply chain leaders and executives of a comprehensive healthcare system responsible for making decisions that depend on epidemiological contingencies. This paper describes the model that was implemented at NorthShore University HealthSystem and is applicable to any communicable disease whose risk of reinfection for the duration of the pandemic is negligible.

Suggested Citation

  • Daniel Chertok & Chad Konchak & Nirav Shah & Kamaljit Singh & Loretta Au & Jared Hammernik & Brian Murray & Anthony Solomonides & Ernest Wang & Lakshmi Halasyamani, 2021. "An operationally implementable model for predicting the effects of an infectious disease on a comprehensive regional healthcare system," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-21, October.
    • Handle: RePEc:plo:pone00:0258710
    DOI: 10.1371/journal.pone.0258710
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0258710
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0258710&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0258710?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. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "A SIR model assumption for the spread of COVID-19 in different communities," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    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. Mohamed M. Mousa & Fahad Alsharari, 2021. "A Comparative Numerical Study and Stability Analysis for a Fractional-Order SIR Model of Childhood Diseases," Mathematics, MDPI, vol. 9(22), pages 1-12, November.
    2. Talal Daghriri & Michael Proctor & Sarah Matthews, 2022. "Evolution of Select Epidemiological Modeling and the Rise of Population Sentiment Analysis: A Literature Review and COVID-19 Sentiment Illustration," IJERPH, MDPI, vol. 19(6), pages 1-20, March.
    3. Alaa El-Sakran & Reem Salman & Ayman Alzaatreh, 2022. "Impacts of Emergency Remote Teaching on College Students Amid COVID-19 in the UAE," IJERPH, MDPI, vol. 19(5), pages 1-21, March.
    4. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    5. Lin William Cong & Ke Tang & Bing Wang & Jingyuan Wang, 2021. "An AI-assisted Economic Model of Endogenous Mobility and Infectious Diseases: The Case of COVID-19 in the United States," Papers 2109.10009, arXiv.org.
    6. Ghanbari, Behzad, 2021. "On detecting chaos in a prey-predator model with prey’s counter-attack on juvenile predators," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    7. Wan, Jinming & Ichinose, Genki & Small, Michael & Sayama, Hiroki & Moreno, Yamir & Cheng, Changqing, 2022. "Multilayer networks with higher-order interaction reveal the impact of collective behavior on epidemic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    8. Korryn Bodner & Chris Brimacombe & Emily S Chenery & Ariel Greiner & Anne M McLeod & Stephanie R Penk & Juan S Vargas Soto, 2021. "Ten simple rules for tackling your first mathematical models: A guide for graduate students by graduate students," PLOS Computational Biology, Public Library of Science, vol. 17(1), pages 1-12, January.
    9. Aguilar-Canto, Fernando Javier & de León, Ugo Avila-Ponce & Avila-Vales, Eric, 2022. "Sensitivity theorems of a model of multiple imperfect vaccines for COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    10. Giovanni Nastasi & Carla Perrone & Salvatore Taffara & Giorgia Vitanza, 2022. "A Time-Delayed Deterministic Model for the Spread of COVID-19 with Calibration on a Real Dataset," Mathematics, MDPI, vol. 10(4), pages 1-14, February.
    11. Yong-Ju Jang & Min-Seung Kim & Chan-Ho Lee & Ji-Hye Choi & Jeong-Hee Lee & Sun-Hong Lee & Tae-Eung Sung, 2022. "A Novel Approach on Deep Learning—Based Decision Support System Applying Multiple Output LSTM-Autoencoder: Focusing on Identifying Variations by PHSMs’ Effect over COVID-19 Pandemic," IJERPH, MDPI, vol. 19(11), pages 1-22, June.
    12. Papageorgiou, Vasileios E. & Tsaklidis, George, 2023. "An improved epidemiological-unscented Kalman filter (hybrid SEIHCRDV-UKF) model for the prediction of COVID-19. Application on real-time data," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    13. Miguel Casares & Hashmat Khan, 2020. "The Timing and Intensity of Social Distancing to Flatten the COVID-19 Curve: The Case of Spain," IJERPH, MDPI, vol. 17(19), pages 1-14, October.
    14. Ahumada, M. & Ledesma-Araujo, A. & Gordillo, L. & Marín, J.F., 2023. "Mutation and SARS-CoV-2 strain competition under vaccination in a modified SIR model," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    15. Aditya Goenka & Lin Liu & Manh-Hung Nguyen, 2021. "Modeling optimal quarantines with waning immunity," Discussion Papers 21-10, Department of Economics, University of Birmingham.
    16. Wu, Yue & Li, Linjiao & Yu, Qiannan & Gan, Jiaxin & Zhang, Yi, 2023. "Strategies for reducing polarization in social networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    17. Caraballo, T. & Settati, A. & Lahrouz, A. & Boutouil, S. & Harchaoui, B., 2024. "On the stochastic threshold of the COVID-19 epidemic model incorporating jump perturbations," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    18. Samuel O. M. Manda & Timotheus Darikwa & Tshifhiwa Nkwenika & Robert Bergquist, 2021. "A Spatial Analysis of COVID-19 in African Countries: Evaluating the Effects of Socio-Economic Vulnerabilities and Neighbouring," IJERPH, MDPI, vol. 18(20), pages 1-15, October.
    19. Jain, Lokesh, 2022. "An entropy-based method to control COVID-19 rumors in online social networks using opinion leaders," Technology in Society, Elsevier, vol. 70(C).
    20. Guihua Wang, 2022. "Stay at home to stay safe: Effectiveness of stay‐at‐home orders in containing the COVID‐19 pandemic," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2289-2305, 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:pone00:0258710. 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.