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Time between Symptom Onset, Hospitalisation and Recovery or Death: Statistical Analysis of Belgian COVID-19 Patients

Author

Listed:
  • Christel Faes

    (Data Science Institute (DSI), I-BioStat, Universiteit Hasselt, BE-3500 Hasselt, Belgium)

  • Steven Abrams

    (Data Science Institute (DSI), I-BioStat, Universiteit Hasselt, BE-3500 Hasselt, Belgium
    Global Health Institute (GHI), University of Antwerp, BE-2000 Antwerp, Belgium)

  • Dominique Van Beckhoven

    (Department of Epidemiology and Public Health, Sciensano, BE-1050 Brussels, Belgium)

  • Geert Meyfroidt

    (Department and Laboratory of Intensive Care Medicine, University Hospitals Leuven and KU Leuven, Herestraat 49, Box 7003 63, 3000 Leuven, Belgium)

  • Erika Vlieghe

    (Department of General Internal Medicine, Infectious and Tropical Diseases, University Hospital Antwerp, BE-2000 Antwerp, Belgium)

  • Niel Hens

    (Data Science Institute (DSI), I-BioStat, Universiteit Hasselt, BE-3500 Hasselt, Belgium
    Centre for Health Economics Research and Modelling of Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, BE-2000 Antwerp, Belgium)

  • Belgian Collaborative Group on COVID-19 Hospital Surveillance

    (Department of Epidemiology and Public Health, Sciensano, BE-1050 Brussels, Belgium
    Members of the Belgian Collaborative Group on COVID-19 Hospital Surveillance: Amir-Samy Aouachria, Kristof Bafort, Leïla Belkhir, Nathalie Bossuyt, Vincent Colombie, Nicolas Dauby, Paul De Munter, Jessika Deblonde, Didier Delmarcelle, Mélanie Delvallee, Rémy Demeester, Thierry Dugernier, Xavier Holemans, Benjamin Kerzmann, Pierre Yves Machurot, Philippe Minette, Jean-Marc Minon, Saphia Mokrane, Catherine Nachtergal, Séverine Noirhomme, Denis Piérard, Camelia Rossi, Carole Schirvel, Erica Sermijn, Frank Staelens, Filip Triest, Nina Van Goethem, Jens Van Praet, Anke Vanhoenacker, Sarah Cooreman, Elise Willems, Chloé Wyndham-Thomas ( Appendix E ).)

Abstract

There are different patterns in the COVID-19 outbreak in the general population and amongst nursing home patients. We investigate the time from symptom onset to diagnosis and hospitalization or the length of stay (LoS) in the hospital, and whether there are differences in the population. Sciensano collected information on 14,618 hospitalized patients with COVID-19 admissions from 114 Belgian hospitals between 14 March and 12 June 2020. The distributions of different event times for different patient groups are estimated accounting for interval censoring and right truncation of the time intervals. The time between symptom onset and hospitalization or diagnosis are similar, with median length between symptom onset and hospitalization ranging between 3 and 10.4 days, depending on the age of the patient (longest delay in age group 20–60 years) and whether or not the patient lives in a nursing home (additional 2 days for patients from nursing home). The median LoS in hospital varies between 3 and 10.4 days, with the LoS increasing with age. The hospital LoS for patients that recover is shorter for patients living in a nursing home, but the time to death is longer for these patients. Over the course of the first wave, the LoS has decreased.

Suggested Citation

  • Christel Faes & Steven Abrams & Dominique Van Beckhoven & Geert Meyfroidt & Erika Vlieghe & Niel Hens & Belgian Collaborative Group on COVID-19 Hospital Surveillance, 2020. "Time between Symptom Onset, Hospitalisation and Recovery or Death: Statistical Analysis of Belgian COVID-19 Patients," IJERPH, MDPI, vol. 17(20), pages 1-18, October.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:20:p:7560-:d:430556
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    Citations

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    Cited by:

    1. González-Parra, Gilberto & Villanueva-Oller, Javier & Navarro-González, F.J. & Ceberio, Josu & Luebben, Giulia, 2024. "A network-based model to assess vaccination strategies for the COVID-19 pandemic by using Bayesian optimization," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    2. Miquel Oliu-Barton & Bary S. R. Pradelski & Nicolas Woloszko & Lionel Guetta-Jeanrenaud & Philippe Aghion & Patrick Artus & Arnaud Fontanet & Philippe Martin & Guntram B. Wolff, 2022. "The effect of COVID certificates on vaccine uptake, health outcomes, and the economy," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    3. Basnarkov, Lasko & Tomovski, Igor & Sandev, Trifce & Kocarev, Ljupco, 2022. "Non-Markovian SIR epidemic spreading model of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    4. Reese Richardson & Emile Jorgensen & Philip Arevalo & Tobias M. Holden & Katelyn M. Gostic & Massimo Pacilli & Isaac Ghinai & Shannon Lightner & Sarah Cobey & Jaline Gerardin, 2022. "Tracking changes in SARS-CoV-2 transmission with a novel outpatient sentinel surveillance system in Chicago, USA," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    5. Amani Almohaimeed & Jochen Einbeck & Najla Qarmalah & Hanan Alkhidhr, 2022. "Using Random Effect Models to Produce Robust Estimates of Death Rates in COVID-19 Data," IJERPH, MDPI, vol. 19(22), pages 1-13, November.
    6. Dijkstra, Sander & Baas, Stef & Braaksma, Aleida & Boucherie, Richard J., 2023. "Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy," Omega, Elsevier, vol. 116(C).

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