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Predicting COVID-19 progression from diagnosis to recovery or death linking primary care and hospital records in Castilla y León (Spain)

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  • Pedro C Álvarez-Esteban
  • Eustasio del Barrio
  • Oscar M Rueda
  • Cristina Rueda

Abstract

This paper analyses COVID-19 patients’ dynamics during the first wave in the region of Castilla y León (Spain) with around 2.4 million inhabitants using multi-state competing risk survival models. From the date registered as the start of the clinical process, it is assumed that a patient can progress through three intermediate states until reaching an absorbing state of recovery or death. Demographic characteristics, epidemiological factors such as the time of infection and previous vaccinations, clinical history, complications during the course of the disease and drug therapy for hospitalised patients are considered as candidate predictors. Regarding risk factors associated with mortality and severity, consistent results with many other studies have been found, such as older age, being male, and chronic diseases. Specifically, the hospitalisation (death) rate for those over 69 is 27.2% (19.8%) versus 5.3% (0.7%) for those under 70, and for males is 14.5%(7%) versus 8.3%(4.6%)for females. Among patients with chronic diseases the highest rates of hospitalisation are 26.1% for diabetes and 26.3% for kidney disease, while the highest death rate is 21.9% for cerebrovascular disease. Moreover, specific predictors for different transitions are given, and estimates of the probability of recovery and death for each patient are provided by the model. Some interesting results obtained are that for patients infected at the end of the period the hazard of transition from hospitalisation to ICU is significatively lower (p

Suggested Citation

  • Pedro C Álvarez-Esteban & Eustasio del Barrio & Oscar M Rueda & Cristina Rueda, 2021. "Predicting COVID-19 progression from diagnosis to recovery or death linking primary care and hospital records in Castilla y León (Spain)," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-14, September.
  • Handle: RePEc:plo:pone00:0257613
    DOI: 10.1371/journal.pone.0257613
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    References listed on IDEAS

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    1. Oscar M. Rueda & Stephen-John Sammut & Jose A. Seoane & Suet-Feung Chin & Jennifer L. Caswell-Jin & Maurizio Callari & Rajbir Batra & Bernard Pereira & Alejandra Bruna & H. Raza Ali & Elena Provenzano, 2019. "Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups," Nature, Nature, vol. 567(7748), pages 399-404, March.
    2. Hagai Rossman & Tomer Meir & Jonathan Somer & Smadar Shilo & Rom Gutman & Asaf Arie & Eran Segal & Uri Shalit & Malka Gorfine, 2021. "Hospital load and increased COVID-19 related mortality in Israel," Nature Communications, Nature, vol. 12(1), pages 1-7, December.
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