About: Time between Symptom Onset, Hospitalisation and Recovery or Death: a Statistical Analysis of Different Time-Delay Distributions in Belgian COVID-19 Patients

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About: Time between Symptom Onset, Hospitalisation and Recovery or Death: a Statistical Analysis of Different Time-Delay Distributions in Belgian COVID-19 Patients Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Time between Symptom Onset, Hospitalisation and Recovery or Death: a Statistical Analysis of Different Time-Delay Distributions in Belgian COVID-19 Patients
Creator	Piérard, Denis Bossuyt, Nathalie Abrams, S Aouachria, Amir-Samy Bafort, Kristof Beckhoven, Van Belkhir, Leïla Colombie, Vincent Cooreman, Sarah Dauby, Nicolas De Munter, Paul Deblonde, Jessika Delmarcelle, Didier Delvallee, Mélanie Demeester, Rémy Dugernier, Thierry Faes, C Goethem, Nina Holemans, Xavier Kerzmann, Benjamin Machurot, Pierre Minette, Philippe Minon, Jean-Marc Mokrane, Saphia Nachtergal, Catherine Noirhomme, Séverine Praet, Jens Rossi, Camelia Schirvel, Carole Sermijn, Erica Staelens, Frank Triest, Filip Vanhoenacker, Anke Willems, Elise Wyndham-Thomas, Chloé
Source	MedRxiv
abstract	Background There are different patterns in the COVID-19 outbreak in the general population and amongst nursing home patients. Different age-groups are also impacted differently. However, it remains unclear whether the time from symptom onset to diagnosis and hospitalization or the length of stay in the hospital is different for different age groups, gender, residence place or whether it is time dependent. Methods Sciensano, the Belgian Scientific Institute of Public Health, collected information on hospitalized patients with COVID-19 hospital admissions from 114 participating hospitals in Belgium. Between March 14, 2020 and June 12, 2020, a total of 14,618 COVID-19 patients were registered. The time of symptom onset, time of COVID-19 diagnosis, time of hospitalization, time of recovery or death, and length of stay in intensive care are recorded. The distributions of these different event times for different age groups are estimated accounting for interval censoring and right truncation in the observed data. Results The truncated and interval-censored Weibull regression model is the best model for the time between symptom onset and diagnosis/hospitalization best, whereas the length of stay in hospital is best described by a truncated and interval-censored lognormal regression model. Conclusions The time between symptom onset and hospitalization and between symptom onset and diagnosis are very similar, with median length between symptom onset and hospitalization ranging between 3 and 10.4 days, depending on the age of the patient and whether or not the patient lives in a nursing home. Patients coming from a nursing home facility have a slightly prolonged time between symptom onset and hospitalization (i.e., 2 days). The longest delay time is observed in the age group 20-60 years old. The time from symptom onset to diagnosis follows the same trend, but on average is one day longer as compared to the time to hospitalization. The median length of stay in hospital varies between 3 and 10.4 days, with the length of stay increasing with age. However, a difference is observed between patients that recover and patients that die. While the hospital length of stay for patients that recover increases with age, we observe the longest time between hospitalization and death in the age group 20-60. And, while the hospital length of stay for patients that recover is shorter for patients living in a nursing home, the time from hospitalization to death is longer for these patients. But, over the course of the first wave, the length of stay has decreased, with a decrease in median length of stay of around 2 days.
has issue date	2020-07-21(xsd:dateTime)
bibo:doi	10.1101/2020.07.18.20156307
has license	medrxiv
sha1sum (hex)	6213dd85547902d54b957f9c5e3f95d5220f8a5b
schema:url	https://doi.org/10.1101/2020.07.18.20156307
resource representing a document's title	Time between Symptom Onset, Hospitalisation and Recovery or Death: a Statistical Analysis of Different Time-Delay Distributions in Belgian COVID-19 Patients
resource representing a document's body	covid:6213dd85547902d54b957f9c5e3f95d5220f8a5b#body_text
is schema:about of	named entity 'groups' named entity 'data' named entity 'gender' named entity 'DISTRIBUTIONS' named entity 'OUTBREAK' named entity 'EVENT' named entity 'IMPACTED' named entity 'SYMPTOM ONSET' named entity 'DEPENDENT' named entity 'residence' named entity 'observed' named entity 'nursing' named entity 'population' named entity 'accounting' named entity 'event' named entity 'symptom' named entity 'general population' named entity 'length of stay' named entity 'nursing home' named entity 'COVID-19' named entity 'Belgian' named entity 'Belgian' named entity 'symptom' named entity 'BIC' named entity 'symptom' named entity 'infection' named entity 'Weibull distribution' named entity 'nursing homes' named entity 'symptom' named entity 'likelihood function' named entity 'nursing home' named entity 'symptom' named entity 'COVID' named entity 'Weibull distribution' named entity 'lognormal distribution' named entity '15.6' named entity 'statistical analysis' named entity 'ICU' named entity 'symptom' named entity 'nursing homes' named entity 'symptom' named entity 'COVID-19 outbreak' named entity 'healthcare systems' named entity 'lognormal distribution' named entity 'nosocomial' named entity 'Weibull distribution' named entity 'sensitivity analysis' named entity 'nursing homes' named entity 'ICU' named entity 'long-term' named entity 'standard deviation'

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