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Enregistrement W3034249744 · doi:10.1101/2020.06.12.20129619

COVID-19 infections among Healthcare Workers and Transmission within Households

2020· preprint· en· W3034249744 sur OpenAlexaffabout
Kevin L. Schwartz, Camille Achonu, Sarah A. Buchan, Kevin A. Brown, Brenda Lee, Michael Whelan, Julie H. Wu, Gary Garber

Notice bibliographique

RevuemedRxiv · 2020
Typepreprint
Langueen
DomainePsychology
ThématiqueCOVID-19 and Mental Health
Établissements canadiensOttawa HospitalPublic Health OntarioUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineHealth careCoronavirus disease 2019 (COVID-19)Transmission (telecommunications)AsymptomaticCross-sectional studyPublic healthEnvironmental healthPopulationPandemicDiseaseFamily medicineInfectious disease (medical specialty)NursingPathology

Résumé

récupéré en direct d'OpenAlex

Abstract Importance Protecting healthcare workers (HCWs) from COVID-19 is a priority to maintain a safe and functioning healthcare system. The risk of transmitting COVID-19 to family members is a source of stress for many. Objective To describe and compare HCW and non-HCW COVID-19 cases in Ontario, Canada, as well as the frequency of COVID-19 among HCWs’ household members. Design, Setting, and Participants Using reportable disease data at Public Health Ontario which captures all COVID-19 cases in Ontario, Canada, we conducted a population-based cross-sectional study comparing demographic, exposure, and clinical variables between HCWs and non-HCWs with COVID-19 as of 14 May 2020. We calculated rates of infections over time and determined the frequency of within household transmissions using natural language processing based on residential address. Exposures and Outcomes We contrasted age, gender, comorbidities, clinical presentation (including asymptomatic and presymptomatic), exposure histories including nosocomial transmission, and clinical outcomes between HCWs and non-HCWs with confirmed COVID-19. Results There were 4,230 (17.5%) HCW COVID-19 cases in Ontario, of whom 20.2% were nurses, 2.3% were physicians, and the remaining 77.4% other specialties. HCWs were more likely to be between 30-60 years of age and female. HCWs were more likely to present asymptomatically (8.1% versus 7.0%, p=0.010) or with atypical symptoms (17.8% versus 10.5%, p<0.001). The mortality among HCWs was 0.2% compared to 10.5% of non-HCWs. HCWs commonly had exposures to a confirmed case or outbreak (74.1%), however only 3.1% were confirmed to be nosocomial. The rate of new infections was 5.5 times higher in HCWs than non-HCWs, but mirrored the epidemic curve. We identified 391 (9.8%) probable secondary household transmissions and 143 (3.6%) acquisitions. Children < 19 years comprised 14.6% of secondary cases compared to only 4.2% of the primary cases. Conclusions and Relevance HCWs represent a disproportionate number of COVID-19 cases in Ontario but with low confirmed numbers of nosocomial transmission. The data support substantial testing bias and under-ascertainment of general population cases. Protecting HCWs through appropriate personal protective equipment and physical distancing from colleagues is paramount. Key Points Question What are the differences between healthcare workers and non-healthcare workers with COVID-19? Findings In this population-based cross-sectional study there were 4,230 healthcare workers comprising 17.5% of COVID-19 cases. Healthcare workers were diagnosed with COVID-19 at a rate 5.5 times higher than the general population with 0.8% of all healthcare workers, compared to 0.1% of non-healthcare workers. Meaning High healthcare worker COVID-19 burden highlights the importance of physical distancing from colleagues, appropriate personal protective equipment, as well as likely substantial testing bias and under-ascertainment of COVID-19 in the general population.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,171
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,115
Tête enseignante GPT0,414
Écart entre enseignants0,299 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations26
Publié2020
Routes d'admission2
Résumé présentoui

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