Ontology highlight
ABSTRACT:
SUBMITTER: Golozar A
PROVIDER: S-EPMC7605581 | biostudies-literature | 2020 Oct
REPOSITORIES: biostudies-literature
Golozar Asieh A Lai Lana Yh LY Sena Anthony G AG Vizcaya David D Schilling Lisa M LM Huser Vojtech V Nyberg Fredrik F Duvall Scott L SL Morales Daniel R DR Alshammari Thamir M TM Abedtash Hamed H Ahmed Waheed-Ul-Rahman WU Alser Osaid O Alghoul Heba H Zhang Ying Y Gong Mengchun M Guan Yin Y Areia Carlos C Jonnagaddala Jitendra J Shah Karishma K Lane Jennifer C E JCE Prats-Uribe Albert A Posada Jose D JD Shah Nigam H NH Subbian Vignesh V Zhang Lin L Abrahão Maria Tereza Fernandes MTF Rijnbeek Peter R PR You Seng Chan SC Casajust Paula P Roel Elena E Recalde Martina M Fernández-Bertolín Sergio S Andryc Alan A Thomas Jason A JA Wilcox Adam B AB Fortin Stephen S Blacketer Clair C DeFalco Frank F Natarajan Karthik K Falconer Thomas T Spotnitz Matthew M Ostropolets Anna A Hripcsak George G Suchard Marc M Lynch Kristine E KE Matheny Michael E ME Williams Andrew A Reich Christian C Duarte-Salles Talita T Kostka Kristin K Ryan Patrick B PB Prieto-Alhambra Daniel D
medRxiv : the preprint server for health sciences 20201027
Early identification of symptoms and comorbidities most predictive of COVID-19 is critical to identify infection, guide policies to effectively contain the pandemic, and improve health systems' response. Here, we characterised socio-demographics and comorbidity in 3,316,107persons tested and 219,072 persons tested positive for SARS-CoV-2 since January 2020, and their key health outcomes in the month following the first positive test. Routine care data from primary care electronic health records ...[more]