Storytelling on COVID-19 Impact Using Experts' Prior Knowledge and Data from Social Media, Official Clinical Data, Digital Phenotype from Smartphones' Raw Sensor Data, and Emergency Departments — Invited Papers
International Society for Bayesian Analysis (ISBA), IMS, Royal Statistical Society, Caucus for Women in Statistics
Organizer(s): Kerrie Mengersen, Queensland University of Technology
Chair(s): TBD TBD, TBD
3:35 PM
Predicting the Impact of COVID-19 on the Emergency Departments in Lombardy, Italy
Antonietta Mira, Università della Svizzera italiana and University of Insubria; Giulia Ghilardi, Istituto di Ricerche Farmacologiche Mario Negri IRCCS; Greta Carrara, Istituto di Ricerche Farmacologiche Mario Negri IRCCS; Angela Andreella, University of Insubria; Spyros Balafas, University of Insubria; Fabrizio Ruggeri, CNR IMATI ; Ernst C Wit, Universita della Svizzera italiana; Livio Finos, University of Padova; Guido Bertolini, Laboratory of clinical epidemiology; Giovanni Nattino, Istituto di Ricerche Farmacologiche Mario Negri IRCCS
Fusing Tweets, Confirmed Cases, and Death Data to Accurately Now-Cast for COVID-19 Conor Michael Rosato, University of Liverpool; Matthew Carter, University of Liverpool; Robert Moore, University of Liverpool; John Heap, University of Liverpool; Simon Maskell, University of Liverpool; Jose Storopoli, UNINOVE - Sao Paulo - Brazil
