COVID-19: Understanding the Disease Through Data
John Ioannidis, MD & Professor of Medicine at Stanford University and Luca Foschini, PhD, & Co-founder/Chief Data Scientist, Evidation Health discuss Understanding the Disease Through Data
About the Speakers
COVID-19: High Risks, High Prevalence, High-level Evidence, and High-stake Decisions
John Ioannidis, MD, DSc
Professor of Medicine, Stanford University
This presentation delineates efforts to understand the magnitude of risk conferred by COVID-19 and the gradient of risk across different populations and settings. It also presents data that to assess the prevalence of the infection, since many infected people are asymptomatic or have very limited symptoms (and thus are not tested). It also provides an overview of research on rigorous testing and evaluation of interventions against COVID-19 and the caveats thereof. Finally, Dr. Ioannidis addresses implications of emerging evidence for high-stake decisions.
Measuring COVID-19 and Influenza in the Real World via Person-Generated Health Data
Luca Foschini, PhD
Co-founder/Chief Data Scientist, Evidation Health
Dr. Foschini presents preliminary findings of an Evidation study, in collaboration with researchers at UW, UCSB, and the Bill & Melinda Gates Foundation, on 85K US participants with the goal of characterizing COVID-19 symptoms presentation in home settings, outside the clinic walls. He will explore longitudinal symptoms reports from 230 confirmed COVID-19 cases and compare those with 6.7k confirmed flu cases. This research identifies unique patterns of COVID-19 symptoms that display increased severity and duration as compared to flu.