Algorithm, model, methods of COVID-19
Recorded On: 12/03/2020
Living systematic benefit-risk assessments for COVID-19 treatments: Establishing a dynamic framework for rapid decision-making
We aimed to review both the benefits and the risks for several proposed COVID-19 treatments in severe disease using a living systematic benefit risk assessment based on currently available data, to strengthen the ongoing monitoring of the benefit-risk balance.
Miranda Davies, Drug Safety Research Unit, Southampton, United Kingdom
Comparing Methodologies to Predict Incidence of COVID-19 in US Counties
The spread of SARS-CoV-2 globally led to stringent governmental measures to prevent it. As lockdowns are being eased, models to evaluate potential infection resurgence are important.
Shimonee Shah/Paul Coplan, Johnson and Johnson, New Brunswick, NJ, USA
Validation of claims-based algorithms to identify hospitalized COVID-19 events within the Sentinel System
During the COVID-19 pandemic, observational data provides timely insight into the natural history of the disease, risk factors, and treatments. While claims databases can provide population-based information for COVID-19 research, they often lack access to laboratory results, the gold standard for COVID-19 diagnosis.
Sheryl Kluberg, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
A COVID-19 epidemiologic model to enhance trial efficiency through evidence-based site selection for SARS-COV-2 vaccine trials
Due to local variability in COVID-19 outbreaks, an epidemiological model capable of predicting intensity of new COVID-19 cases over time at the level of a vaccine trial site’s catchment population is needed to inform site selection.
Debra Schaumberg, London School of Economics and Political Sciences, Evidera