Alliance for Pandemic Preparedness
May 26, 2020
Visualizing the Invisible: The Effect of Asymptomatic Transmission on the Outbreak Dynamics of COVID-19
Category: Article Summary
Topic: Modeling and Prediction
- [pre-print, not peer reviewed] Peirlinck et al. used reported symptomatic case data, antibody seroprevalence studies, a mathematical epidemiology model, and a Bayesian framework to infer the epidemiological characteristics of COVID-19 and predict Rt. This approach found outbreak dynamics to be sensitive to Rt, the ratio of symptomatic to asymptomatic populations, and the infectious periods of both groups.
- For three locations for which seroprevalence data are available, this model estimated the proportion of the population that has been infected and recovered by May 13 to be 6.2% (Santa Clara, CA), 22.7% (New York, NY) and 20.5% Heinsberg (Germany).
Peirlinck et al. (May 26, 2020). Visualizing the Invisible: The Effect of Asymptomatic Transmission on the Outbreak Dynamics of COVID-19. Pre-print downloaded May 26 from https://doi.org/10.1101/2020.05.23.20111419