Reconciling early-outbreak preliminary estimates of the basic reproductive number and its uncertainty: a new framework and applications to the novel coronavirus (2019-nCoV) outbreak
Sang Woo Park, David Champredon, David J.D. Earn, Michael Li, Joshua S. Weitz, Bryan T. Grenfell, Jonathan Dushoff
doi: https://doi.org/10.1101/2020.01.30.20019877
This article is a preprint and has not been peer-reviewed [what does this mean?]. It reports new medical research that has yet to be evaluated and so should not be used to guide clinical practice.
Abstract
A novel coronavirus (2019-nCoV) has recently emerged as a global threat. As the epidemic progresses, many disease modelers have prioritized estimating the basic reproductive number Ro, defined as the average number of secondary cases caused by a primary case. While these efforts are extremely valuable, their modeling approaches and the resulting estimates vary widely. Here, we present a framework for comparing different estimates of Ro across a wide range of models by decomposing it into three key quantities (the exponential growth rate r, the mean generation interval G, and the generation-interval dispersion kappa) and apply our framework to early estimates of Ro for the 2019-nCoV outbreak. Our results emphasize the importance of propagating uncertainties in all three quantities, in particular in the shape of the generation-interval distribution. While rapid response during an outbreak can be valuable, avoiding over-confidence is also important. Modelers should work with field-workers to develop better methods for characterizing generation intervals.
