February 12, 2020

Beyond R0: the importance of contact tracing when predicting epidemics

Category: Article Summary

Topic: Modeling and Prediction

• Hebert-Dufrense, et al. apply network theory to improve basic estimates of R0, using added information from the numeric heterogeneity of secondary infections – that is, the fact that some individuals create more secondary infections then others. 
• A range of predictions for the final size of the Wuhan 2019-nCoV epidemic is provided, using R0 estimates from early cases and SARS data for the underlying distribution of secondary cases. The resulting range, as a fraction of the total susceptible population, is 5%-40%. 
• With a high heterogeneity (e.g., transmission mostly maintained by “super-spreading” events), the epidemic is less likely to spread extensively and be easier to manage with contact tracing, screening and infection control 
• With low heterogeneity, containment strategies will likely fail, and pandemic of 2019-nCoV is likely.
• Overall, this network modeling approach highlights the need for contact tracing during emerging infectious disease outbreaks; and the need to look beyond R0 when predicting epidemic size.

Hebert-Dufrense L, et al. (Feb 11, 2020) Beyond R0: the importance of contact tracing when predicting epidemics. Pre-print. Accessed Feb 12 from https://www.medrxiv.org/content/10.1101/2020.02.10.20021725v1