Digital proximity tracing on empirical contact networks for pandemic control
oleh: G. Cencetti, G. Santin, A. Longa, E. Pigani, A. Barrat, C. Cattuto, S. Lehmann, M. Salathé, B. Lepri
| Format: | Article |
|---|---|
| Diterbitkan: | Nature Portfolio 2021-03-01 |
Deskripsi
Digital contact tracing is increasingly considered as one of the tools to control infectious disease outbreaks, in particular the COVID-19 epidemic. Here, the authors present a modeling framework informed by empirical high-resolution contact data to analyze the impact of digital contact tracing apps.