1. Modeling the effect of exposure notification and non-pharmaceutical interventions on COVID-19 transmission in Washington state
- Author
-
Paul Eastham, Yusef Shafi, Austin Wu, Robert Hinch, Anel Nurtay, Michael V. McConnell, Neo Wu, Lucie Abeler-Dörner, Luyang Liu, Matt Rosencrantz, Zhao Cheng, Shawn O'Banion, Christophe Fraser, Michael Dikovsky, Matthew Abueg, David Bonsall, and William J. M. Probert
- Subjects
Coronavirus disease 2019 (COVID-19) ,Epidemiology ,Computer applications to medicine. Medical informatics ,Internet privacy ,R858-859.7 ,Psychological intervention ,Medicine (miscellaneous) ,Health Informatics ,030501 epidemiology ,Article ,law.invention ,Exposure Notification ,03 medical and health sciences ,0302 clinical medicine ,Health Information Management ,law ,030212 general & internal medicine ,Implementation ,business.industry ,Health policy ,Computer Science Applications ,Transmission (mechanics) ,Work (electrical) ,State (computer science) ,0305 other medical science ,business ,Contact tracing - Abstract
Contact tracing is increasingly used to combat COVID-19, and digital implementations are now being deployed, many based on Apple and Google’s Exposure Notification System. These systems utilize non-traditional smartphone-based technology, presenting challenges in understanding possible outcomes. In this work, we create individual-based models of three Washington state counties to explore how digital exposure notifications combined with other non-pharmaceutical interventions influence COVID-19 disease spread under various adoption, compliance, and mobility scenarios. In a model with 15% participation, we found that exposure notification could reduce infections and deaths by approximately 8% and 6% and could effectively complement traditional contact tracing. We believe this can provide health authorities in Washington state and beyond with guidance on how exposure notification can complement traditional interventions to suppress the spread of COVID-19.
- Published
- 2021
- Full Text
- View/download PDF