Anatomy of digital contact tracing: Role of age, transmission setting, adoption, and case detection

The efficacy of digital contact tracing against coronavirus disease 2019 (COVID-19) epidemic is debated: Smartphone penetration is limited in many countries, with low coverage among the elderly, the most vulnerable to COVID-19. We developed an agent-based model to precise the impact of digital contact tracing and household isolation on COVID-19 transmission. The model, calibrated on French population, integrates demographic, contact and epidemiological information to describe exposure and transmission of COVID-19. We explored realistic levels of case detection, app adoption, population immunity, and transmissibility. Assuming a reproductive ratio R = 2.6 and 50% detection of clinical cases, a ~20% app adoption reduces peak incidence by ~35%. With R = 1.7, >30% app adoption lowers the epidemic to manageable levels. Higher coverage among adults, playing a central role in COVID-19 transmission, yields an indirect benefit for the elderly. These results may inform the inclusion of digital contact tracing within a COVID-19 response plan.This study was partially supported by the ANR project DATAREDUX (ANR-19-CE46-0008-01) to A.B., V.C., and P.-Y.B.; EU H2020 grants MOOD (H2020-874850) to V.C., C.P., and P.-Y.B. and RECOVER (H2020-101003589) to V.C.; the Municipality of Paris (www.paris.fr/) through the program Emergence(s) to J.A.M.L., B.A.G., P.B., F.P., and C.P.; the ANR and Fondation de France through the project NoCOV (00105995) to P.-Y.B. and C.P.; the Spanish Ministry of Science and Innovation to J.A.M.L. and B.A.G.; the AEI and FEDER (EU) under the grant PACSS (RTI2018-093732-B-C22) J.A.M.L. and B.A.G.; and the Maria de Maeztu program for Units of Excellence in R&D (MDM-2017-0711) to J.A.M.L. and B.A.G.Peer reviewe