Abstract
We study how homophily of human physical interactions affects the efficacy of digital proximity tracing. Analytical results show a non monotonous dependence of the reproduction number with respect to the mixing rate between individuals that adopt the contact tracing app and the ones that do not. Furthermore, we find regimes in which the attack rate has local optima, minima or monotonously varies with the mixing rate. We corroborate our findings with Monte Carlo simulations on a primary-school network. This study provides a mathematical basis to better understand how homophily in health behavior shapes the dynamics of epidemics.
Highlights
Preventing disease outbreaks is one of the greatest challenges humanity has faced in its history [1]
We study how homophily of human physical interactions affects the impact of digital proximity tracing on the epidemic evolution
Analytical and numerical results show the existence of different dynamical regimes with respect to the mixing rate between adopters and nonadopters, revealing a rich phenomenology in terms of the reproduction number as well as the attack rate
Summary
Preventing disease outbreaks is one of the greatest challenges humanity has faced in its history [1]. Analytical and numerical results show the existence of different dynamical regimes with respect to the mixing rate between adopters and nonadopters, revealing a rich phenomenology in terms of the reproduction number as well as the attack rate. In the absence of an intervention, i.e., app adoption, and assuming homogeneous mixing, the basic reproduction number of the disease is given by R0 = βk.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
