Message-passing approach to epidemic tracing and mitigation with apps

With the hit of new pandemic threats, scientific frameworks are needed to understand the unfolding of the epidemic. The use of mobile apps that are able to trace contacts is of utmost importance in order to control new infected cases and contain further propagation. Here we present a theoretical approach using both percolation and message-passing techniques, to the role of contact tracing, in mitigating an epidemic wave. We show how the increase of the app adoption level raises the value of the epidemic threshold, which is eventually maximized when high-degree nodes are preferentially targeted. Analytical results are compared with extensive Monte Carlo simulations showing good agreement for both homogeneous and heterogeneous networks. These results are important to quantify the level of adoption needed for contact-tracing apps to be effective in mitigating an epidemic.

Automated summary

The use of mobile apps for contact tracing is crucial for controlling the spread of new pandemics. A theoretical approach combining percolation and message-passing techniques shows that increasing app adoption raises the epidemic threshold value, optimized by targeting high-degree nodes. Analytical results are in good agreement with Monte Carlo simulations, providing insight into the effectiveness of contact-tracing apps in mitigating epidemics.