Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps

摘要

The rapid spread of COVID-19 has demonstrated the need for accurate information to contain its diffusion. Technological solutions are a complement that can help citizens to be informed about the risk in their environment. Although measures such as contact traceability have been successful in some countries, their use raises society's resistance. This paper proposes a variation of the consensus processes in directed networks to create a risk map of a determined area. The process shares information with trusted contacts: people we would notify in the case of being infected. When the process converges, each participant would have obtained the risk map for the selected zone. A consensus simulation has been introduced in an SEIR model to evaluate how having available a risk map could affect the virus's propagation. The scenario chosen is La Gomera Island: a region where the Spanish government has tested its contact tracing app (RadarCOVID). The paper also compares both strategies joint and separately: contact tracing to detect potential infections, and risk maps to avoid movements into conflictive areas. Contact tracing apps could work with 40% of participants instead of 60%. On the other hand, the elaboration of risk maps could work with just a 20% of active installations. Nevertheless, the effect is to delay the propagation instead of reducing the contagion. With both strategies actives, we significantly reduce infected peoples with a relatively low participant number.