Topology-Aware Optimisation of Vaccination Strategy for Minimising Virus Spreading
Vaccination is currently the primary way for mitigating the COVID-19 outbreak without severe lockdown. Despite its importance, the available number of vaccines worldwide is insufficient, and the production rates are hard to be increased in a short time. Therefore, vaccination needs to follow strict prioritization criteria. In this regard, almost all countries have prioritized similar classes of exposed workers: healthcare professionals and the elderly obtaining to maximize the survival of patients and years of life saved. Nevertheless, the virus is currently spreading at high rates, and any prioritization criterion so far adopted did not show to account for the topology of the contact networks. We consider that a network in which nodes are people while the edges represent their contacts may model the virus's spreading efficiently. In such a model, it is already known that spreading may be efficiently stopped by disconnecting the network, i.e., by vaccinating more central or relevant nodes, therefore, eliminating "bridge edges". Consequently, we introduce such a model and discuss the use of a topology-aware versus an age-based vaccination strategy.