Today, only two methods are viable to immunize people against an epidemic spreading: vaccine and quarantine, but a prolonged quarantine extended to the whole population implies unsustainable costs, while vaccinations take a lot of time. Nevertheless, it would be possible to stop the propagation of viruses and alleviate the economic activities lockdown greatly, vaccinating or quarantining only a small percentage of the population using well-known methodologies to select people to immunize. From a practical point of view, it is necessary to provide the social or relational national network, which will constitute the spectral graph analysis, our primary methodological tool. This requires to generate a graph of many nodes (people) and links (relations, of any kind) mapping the whole population. The connections are extracted from the national register, media, web resources, cellular phones and any other source, possibly after an anonymizing step. The procedure is inherently dynamic since relations and people geo-localization change continuously; therefore, a real-time update must be implemented. Fortunately, internet data collection mechanisms can provide vast information to support the update step. Once the National Relation Network is available, individuals that could propagate more dangerously the infection (which is subtly different from propagating to more people the infection) will be identified quickly and immunized with high priority. A careful selection of these individuals may stop or slow down the spreading, safeguarding at the same time, the economic system. Likewise, the National Relational Network can directly indicate the subjects hit financially by the epidemic without additional computational costs. Moreover, the Graph theory usage will allow applying its numerous, impressive achievements to the epidemic containment. We warn that no real experiment has been conducted on a large scale, so no evidence is available; however theoretical demonstrations and computer simulations are encouraging. Finally, we do not intend to present a formal treatment of the issue or foster academic discussions; instead, we propose a practical approach to the epidemic spreading problem. © Springer Nature Switzerland AG 2021.

cited By 0; Conference of 15th International Conference on Universal Access in Human-Computer Interaction, UAHCI 2021, held as part of the 23rd International Conference, HCI International 2021 ; Conference Date: 24 July 2021 Through 29 July 2021; Conference Code:262029