The Covid-19 pandemic hit the world, took many lives and had devastating effects on the words economy. While organizations scrambled to prepare the vaccine, countries imposed lockdowns and quarantines on citizens to prevent the spread of the virus. Covid-19 is a highly communicable virus, so it would very rapidly spread across communities and groups. Governments were quick to realize that if you look at a single or group of people as a node, you could treat the issue of minimizing spread as a social networking problem. If people represented nodes, then the contacts they made would be the edges in the graph. The more people you interact with daily, the higher your degree as a node would be. Then betweenness can also be calculated as the number of groups you intermediate. If we wanted to minimize the spread of a virus in our graph, using an algorithm such as Girvan-Newman to isolate and therefore remove the most communicable nodes would pre-emptively limit the spread of the virus?
The first challenge in preparing such a network, however, would be data collection. Governments worked together with Apple and Google to develop new contact-tracing firmware that allowed your mobile device to create exposure notifications. It would, to abridge the process, store an adjacency list on your device to keep track of the nodes you interact with. Each time your phone came in proximity to another, they would exchange proximity keys, and that information was used to build social exposure networks. Governments could then use this information to tell people if they had been near someone who later tested positive for Covid-19, and so they could take the necessary precautions. This system was not perfect, however, as there were still privacy concerns around how this data would be used and whether people would opt-in to such a program. Another issue was that while this system could be used to alert people of possible exposure, it couldn’t do anything to prevent further spread once an infection had occurred. The next step would be, as suggested above, pre-emptive isolation of nodes with stronger betweenness. This would however raise some serious ethical concerns, as some people would be isolated even if they had not contracted the virus yet.
The combination of social networking analysis and graph theory proved effective in minimizing the spread of Covid-19. By identifying high-risk individuals and groups early on, we can pre-emptively take measures to isolate them and stop the virus from spreading further.