Social network analysis as a tool of Social Work in the face of COVID 19

Abstract

Scientific consensus indicates that the best way to slow the spread of COVID 19 is by tracing the contacts of infected people. This measure has a social nature, since it seeks to analyze people’s networks to detect early who is at risk of being infected, alert them and impose quarantine, a measure of social isolation that prevents the potential spread. So far, much has been said about which professionals should perform this screening but Little about how it should be done. In this article, in the first place, it is defined what tracking is, which professionals are best prepared for the use of scientific methodologies that support tracking word. From the scientific literature that analyzes how socialization affects the spread, a simulation is developed on how COVID 19 can spread during the social interactions of people in their different areas of socialization. On this simulation, social network analysis and certain algorithms for community detection and cohesion analysis are used to show the suitability of these methodologies for tracking. The results show that with the support of social network analysis and certain algorithms, key information about communities formed in the network structure and who are the super-propagators and intermediaries between the detected communities is accessed early. This can help prioritize contacting these people to cut the chains of community transmission. Finally, we discuss the suitability for Social Work professionals to be trained in these methodologies in order to develop this tracking work.