Modeling Indonesian COVID-19 Contact Tracing using Social Network Analysis

Abstract

As coronavirus SARS-CoV-2 emerged around the world, researchers are looking for the best method to decrease the spread. Testing, Tracing, Treatment, or 3T is a rule to control the pandemic COVID-19. However, 3T in Indonesia is still poor, testing capacity is still low as well as the tracing rate. This research aims to model the Indonesian Corona Virus spread from a small cluster in society. As the difficulty rises in acquiring real data, the data are synthetically generated, as well as its relationship. This paper applied Social Network Analysis with Network X, a Python library. The modeling method started with creating the graph and its community graph, then calculate the betweenness centrality to generate Page Rank based graph. This paper shows that the top 3 of the highest Page Rank is LUP with the value of 0.012356, MIH with 0.012035 points, and WAGP with 0.011824. The relationship between people impacts contacts tracing in the graph. The higher rank of a person, the higher chance he or she transmitted the virus or got infected by the virus.