A social network analysis of COVID-19 transmission in Rosales, Pangasinan, Philippines

In this study, we use social networks to analyze the spread of Coronavirus Disease (COVID-19) in Rosales, Pangasinan, Philippines. The igraph package of the software R was used to create network graphs and analyze the node and edge attributes. The nodes represent the infected individuals, and the edges represent the directed links from sources to target patients. We apply three centrality measures: degree, closeness, and betweenness centrality, to identify patterns and characteristics of primary nodes that caused the majority of the infections in the municipality. Out of the seventy-eight cases recorded from 23 March 2020 to 27 December 2020, 42.3% are in the age range (20, 40]. The average age of infected individuals is 43 years with a standard deviation of 21. However, all the deaths occurred in older patients. Only four health workers were infected, all of whom are isolated cases. There were twenty-eight isolated cases, while the number of contacts per patient (outdegree) is 0.53. About a third of the cases have travel history from different provinces or countries, and 64.1% of them are sources of infections. Almost half of the infected individuals are symptomatic. Among the identified central cases, 70% have no travel history, and 60% are asymptomatic. This study further demonstrates the importance of effective contact tracing and isolation protocols to reduce the spread of COVID-19. © 2022 Author(s).