A Social Network Analysis of COVID-19 Transmission Models in Taiwan: Two Epidemic Waves in 2020-2021

Abstract

The COVID-19 pandemic has made a profound global impact. As it rages on around the globe, social network researchers have been involved in exploring key factors of rapid infection and transmission. For Taiwan, it is thus worthy of exploring the differences between the transmission models of the two epidemic waves in 2020-2021 for any insight that may have been overlooked. In this study, the social network analysis is adopted for revealing any unforeseen threats of infection. In the first wave, 652 confirmed cases were reported from January 21, 2020, to November 30, 2020. In the second wave, 880 confirmed cases were reported from May 03, 2021, to May 17, 2021. The infection source attribute, i.e., local vs. imported, made the transmission models to be structured differently between the first and the second wave. In the first wave, it was found that a community outbreak could easily happen when one node got infected without knowing when and where the transmission occurred. In contrast, in the second wave, it was found that the gender attribute was more effective than the age attribute in quickly identifying the differences in the transmission models among all the confirmed cases.