Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic

Abstract

Background: The coronavirus pandemic (COVID-19) has spread worldwide via international travel. This study traced its diffusion from the global to national level and identified a few superspreaders that played a central role in the transmission of this disease in India. Data and methods: We used the travel history of infected patients from 30 January to 6 April 6 2020 as the primary data source. A total of 1386 cases were assessed, of which 373 were international and 1013 were national contacts. The networks were generated in Gephi software (version 0.9.2). Results: The maximum numbers of connections were established from Dubai (degree 144) and the UK (degree 64). Dubai’s eigenvector centrality was the highest that made it the most influential node. The statistical metrics calculated from the data revealed that Dubai and the UK played a crucial role in spreading the disease in Indian states and were the primary sources of COVID-19 importations into India. Based on the modularity class, different clusters were shown to form across Indian states, which demonstrated the formation of a multi-layered social network structure. A significant increase in confirmed cases was reported in states like Tamil Nadu, Delhi and Andhra Pradesh during the first phase of the nationwide lockdown, which spanned from 25 March to 14 April 2020. This was primarily attributed to a gathering at the Delhi Religious Conference known as Tabliqui Jamaat. Conclusions: COVID-19 got induced into Indian states mainly due to International travels with the very first patient travelling from Wuhan, China. Subsequently, the contacts of positive cases were located, and a significant spread was identified in states like Gujarat, Rajasthan, Maharashtra, Kerala and Karnataka. The COVID-19’s spread in phase one was traced using the travelling history of the patients, and it was found that most of the transmissions were local.