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Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic.
J Travel Med. 2020 12 23; 27(8)JT

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.

Authors+Show Affiliations

School of Basic Sciences, Indian Institute of Technology Mandi, Mandi 175075, Himachal Pradesh, India.School of Basic Sciences, Indian Institute of Technology Mandi, Mandi 175075, Himachal Pradesh, India.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32776124

Citation

Azad, Sarita, and Sushma Devi. "Tracking the Spread of COVID-19 in India Via Social Networks in the Early Phase of the Pandemic." Journal of Travel Medicine, vol. 27, no. 8, 2020.
Azad S, Devi S. Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic. J Travel Med. 2020;27(8).
Azad, S., & Devi, S. (2020). Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic. Journal of Travel Medicine, 27(8). https://doi.org/10.1093/jtm/taaa130
Azad S, Devi S. Tracking the Spread of COVID-19 in India Via Social Networks in the Early Phase of the Pandemic. J Travel Med. 2020 12 23;27(8) PubMed PMID: 32776124.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic. AU - Azad,Sarita, AU - Devi,Sushma, PY - 2020/05/24/received PY - 2020/07/22/revised PY - 2020/08/04/accepted PY - 2020/8/11/pubmed PY - 2021/1/21/medline PY - 2020/8/11/entrez KW - COVID-19 KW - Delhi religious conference KW - Indian states KW - international travels KW - local transmission KW - mass gathering KW - superspreading event JF - Journal of travel medicine JO - J Travel Med VL - 27 IS - 8 N2 - 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. SN - 1708-8305 UR - https://www.unboundmedicine.com/medline/citation/32776124/Tracking_the_spread_of_COVID_19_in_India_via_social_networks_in_the_early_phase_of_the_pandemic_ L2 - https://academic.oup.com/jtm/article-lookup/doi/10.1093/jtm/taaa130 DB - PRIME DP - Unbound Medicine ER -