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Article

Two-Way Contact Network Modeling for Identifying the Route of COVID-19 Community Transmission

1
Department of Forensics, Sungkyunkwan University, Seoul 03063, Korea
2
Capital Market Judiciary Enforcement Unit, Financial Supervisory Service, Seoul 07321, Korea
3
Department of Police Science, Korea National Police University, Asan 10050, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Antony Bryant
Received: 13 February 2021 / Revised: 17 March 2021 / Accepted: 22 March 2021 / Published: 25 March 2021
In this study, we address the problem originated from the fact that “The Corona 19 Epidemiological Research Support System,” developed by the Korea Centers for Disease Control and Prevention, is limited to analyzing the Global Positioning System (GPS) information of the confirmed COVID-19 cases alone. Consequently, we study a method that the authority predicts the transmission route of COVID-19 between visitors in the community from a spatiotemporal perspective. This method models a contact network around the first confirmed case, allowing the health authorities to conduct tests on visitors after an outbreak of COVID-19 in the community. After securing the GPS data of community visitors, it traces back to the past from the time the first confirmed case occurred and creates contact clusters at each time step. This is different from other researches that focus on identifying the movement paths of confirmed patients by forward tracing. The proposed method creates the contact network by assigning weights to each contact cluster based on the degree of proximity between contacts. Identifying the source of infection in the contact network can make us predict the transmission route between the first confirmed case and the source of infection and classify the contacts on the transmission route. In this experiment, we used 64,073 simulated data for 100 people and extracted the transmission route and a top 10 list for centrality analysis. The contacts on the route path can be quickly designated as a priority for COVID-19 testing. In addition, it is possible for the authority to extract the subjects with high influence from the centrality theory and use them for additional COVID-19 epidemic investigation that requires urgency. This model is expected to be used in the epidemic investigation requiring the quick selection of close contacts. View Full-Text
Keywords: COVID-19; contact network; route of transmission; social network analysis; centrality; clustering; forensic science; policing COVID-19; contact network; route of transmission; social network analysis; centrality; clustering; forensic science; policing
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MDPI and ACS Style

Lee, S.J.; Lee, S.E.; Kim, J.-O.; Kim, G.B. Two-Way Contact Network Modeling for Identifying the Route of COVID-19 Community Transmission. Informatics 2021, 8, 22. https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020022

AMA Style

Lee SJ, Lee SE, Kim J-O, Kim GB. Two-Way Contact Network Modeling for Identifying the Route of COVID-19 Community Transmission. Informatics. 2021; 8(2):22. https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020022

Chicago/Turabian Style

Lee, Sung J., Sang E. Lee, Ji-On Kim, and Gi B. Kim 2021. "Two-Way Contact Network Modeling for Identifying the Route of COVID-19 Community Transmission" Informatics 8, no. 2: 22. https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020022

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