Abstract
The COVID-19 Epidemiological InvestigationSupport System (EISS) is a digital epidemiological tool, which utilizeslocation data from cellular base stations, credit card transactions records,and QR codes. It is a mass surveillance system that uses big data to track theentire infected population, featuring an extensive, automated, and speedyprocessing of data on personal location and the linkage of multiple databasesfrom various governmental agencies. Based on interviews with people who havedeveloped Korean digital epidemiology systems, this paper explores thetechnical, infrastructural, social, and institutional factors that have shapedKorean digital epidemiology since the 2014 avian flu crisis and examines theessential conditions of big data for digital epidemiology. The main findingsare as follows: The feasibility of EISS goes beyond the matter of privacy; itis closely connected to technological infrastructures such as a high density ofcellular base stations and private cloud systems; people’s behavior such as ahigh rate of smartphone and credit card usage; and new forms of governance andinstitutions for speedy data processing. Multiple database linkage woulddevelop EISS into a big data surveillance system that enables the prediction ofrisk-prone groups in a more preemptive manner.
Keywords: Digital epidemiology COVID-19 bigdata surveillance Korea
