The Birth of Digital Epidemiology in South Korea

Abstract

The COVID-19 Epidemiological Investigation Support System (EISS) is a digital epidemiological tool, which utilizes location data from cellular base stations, credit card transactions records, and QR codes. It is a mass surveillance system that uses big data to track the entire infected population, featuring an extensive, automated, and speedy processing of data on personal location and the linkage of multiple databases from various governmental agencies. Based on interviews with people who have developed Korean digital epidemiology systems, this paper explores the technical, infrastructural, social, and institutional factors that have shaped Korean digital epidemiology since the 2014 avian flu crisis and examines the essential conditions of big data for digital epidemiology. The main findings are as follows: The feasibility of EISS goes beyond the matter of privacy; it is closely connected to technological infrastructures such as a high density of cellular base stations and private cloud systems; people’s behavior such as a high rate of smartphone and credit card usage; and new forms of governance and institutions for speedy data processing. Multiple database linkage would develop EISS into a big data surveillance system that enables the prediction of risk-prone groups in a more preemptive manner.

Keywords:

• Digital epidemiology
• COVID-19
• big data
• surveillance
• Korea

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1 There is a tradeoff between privacy protection and data utility for digital epidemiology (Tarkoma et al. 2020): low privacy infringement leads to the poor accuracy of digital epidemiology (Mittelstadt et al. 2018).

2 “Surveillance creep” refers to data being used for other purposes without sunset procedures after epidemiological investigations.

3 The project was based on the tradition of the developmental state, that is, “technological developmentalism.” It implies the Korean government encourages new technological innovation and economic growth by supporting private companies (Kim 2018).

4 The Personal Information Protection Act was established in 2011 after a series of scandals regarding the leak of personal information from private companies such as Auction in 2008. The penalty in the act became stricter after several credit card and telecommunication companies leaked personal information of clients in 2014 (Lee 2020).

5 Based on this project, KT has developed a Global Epidemic Prevention Platform (GEPP) that tracks infectious diseases occurring overseas. The GEPP project drew the attention of international bodies such as the UN, the Davos Forum, and the G-20 from 2016 to 2018. From KT’s perspective, GEPP can not only create international cooperation and prevention of infectious diseases, but also overseas investment in developing countries. KT received an investment of about 120 billion won from the Bill & Melinda Gates Foundation in 2020. With the Foundation’s support, KT is developing an artificial intelligence-based early diagnosis algorithm for infectious diseases (Lee 2020). Since 2018, KT has encouraged the establishment of GEPP projects in Asian countries such as Malaysia, Cambodia, and Laos, as well as Kenya, Ghana, and other African countries (I-8).

6 Despite the concerns of political activists, EISS is not likely to result in automated decision-making by replacing traditional epidemiology, at least in the near future, as epidemiological investigators remain the decision-makers. This is consistent with previous findings on digital epidemiology (Bansal et al. 2016; Salathé et al. 2012; Simonsen et al. 2016).

7 The conventional idea of privacy is based on Western liberal individualism (Gilliom 2001). While there is no doubt that privacy is vital for the ethics of public health surveillance (Fairchild and Bayer 2004), critiques of surveillance that just focus on “the invasion of privacy” may be simplistic and limited from the post-colonialist perspective, let alone the political economy perspective (Gilliom 2001).

Additional information

Funding

This work was supported by National Research Foundation of Korea: [Grant Number NRF-2020S1A5A2A01040236].

Notes on contributors

Eun-Sung Kim

Eun-Sung Kim is a professor in the Department of Sociology at Kyung Hee University, Seoul, Republic of Korea. His recent interest includes the politics of big data and algorithms in governance associated with public health, environment, and policing. His works related to COVID-19 surveillance have appeared in Social Science and Medicine and Critical Policy Studies. In 2022, he published two books (in Korean): Policy and Society and Senses and Things: A New Code to Read Korean Society.