코로나바이러스감염증-19의 시공간적 확산 패턴 및 지역 간 감염 네트워크 분석 = Spatiotemporal Evolution and the Diffusion Pattern of COVID-19 in South Korea in Three Waves

다국어 초록 (Multilingual Abstract)

This study aims to uncover cross-district transmission patterns of COVID-19 outbreaks in South Korea in three waves. To this end, a total of 93,755 reported cases that local governments published online were firstly mapped and analyzed the spatial diffusion patterns using ArcMap 10.5. Secondly, network analyses method was employed to discover the directions of transmission as well as the relationships between urban hierarchy and transmission patterns of the virus in three waves. In network analysis, 28,365 cases, that contain information of both origin and destination of individual cases, were analyzed and visualized using Gephi. The analyses unveiled the differences among three outbreak waves in their transmission scales, speed, and directions. At an overall level, the Seoul Metropolitan Areas (SMA) found to be the super-spreader and instrumental in spreading the virus throughout the pandemic. But the second and third waves were more diverse and heterogeneous while the transmission of the first wave was concentrated around the SMA. Districts with over 1 million population found to have contributed to widespread and rapid transmission of the virus. The findings of this study contribute to developing and deploying area-specific prevention and intervention measures against future epidemics.

국문 초록 (Abstract)

본 논문의 목적은 코로나19 발생지 자료를 토대로 유행 시기별 코로나19의 공간적 확산 패턴과 방향성을 분석하는 것이다. 기존 연구와 달리 코로나19 발생지를 기준으로 감염병이 시간이 흐를수록 공간적으로 어떻게 확산되는지, 주요 역할을 하는 지역이 어디인지, 각 지역 간 영향력이 어떻게 되는가 등을 살펴보았다. 그 결과 코로나19는 서울 및 수도권을 중심으로 인접성과 연결성에 따라 공간적으로 확산되었으며, 3차 유행으로 갈수록 코로나19 확산의 범위와 빈도, 속도가 빨라졌다. 또한 팬데믹 초기에는 서울 및 수도권이 코로나19 확산에 가장 큰 역할을 하였으나, 시간이 지날수록 이러한 역할이 지방 대도시로 확산되면서 보다 산발적인 감염이 일어난 것으로 확인되었다. 이는 팬데믹 상황이 장기화될수록 코로나19 전파 통로가 다양하지고 도시 간 전파 역시 늘어나 특정 지역에 초점을 맞춘 방역에 한계가 있을 수 있음을 시사한다. 또한 지역 위계별로 인구 규모가 큰 지역일수록 코로나19 유출입 빈도가 높아 확산에 중요한 역할을 하였으며, 지역 간 전파에 있어서도 매개지역이 된 것으로 나타났다. 이는 수도권과 지방으로 이분화된 방역 조치가 도시의 규모와 타 지역과의 연결성 등을 토대로 보다 세분화되어야 함을 알려준다.

참고문헌 (Reference)

1 박수은, "코로나바이러스감염증-19의 바이러스(SARS-CoV-2) 특징, 전파 및 임상 양상" 대한소아감염학회 27 (27): 1-10, 2020

2 장진화, "코로나바이러스감염증-19 국내 주요 집단발생 1년간특징" 14 (14): 482-495, 2021

3 "코로나바이러스감염증-19"

4 허중연, "코로나바이러스감염병-19 초기 유행의 임상 역학적 특성" 대한내과학회 95 (95): 67-73, 2020

5 이진희, "지역적 건강불평등과 개인 및 지역수준의 건강결정요인" 한국보건사회연구원 36 (36): 345-384, 2016

6 이진희, "수도권 지역 코로나바이러스감염증-19 발생 시기별 감염경로 다이나믹스" 한국보건사회연구원 41 (41): 7-26, 2021

7 박선엽, "벡터매개 질병(vector-borne diseases) 공간역학을 중심으로 한 보건지리학의 최근 연구" 대한지리학회 47 (47): 677-699, 2012

8 최병두, "메르스 사태의 지리학과 생명권력의 정치" 한국공간환경학회 25 (25): 175-194, 2015

9 김상조, "도시정책 전환기의 도시기본계획제도 개선을 위한 운용실태 분석 연구" 국토연구원 2012

10 이진희, "감염병 대응을 위한 공간정책과제" 국토연구원 2020

11 Jacques Teller, "Urban density and Covid-19: towards an adaptive approach" Ubiquity Press, Ltd. 2 (2): 150-165, 2021

12 Liu, Y., "Uncovering transmission patterns of COVID-19 outbreaks: A region-wide comprehensive retrospective study in Hong Kong" 100929-, 2021

13 Fortaleza, C. M., "The use of health geography modeling to understand early dispersion of COVID-19 in São Paulo, Brazil" 16 (16): e0245051-, 2021

14 Richard C. Jones, "The spatial diffusion of covid-19 in Texas" Informa UK Limited 1-14, 2021

15 Lee Jin Hui, "The selection of compact city policy instruments and their effects on energy consumption and greenhouse gas emissions in the transportation sector: The case of South Korea" 37 : 116-124, 2018

16 Diego F. Cuadros, "Spatiotemporal transmission dynamics of the COVID-19 pandemic and its impact on critical healthcare capacity" Elsevier BV 64 : 102404-, 2020

17 Kim, S., "Spatiotemporal pattern of COVID-19 and government response in South Korea (as of May 31, 2020)" 98 : 328-333, 2020

18 Peter Congdon, "Spatiotemporal Frameworks for Infectious Disease Diffusion and Epidemiology" MDPI AG 13 (13): 1261-, 2016

19 Hornsby, K, "Spatial diffusion: conceptualizations and formalizations. documento de trabajo del National Center for Geographic Information and Analysis and the Department of Spatial Information Science and Engineering" University of Maine

20 Golub, A., "Spatial diffusion of the HIV/AIDS epidemic: Modeling implications and case study of AIDS incidence in Ohio" 25 (25): 85-100, 1993

21 Cliff, A. D., "Spatial Diffusion: an Historical Geography of Epidemics in an Island Community" Cambridge University Press 1981

22 Cao, K., "Spatial - temporal epidemiology of tuberculosis in mainland China: an analysis based on Bayesian theory" 13 (13): 469-477, 2016

23 S. Saraswathi, "Social network analysis of COVID-19 transmission in Karnataka, India" Cambridge University Press (CUP) 148 : 2020

24 Wasserman, S., "Social Network Analysis:Methods and applications" Cambridge University Press 1994

25 Lai, C. C., "Severe acute respiratory syndrome coronavirus 2 and coronavirus disease-2019: The epidemic and the challenges" 55 (55): 105924-, 2020

26 Zhu, D., "Revealing the spatial shifting pattern of COVID-19 pandemic in the United States. Scientific Reports 11"

27 Zindoga Mukandavire, "Quantifying early COVID-19 outbreak transmission in South Africa and exploring vaccine efficacy scenarios" Public Library of Science (PLoS) 15 (15): e0236003-, 2020

28 DeFries, R., "Post-lockdown spread of COVID-19 from cities to vulnerable forest-fringe villages in Central India" 119 (119): 52-58, 2020

29 Mao, Y., "Notifiable respiratory infectious diseases in China: a spatial - temporal epidemiology analysis" 17 (17): 2301-, 2020

30 Liu, J., "Network analysis of population flow among major cities and its influence on COVID-19 transmission in China" 112 : 103138-, 2021

31 Adler, P., "Mega regions and pandemics" 111 (111): 465-481, 2020

32 Kang Hao Cheong, "Introducing the 21st Century's New Four Horsemen of the Coronapocalypse" Wiley 42 (42): 2000063-, 2020

33 Yi, H., "Health equity considerations in COVID-19: geospatial network analysis of the COVID-19outbreak in the migrant population in Singapore" 28 (28): 159-, 2021

34 Fruchterman, T. M., "Graph drawing by force‐directed placement" 21 (21): 1129-1164, 1991

35 Bastian, M., "Gephi: an open source software for exploring and manipulating networks" 3 (3): 361-362, 2009

36 Joel Hellewell, "Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts" Elsevier BV 8 (8): e488-e496, 2020

37 Warf, B, "Encyclopedia of Geography 1" SAGE Publications, Inc 2950-2951, 2010

38 Kucharski, A. J., "Early dynamics of transmission and control of COVID-19: a mathematical modelling study" 20 (20): 553-558, 2020

39 Shima Hamidi, "Does Density Aggravate the COVID-19 Pandemic?" Informa UK Limited 86 (86): 495-509, 2020

40 Giovanni A. Rabino, "Comprendre les structures spatiales à partir de données de réseaux : considérations théoriques et applications" OpenEdition 1997

41 Ayoub, H. H., "Characterizing key attributes of the epidemiology of COVID-19 in China : Model-based estimations" 2 : 100042-, 2020

42 Sabel, C. E., "A Companion to Health and Medical Geography" Blackwell Publishing Ltd. 111-132, 2010