Journal of the Korea Society for Simulation (한국시뮬레이션학회논문지)

The Korea Society for Simulation (한국시뮬레이션학회)
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Agent-Based COVID-19 Simulation Considering Dynamic Movement: Changes of Infections According to Detect Levels

동적 움직임 변화를 반영한 에이전트 기반 코로나-19 시뮬레이션: 접촉자 발견 수준에 따른 감염 변화

  • Lee, Jongsung (Department of Industrial and Management Engineering at Korea National University of Transportation)
  • Received : 2020.12.13
  • Accepted : 2021.01.12
  • Published : 2021.03.31
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Abstract

Since COVID-19 (Severe acute respiratory syndrome coronavirus type 2, SARS-Cov-2) was first discovered at the end of 2019, it has spread rapidly around the world. This study introduces an agent-based simulation model representing COVID-19 spread in South Korea to investigate the effect of detect level (contact tracing) on the virus spread. To develop the model, related data are aggregated and probability distributions are inferred based on the data. The entire process of infection, quarantine, recovery, and death is schematically described and the interaction of people is modeled based on the traffic data. A composite logistic functions are utilized to represent the compliance of people to the government move control such as social distancing. To demonstrate to effect of detect level on the virus spread, detect level is changed from 0% to 100%. The results indicate active contact tracing inhibits the virus spread and the inhibitory effect increases geometrically as the detect level increases.

2019년 말 코로나19(중증급성 호흡기 증후군 코로나 바이러스 타입 2)가 발견된 이후로 전세계적으로 퍼져나가고 있다. 본 연구에서는 접촉자 발견 수준이 바이러스 전파에 미치는 영향을 파악하기 위해서 현재 대한민국의 코로나19 전파 상황을 반영한 에이전트 기반 시뮬레이션 모델을 소개한다. 본 연구에서는 실제적인 시뮬레이션 모델 개발을 위해 대한민국 내 관련 데이터를 수집하고 그 확률분포를 추정하였다. 감염, 격리, 회복, 사망의 전체 감염 프로세스를 도식화하였으며 사람들의 상호작용을 교통량 데이터를 기반으로 하여 모델링 하였다. 사회적 거리 두기 같은 정부 시책에 대한 사람들의 순응도를 반영하기 위해 합성 로지스틱 함수를 활용하였다. 접촉자 발견 수준에 따른 감염 양상 변화를 파악하기 위해 발견 수준을 0%에서 100%까지 변화 시켰다. 그 결과 적극적인 접촉자 추적이 바이러스 확산을 효과적으로 제한하고 제한의 효과가 접촉자 발견 수준이 증가함에 따라 기하급수적으로 증가하는 것을 확인하였다.

Keywords

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