Development of agent-based simulation model for infectious disease transmission

• 발행기관: 한국예방수의학회
• 저자명: Jun-Hee Han Inho Hong Jaehoon Kim Min-Gyu Yoo Myeongsu Yoo Dae Sung Yoo
• 간행물 정보: 『Journal of Preventive Veterinary Medicine』Vol.49, No.2, 71~76쪽, 전체 6쪽
• 주제분류: 의약학 > 기타의약학
• 파일형태: PDF
• 발행일자: 2025.06.30

국문 초록

The emergence and re-emergence of infectious diseases pose ongoing threats to public health. This study aims to develop an agent-based simulation model (ABM) to predict the spread of novel infectious diseases during early outbreak phases and evaluate the effectiveness of control measures, specifically focusing on the impact of interventions such as maskwearing, vaccination, and social distancing on outbreak dynamics and the reduction of symptomatic cases. Using demographic and COVID-19 outbreak data from South Korea, we constructed a detailed contact network model encompassing workplaces, schools, households, and communities. Using demographic and COVID-19 outbreak data from Seoul, South Korea, we constructed a detailed contact network model encompassing workplaces, schools, households, and communities. Key transmission parameters were inferred using Approximate Bayesian Computation. The resulting ABM platform, implemented in a C-based R package, allows for flexible scenario simulation involving 56 adjustable parameters, including mask-wearing, vaccination coverage, and social distancing. Simulation outputs demonstrated the model’s capacity to reproduce observed transmission patterns in workplace and school outbreaks, enabling public health authorities to anticipate outbreak dynamics and assess interventions. This framework provides a valuable decision-support tool for controlling future infectious disease incursions.

목차

INTRODUCTION

MATERIALS AND METHODS

RESULTS

DISCUSSION

REFERENCES

키워드

Agent-based model Infectious disease transmission Contact network Early response Intervention