Earticle

초록

영어

Emerging of global infectious diseases threat to worldwide induced numerous patients through person to person infection. In previous study, we investigated effects of traveling nationwide using expressway data on the spread of H1N1 influenza virus in Korea during 2009–2010. As a result, influenza epidemic patterns of the 2009 were correlated with some region traffic flow. In this study, we focused on Seoul which region is a highest density of population in Korea. Also using system dynamics-based simulation of the spread of an infectious disease in each of the 25 districts in Seoul was performed. Consequently, the decrease in the number of infected people in the district with a large floating population size was more significant than that with a high population density. This study is meaningful as it visualized the number of infected people on the map, which includes actual geographical information and the changes over time in the number of individuals that belong to S, I, and R classes of population. Also mathematical model based on Korea unique traffic and population movement information could be used. These results can be applying additional population and traffic data in the future, and support making decisions when establishing an effective infectious disease control strategy.

목차

Abstract
 1. Introduction
 2. Materials and Methods
  2.1. Epidemiological System Dynamics Modeling
  2.2. Epidemic Scenario using Floating Population Data and Census Data
  2.3. Simulation of Infectious Disease Spread in Seoul using AnyLogic
 3. Results
  3.1. Calculated Contact Rate using Floating Population Data in Seoul
  3.2. Infectious Disease Spreading Simulation in Seoul
 4. Discussion and Conclusions
 References

키워드

저자

• Jinhwa Jang [ Biomedical Prediction Technology Laboratory, Korea Institute of Science and Technology Information, Korea / Laboratory of Computational Biology and Bioinformatics,Graduate School of Public Health, Seoul National University, Korea ]
• Insung Ahn [ Biomedical Prediction Technology Laboratory, Korea Institute of Science and Technology Information, Korea / Dept. of Big Data Science, University of Science & Technology, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605