한국ITS학회 논문지 (The Journal of The Korea Institute of Intelligent Transport Systems)

  • 제21권4호
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  • Pages.78-95
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  • 2022
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  • 1738-0774(pISSN)
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  • 2384-1729(eISSN)
한국ITS학회 (The Korea Institute of Intelligent Transport Systems)
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가축관련 운송차량 통행 데이터를 이용한 가축전염병 확산 예측모형 개발

Development of Predicting Model for Livestock Infectious Disease Spread Using Movement Data of Livestock Transport Vehicle

  • 강웅 (고려대학교 일반대학원 산업경영공학과) ;
  • 홍정열 (계명대학교 도시학부 교통공학과) ;
  • 정희현 (한국개발연구원 공공투자관리센터) ;
  • 박동주 (서울시립대학교 교통공학과)
  • Kang, Woong (Dept. of Industrial and Management Engineering, Korea University) ;
  • Hong, Jungyeol (Dept. of Transportation Engineering, Keimyung University) ;
  • Jeong, Heehyeon (Public and Private Infrastructure Investment Management Center, Korea Development Institute) ;
  • Park, Dongjoo (Dept. of Transportation Engineering, University of Seoul)
  • 투고 : 2022.04.14
  • 심사 : 2022.07.06
  • 발행 : 2022.08.31
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초록

아프리카 돼지열병, 구제역 등 가축전염병 유행과 관련된 기존의 연구 결과에서 가축전염병 확산의 주요 원인으로 축산 관련 차량 통행을 지목하는 경우가 많다. 이에 본 연구는 경기도 내 축산시설의 차량 방문이력 데이터와 화물차량의 디지털 운행기록계 데이터를 결합하여 각 읍면동의 주중 축산 화물차량 OD 통행량을 구한 후, 이에 기반한 가축전염병 확산 예측모형을 개발하였다. 모형은 2015년 1~2월 당시 주차별 구제역 발병기록을 이용하여 훈련되었으며, 긍정적 시나리오 기준으로 검증용 감염 표본 13개의 감염을 모두 예측해내는 데에 성공했다.

The result of previous studies and epidemiological invstigations for infectious diseases epidemic in livestock have shown that trips made by livestock-related vehicles are the main cause of the spread of these epidemics. In this study, the OD traffic volume of livestock freight vehicle during the week in each zone was calculated using livestock facility visit history data and digital tachograph data. Based on this, a model for predicting the spread of infectious diseases in livestock was developed. This model was trained using zonal records of foot-and-mouth disease in Gyeonggi-do for one week in January and February 2015 and in positive, it was succesful in predicting the outcome in all out of a total 13 actual infected samples for test.

키워드

과제정보

본 연구는 국토교통부 교통물류연구개발사업의 연구비지원(21TLRP-B148680-04)에 의해 수행되었습니다. 본 논문은 정희현·홍정열·박동주의 한국ITS학회 논문지 제19권 제6호에 게재되었던 논문, 「빅데이터 기반 가축관련 운송차량 이동경로 분석을 통한 가축전염병 노출수준 평가」를 수정·보완하여 작성하였습니다.

참고문헌

  1. Cheung, E., Bera, A., Kubin, E., Gray, K. and Manocha, D.(2018), "Identifying driver behaviors using trajectory features for vehicle navigation", IEEE International Conference on Intelligent Robots and Systems.
  2. Ferguson, N. M., Donelly, C. A. and Anderson, R. M.(2010), "The Foot-and-Mouth epidemic in Great Bratain: Pattern of Spread and Impact of Interventions", Science, vol. 292, pp.1155-1160. https://doi.org/10.1126/science.1061020
  3. Firth, D.(1993), "Bias Reduction of maximum likelihood estimates", Biometrika, vol. 80, pp.27-28. https://doi.org/10.1093/biomet/80.1.27
  4. Gho, K.(2018), Livestock infectious disease, Korea Institute of S&T Evaluation and Planning.
  5. Gregor, M.(2007), "The long haul: Risks associated with livestock transport", Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science, vol. 5, no. 4, pp.301-312. https://doi.org/10.1089/bsp.2007.0028
  6. Guinat, C., Relun, A., Wall, B., Morris, A., Dixon, L. and Pfeiffer, D. U.(2016), "Exploring pig trade patterns to inform the design of risk-based disease surveillance and control strategies", Science Reports, vol. 6, 28429.
  7. Jeong, H., Hong, J. and Park, D.(2021), "A Framework of an integrated livestock vehicle trajectory database using digital tachograph data", Sustainability, vol. 13, no. 5, 2694.
  8. Kim, H., Ko, T., Park, N. and Lee, W.(2014), "Comparison of Bias Correction Methods for the Rare Event Logistic Regression", The Korean Journal of Applied Statistics, vol. 27, no. 2, pp.277-290. https://doi.org/10.5351/KJAS.2014.27.2.277
  9. Korea Law Information Center, https://www.law.go.kr/LSW/admRulLsInfoP.do?admRulSeq=2100000182438, 2022.02.16.
  10. Korea Rural Economic Institute(2016), Research for the causes of foot-and-mouth disease in 2014-2015 and on measures to improve the quarantine system. (in Korean)
  11. Lee, G. J., Park, S. I., Lee, K. N., Kim, H. Y., Park, J. H. and Hong, S. J.(2018), "Hub Facilities in Vehicle Movement Network between Livestock Facilities", Journal of the Korea Academia-Industrial Cooperation Society, vol. 19, no. 6, pp.137-146. https://doi.org/10.5762/KAIS.2018.19.6.137
  12. Lee, Y. J., Shin, M. S., Yoon, H. J., Jang, W. S., Hwang, S. C., Kim, Y. J., Jeong, J. W. and Lee, S. J.(2010), "Epidemiological characteristics about introduction and transmission of foot-and-mouth disease in republic of Korea in January 2010", Journal of Preventive Veterinary Medicine, vol. 34, no. 3, pp.203-201.
  13. Liu, L., Zhong, Y., Ao, S. and Wu, H.(2019), "Exploring the relevance of green space and epidemic diseases based on panel data in China from 2007 to 2016", Environmental Research and Public Health, vol. 16, no. 14, 2551.
  14. Lowe, J., Gauger, P., Harmon, K., Zhang, J., Connor, J., Yeske, P., Loula, T., Levis, I., Dufresne, L. and Main, R.(2014), "Role of transportation in spread of porcine epidemic diarrhea virus infection, United States", Emerging Infectious Diseases, vol. 20, no. 5, p.872.
  15. Mansour, S. M., Ali, H., Chase, C. C. and Cepica, A.(2015), "Loop-mediated isothermal amplification for diagnosis of 18 World Organization for Animal Health (OIE) notifiable viral diseases of ruminants, swine and poultry", Animal Health Research Review, vol. 16, no. 2, pp.89-106. https://doi.org/10.1017/S1466252315000018
  16. Mweu, M. M., Fournie, G., Halasa, T., Toft, N. and Nielsen, S. S.(2013), "Temporal characterisation of the network of Danish cattle movements and its implication for disease control: 2000-2009", Preventive Veterinary Medicine, vol. 110, pp.379-387. https://doi.org/10.1016/j.prevetmed.2013.02.015
  17. Paju City(2020), White paper on African Swine Fever in Paju City, pp.26-27.
  18. Shirley, M. D. F. and Rushton, S. P.(2005), "Where diseases and networks collide: Lessons to be learnt from a study of the 2001 foot-and-mouth disease epidemic", Epidemiology & Infection, vol. 133, pp.1023-1032. https://doi.org/10.1017/S095026880500453X