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Perspectives on mathematical models applied to invasive virus diseases for animals

첫 페이지 보기
  • 발행기관
    강원대학교 산림과학연구소 바로가기
  • 간행물
    강원대학교 산림과학연구소 학술대회 바로가기
  • 통권
    2022 International symposium of Institute of Forest Science for the 40th Anniversary of College of Forest and Environment Science (2022.10)바로가기
  • 페이지
    pp.117-117
  • 저자
    Tae Soo Chon, Sang Jin Lim, Yeonsu Oh, Yung Chul Park
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A450487

원문정보

초록

영어
Due to environmental disturbance and human aggregation, alien species invade new area rapidly; especially disease expansion is critical due to high possibility of contagion and contamination. Since numerous factors including pathogens, hosts, environmental factors and human involvements are closely associated with disease transmission in a complex manner, mathematical models are required to predict disease dispersal objectively and provide optimal management strategies for disease control. Mathematical models are reviewed regarding virus diseases that have a strong possibility of invading in Korea, including Lumpy skins virus, Nipah virus and West Nile virus. With data-driven models, statistical models were used to determine disease occurrences and spatio-temporal distributions. Technics in machine learning (e.g., Maxent, genetic algorithm) were utilized to present associative properties and causality relationships between pathogens, hosts and environmental factors and to be able to predict disease outbreaks. Regarding mechanistic models, mathematical structure models were developed to present the quantitative framework of dynamical disease transmission between variables, for instance, susceptible, infected and recovered populations. The possibility of using simulation models (e.g., individual based models, lattice structure models) based on transmission rules applied to complex environmental and dispersal conditions is additionally discussed to identify risk factors, prognose disease occurrences and select optimal strategies for control management according to various scenarios.

키워드

Virus disease Epizootics Data-driven models Mechanistic models Disease transmission

저자

  • Tae Soo Chon [ Ecology and Future Research Institute, Busan 46228, Republic of Korea ] Corresponding Author
  • Sang Jin Lim [ Institute of Forest Science, Kangwon National University, Chuncheon 24341, Republic of Korea ]
  • Yeonsu Oh [ College of Veterinary Medicine & Institute of Veterinary Science, Kangwon National University, Chuncheon 24341, Republic of Korea ]
  • Yung Chul Park [ Division of Forest Science, Kangwon National University, Chuncheon 24341, Republic of Korea ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    강원대학교 산림과학연구소 [Institute of Forest Science Kangwon National University]
  • 설립연도
    1975
  • 분야
    농수해양>임학
  • 소개
    강원대학교부설산림과학연구소(이하 “연구소”라 한다)는 산림에 관한 제반 학술적 연구를 통하여 산림자원의 효용을 밝히고 임업 및 임산업의 발전에 기여함을 목적으로 한다.

간행물

  • 간행물명
    강원대학교 산림과학연구소 학술대회
  • 간기
    부정기
  • 수록기간
    2017~2024
  • 십진분류
    KDC 526 DDC 634

이 권호 내 다른 논문 / 강원대학교 산림과학연구소 학술대회 2022 International symposium of Institute of Forest Science for the 40th Anniversary of College of Forest and Environment Science

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