earticle

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.