| A Study on Data-Based Efficient Response to Livestock Infectious Diseases (Year 1 of 2) | |||
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| Author | Kim, Hyunjoong | ||
| Views | 15693 | Publication Date | 2023.03.20 |
| Original | |||
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Background and Purpose ○The outbreak of contagious animal diseases, including highly pathogenic avian influenza (HPAI), food-and-mouth disease (FMD), and African swine fever (ASF), increases fiscal spending due to disease control measures and causes various forms of social and economic damage such as unbalanced supply and demand for livestock products, environmental pollution at burial sites, and the people’s inconvenience from disease control activities. Therefore, it is necessary to implement disease control policies that can minimize the damage. The purpose of this first-year study is to present measures to improve the disease control system in order to efficiently respond to contagious animal diseases through a data-based analysis of HPAI outbreak and spread types. Research Methodology ○First, to identify the current state and causes of HPAI outbreaks at home and abroad, we referred to materials and reports provided by the government and international organizations. Second, based on statistics and policy materials related to livestock production, this study analyzed the effects of HPAI outbreaks, including changes in social welfare, and computed recovery periods after slaughter by reviewing literature and legislations. Third, we analyzed poultry rearing density through the geographic information system (GIS) program by using data collected from the poultry traceability system; and commissioned a survey firm to conduct a survey of poultry farms and analyzed the survey results. Fourth, tasks for improving the HPAI control system were derived by reviewing legislations, literature, and the government’s countermeasures and guidelines. Fifth, we commissioned an expert to write a manuscript in order to research the disease control systems in Japan and the U.S. and draw implications from them. Sixth, we analyzed cases that used smart livestock farms’ information to establish a HPAI monitoring system; and spatio-temporal correlations of HPAI-infected farms through GIS. Seventh, a joint study was carried out to analyze the outbreak probability and spread risk of HPAI. We adopted a machine learning method for outbreak risk and the SIR model for spread risk, and collected data for analysis from related institutions. (For more information, please refer to the report.) |
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