Assessment of regional vulnerability to Africa swine fever in China during 2018/8‐2019/7 based on data envelopment analysis method

Abstract

In this study, we introduce a vulnerability index to measure the regional ASF epidemic and present the ASF severity ratings of the 31 provinces of mainland China.The index is defined based on the data from the investigation, national statistical yearbook and reports. The data to be used include pig breeding, financial resources, human resources, epidemic information of ASF and price fluctuation from the 31 provinces. Then, we use the data envelopment analysis (DEA) method to define the vulnerability index, the relative severity value for each region, which quantitatively reflects the damage degree caused by the epidemic of ASF. The method allows us to provide a systematic classification for the regional vulnerability level of ASF in China.Using this index, we find that the vulnerability of the whole country is at a high level, and there is no regional aggregation phenomenon. The vulnerability level of the 31 provinces is quite different and the provinces with high vulnerability level are dispersive geographically. For the five major prevention and control zones for ASF in China, the northern region has the highest vulnerability level, while the eastern zoon level is the lowest.

Benchmarking of COVID-19 testing facilities: a case in the Philippines

“…Hunt and Klima (2020) used DEA for the measurement of disaster recovery efficiency of electric power restoration. Li et al (2020b) assessed the regional vulnerability of China to swine fever using DEA. Hong and Mwakalonge (2020) used DEA in the design of a biofuel logistics network.…”