COVID-19 Quarantine Measures Efficiency Evaluation by Best Tube Interval Data Envelopment Analysis

被引:0
作者
Demin S. [1 ]
机构
[1] National Research University Higher School of Economics, Institute of Control Sciences of Russian Academy of Sciences, Moscow
关键词
COVID-19; Data envelopment analysis; Efficiency evaluation; Interval data; Law-abidingness; Quarantine measures;
D O I
10.1007/s43069-023-00200-z
中图分类号
学科分类号
摘要
All countries have responded with a wide range of measures to stop the propagation of coronavirus. We apply best tube interval data envelopment analysis, in order to evaluate efficiency of quarantine measures using imprecise data. Using the Oxford COVID-19 Government Response Tracker’s (OxCGRT) data and given method, we construct time series of efficiency assessment of government responses to COVID-19. In addition, we separate all examined countries into several groups with similar patterns of quarantine measures efficiency. As a result, we highlight China and Vietnam as a benchmark for all other countries, because efficiency of these countries is high for almost whole period of research. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
引用
收藏
相关论文
共 16 条
  • [1] The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2, Nat Microbiol, 5, 4, pp. 536-544, (2020)
  • [2] Mishra S., Scott J.A., Laydon D.J., Et al., Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling, Sci Rep, 11, (2021)
  • [3] Dong E., Du H., Gardner L., An interactive web-based dashboard to track COVID-19 in real time, Lancet Inf Dis, 20, 5, pp. 533-534, (2020)
  • [4] Bermingham F., Wang O., China’s economy shrank for the first time since 1976 in first quarter., (2020)
  • [5] Aleskerov F., Demin S., An assessment of the impact of natural and technological disasters using a DEA approach, Dynamics of Disasters – Key Concepts, Models, Algorithms, and Insights., pp. 1-14, (2016)
  • [6] Ali I., Pant M., Rana U.S., Jauhar S.K., DEA for measuring the academic performance of a higher educational institute of Uttarakhand, India, International Journal of Computer Information Systems and Industrial Management Applications, 9, pp. 206-217, (2017)
  • [7] Sakouvogui K., Shaik S., Addey K.A., Cluster-adjusted DEA efficiency in the presence of heterogeneity: an application to banking sector, Open Economics, 3, 1, pp. 50-69, (2020)
  • [8] Farrell M.J., The measurement of productive efficiency, J Royal Stat Soc Ser a (General), 120, 3, pp. 253-290, (1957)
  • [9] Charnes A., Cooper W.W., Rhodes E., Measuring the efficiency of decision-making units, European Journal of Operations Research, 2, 6, pp. 429-444, (1978)
  • [10] Aleskerov F., Demin S., DEA for the assessment of regions’ ability to cope with disasters, Dynam Dis Imp Ris Resil Sol, 1, 2, pp. 31-37, (2021)