Document Type : Research Paper
Authors
1 Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Iran.
2 Department of Industrial Engineering, Golpayegan University of Technology, Golpayegan, Iran.
3 Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran.
Abstract
There have been several major global outbreaks during the past decades, with the latest being the worst. The COVID-19 pandemic has infected hundreds of thousands and killed thousands in the world affecting most countries in around the globe. Outbreak response management efficiency can have a major impact on the outcome of the pandemic. Therefore, in this paper, the performance of most seriously affected countries regarding contagion control and medical treatment of COVID-19 is evaluated using data envelopment analysis. The efficiency values are calculated based on the conditions of the countries and the number of confirmed cases in the first step in order to create a basis for analysis according to the contagion control. In the second step the performance evaluation is done considering the total number of confirmed cases, the death cases, and the recovered cases to evaluate the efficiency of medical treatment in the countries. The countries are also classified into four groups using area chart, and for each group, some suggestions and analyses are presented. The results show the performance of the countries regarding the contagion control and medical treatment.
Keywords
- COVID-19
- SARS-CoV-2
- Outbreak response management
- Efficiency evaluation
- Contagion
- Medical treatment
- Data envelopment analysis
Main Subjects
Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins
and receptor binding. The Lancet, 395(10224), 565-574.
[2] Liu, Y., Gayle, A.A., Wilder-Smith, A., Rocklöv, J.(2020). The reproductive number of COVID-19
is higher compared to SARS coronavirus. Journal of travel medicine, 27(2), taaa02.
[3] World Health Organization, (2020, 2020/14/03). Coronavirus disease 2019 (COVID-19) Situation
Report –68.
[4] Riou, J., Althaus, C.L.(2020). Pattern of early human-to-human transmission of Wuhan 2019 novel
coronavirus (2019-nCoV), December 2019 to January 2020. Eurosurveillance, 25(4), pii2000058.
[5] Jouzdani, J., Shirouyehzad, H.(2020). Fight against COVID-19: what can be done in the case of
Iran?, Journal of Applied Research on Industrial Engineering, 7(1), 1-12.
[6] Jouzdani, J.(2020). Fight against COVID-19: A global outbreak response management performance
view. Journal of Project Management, 5(1).
[7] Sheps, C.G., Wagner, E.H., Schonfeld, W.H., DeFriese, G.H., Bachar, M., Brooks, E., Gillings,
D.B., Guild, P.A., Konrad, T.R., McLaughlin, C.P.(1983). An evaluation of subsidized rural primary
care programs: I. A typology of practice organizations. American journal of public health, 73(1), 38-
49.
[8] World Health Organization, (2019). Compliance with the International Health Regulations
Estimates by Country.
[9] United Nations Statistics Division,(2020). Population density and urbanization.
[10] Villa, G., Lozano, S.(2004). A constant sum of outputs DEA model for Olympic Games target
setting. In: 4th International Symposium on DEA. Proceedings of the 4th International Symposium on
DEA, Aston University,P36.
[11] Farrell, M.J.(1957). The measurement of productive efficiency. Journal of the Royal Statistical
Society: Series A (General), 120(3), 253-281.
[12] Charnes, A., Cooper, W.W., Rhodes, E.(1978). Measuring the efficiency of decision making units.
European journal of operational research, 2(6), 429-444.
[13] Kabnurkar, A.(2001). Mathematical modeling for data envelopment analysis with fuzzy
restrictions on weights. Virginia Tech.
[14] Banker, R.D., Charnes, A., Cooper, W.W.(1984). Some models for estimating technical and scale
inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
[15] Khodabakhshi, M., Asgharian, M.,(2009). An input relaxation measure of efficiency in stochastic
data envelopment analysis. Applied Mathematical Modelling 33(4), 2010-2023.
)