Assessing the Efficiency of Contagion Control and Medical Treatment for COVID-19 in OECD Countries Using Data Envelopment Analysis

Ana Martins and David Sousa

Chapter 5 in Handbook on Data Envelopment Analysis in Business, Finance, and Sustainability:Recent Trends and Developments, 2024, pp 147-192 from World Scientific Publishing Co. Pte. Ltd.

Abstract: The disease caused by the coronavirus (COVID-19) was one of the most significant health problems worldwide. The World Health Organization declared the event a global public health emergency in late January 2020 and then declared it a global pandemic in March 2020. The impressive and rapid spread of the virus was unprecedented and surpassed all expectations. With nearly every country in the world infected, the challenge of containing the virus became increasingly serious. The main objective of this study is to explore the potential of using data envelopment analysis (DEA) to establish international comparisons on the efficiency of implementing programs to fight the COVID-19 pandemic, thus allowing for the identification of a set of good practices. To do this, data from 18 countries belonging to the Organization for Economic Co-operation and Development were used to assess the efficiency of infection control and medical treatment, models A and B, respectively. The results indicate that there is a notable variation in efficiency, suggesting that a better use of resources could prevent the spread of the virus and high mortality. The most efficient countries for both models are Slovenia and Latvia. Less efficient countries were Denmark, Iceland, and Switzerland in the control of infection and Germany, Austria, and Switzerland in medical treatment. These results also demonstrate the potential strategic role of the DEA methodology for the efficient and effective planning of scarce resources to fight the pandemic.

Keywords: Data Envelopment Analysis; Business; Finance; Banking; Accounting; Sustainability; Efficiency; Performance; Productivity; Total Factor Productivity; Frontier Analysis (search for similar items in EconPapers)
JEL-codes: C44 C5 (search for similar items in EconPapers)
Date: 2024
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