To identify sources of the success and failure of COVID-19 control measures and develop best-practice public health policy in mitigating the spread of COVID-19, this paper aims to evaluate the efficiency of various combinations of government COVID-19 control measures among OECD countries. This paper also identifies which factors critically influence the efficiency of COVID-19 control measures.
This paper employed two-stage network SBM (slacks-based measure of efficiency) models with variable returns-to-scale and constant returns-to-scale, respectively, among various forms of data envelopment analysis (DEA) models. As a post hoc analysis, the authors used Tobit regression for examining the causal relationship between a nation's cultural dimensions and its COVID-19 control measure's efficiency scores.
The authors found that the pervasive less individualistic and higher uncertainty avoiding culture positively influenced the efficient control of COVID-19 outbreaks since such a culture helped the government impose its mandatory COVID-19 control measures without people's strong resistance to those measures.
Many public health policymakers are wondering why COVID-19 control measures are not effective in coping with the COVID-19 outbreaks. This paper helps the government find the most efficient combination of COVID-19 controls measures for curbing the spread of the stubborn coronavirus. This paper is one of the first attempts to identify pandemic risk mitigation factors from a cultural perspective.
