A network Data Envelopment Analysis to estimate nations' efficiency in the fight against SARS-CoV-2

Area of Science:

• Public Health
• Health Economics
• Network Analysis

Background:

• The COVID-19 pandemic has strained global health systems, necessitating efficient national response strategies.
• Measuring country-specific pandemic response efficiency is crucial for informing policy and improving outcomes.
• Existing analyses often lack a comprehensive, multi-stage approach to evaluating pandemic management.

Purpose of the Study:

• To develop and apply a network Data Envelopment Analysis (DEA) model for assessing the efficiency of 55 countries' COVID-19 responses.
• To identify best practices in pandemic management by highlighting high-efficiency nations.
• To provide actionable insights for improving national COVID-19 strategies worldwide.

Main Methods:

• A network DEA model with a series structure of five stages: population, contagion, triage, hospitalization, and intensive care unit admission.
• Incorporation of both input minimization (financial perspective) and output maximization (social perspective) orientations.
• Inclusion of health costs, personal protective equipment usage, infected population, COVID-19 recoveries, and COVID-19 deaths as key variables.

Main Results:

• Estonia, Iceland, Latvia, Luxembourg, the Netherlands, and New Zealand emerged as countries with the highest mean system efficiencies in their COVID-19 response.
• A statistically significant correlation was observed between larger national populations and lower mean efficiency scores.
• The study provides a novel cross-country efficiency measurement framework for pandemic response.

Conclusions:

• The identified high-efficiency countries offer valuable models for national COVID-19 strategy adaptation.
• Policy-makers should examine and adopt strategies from leading nations to enhance pandemic preparedness and response.
• Addressing population size as a factor may be critical for optimizing future pandemic management efforts.