Spatial Analysis of Health System Factors in Infectious Disease Management: Lessons Learned from the COVID-19 Pandemic in Korea

Abstract

Infectious disease outbreaks present ongoing and substantial challenges to health systems at local, national, and global levels, testing their preparedness, response capabilities, and resilience. This study aimed to identify and analyze critical health system-level factors that influence infection outbreaks, focusing on the experience of the COVID-19 pandemic in Korea. Conducted as a secondary data analysis, this study utilized national datasets from Korea. Given the inherent spatial dependencies in the spread of infectious diseases, we employed a spatial lag model to analyze data. While city-specific characteristics did not emerge as significant factors, health system variables, particularly the number of community health centers and health budgets, showed significant influence on the course of the COVID-19 outbreak, along with spatial autocorrelation coefficients. Our findings underscore the importance of enhancing public healthcare infrastructure, considering regional specificities, and promoting collaboration among local governments to bolster preparedness for future outbreaks. These insights are crucial for policymakers and healthcare professionals in formulating effective strategies to prevent, manage, and mitigate the impact of infectious disease outbreaks.