Precision Mapping of COVID-19 Vulnerable Locales by Epidemiological and Socioeconomic Risk Factors, Developed Using South Korean Data

• Main Authors: Bayarmagnai Weinstein, Alan R. da Silva, Dimitrios E. Kouzoukas, Tanima Bose, Gwang-Jin Kim, Paola A. Correa, Santhi Pondugula, YoonJung Lee, Jihoo Kim, David O. Carpenter
• Format: Article
• Language: English
• Published: MDPI AG 2021-01-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: COVID-19; pandemics; socioeconomic factors; spatial regression; South Korea
• Online Access: https://www.mdpi.com/1660-4601/18/2/604
• ISSN: 1661-7827; 1660-4601

COVID-19 has severely impacted socioeconomically disadvantaged populations. To support pandemic control strategies, geographically weighted negative binomial regression (GWNBR) mapped COVID-19 risk related to epidemiological and socioeconomic risk factors using South Korean incidence data (January 20, 2020 to July 1, 2020). We constructed COVID-19-specific socioeconomic and epidemiological themes using established social theoretical frameworks and created composite indexes through principal component analysis. The risk of COVID-19 increased with higher area morbidity, risky health behaviours, crowding, and population mobility, and with lower social distancing, healthcare access, and education. Falling COVID-19 risks and spatial shifts over three consecutive time periods reflected effective public health interventions. This study provides a globally replicable methodological framework and precision mapping for COVID-19 and future pandemics.