Abstract
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 (20 January 2020 to 1 July 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.
| Dokumententyp: | Zeitschriftenartikel | 
|---|---|
| Fakultät: | Medizin | 
| Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit | 
| Sprache: | Englisch | 
| Dokumenten ID: | 102998 | 
| Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2023 15:41 | 
| Letzte Änderungen: | 17. Okt. 2023 15:12 | 
 
		 
	 
    


