Yearly Spatiotemporal Patterns of COVID-19 During the Pandemic Period: An In-Depth Analysis of Regional Trends and Risk Factors in the Republic of Korea
Background: South Korea was one of the first countries to experience the Coronavirus disease (COVID-19) epidemic, and the regional-level trends and patterns in the incidence and case-fatality rates have been observed to evolve with time. This study established yearly spatiotemporal evolution pattern...
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MDPI AG
2025-03-01
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| author | Chiara Achangwa Jung-Hee Park Moo-Sik Lee |
| author_facet | Chiara Achangwa Jung-Hee Park Moo-Sik Lee |
| author_sort | Chiara Achangwa |
| collection | DOAJ |
| description | Background: South Korea was one of the first countries to experience the Coronavirus disease (COVID-19) epidemic, and the regional-level trends and patterns in the incidence and case-fatality rates have been observed to evolve with time. This study established yearly spatiotemporal evolution patterns of COVID-19 by region and identified possible regional risk factors accounting for the observed spatial variations. Methods: COVID-19 data between 20 January 2020 and 31 August 2023 were collected from the Korean Centers for Disease Prevention and Control (KCDA). We generated epidemic curves and calculated the yearly incidence and case-fatality rates for each region. In addition, choropleth maps for the location quotient of cases and deaths to visualize yearly regional intensities were generated and the Moran’s I calculated. Associations between the incidence and case-fatality rates with regional risk factors were estimated using regression models. All analyses were performed in R version 4.4.2. Results: We noted a significant difference in the incidence rate by year, with 2022 recording the highest for all regions. A consistent and significant spatial autocorrelation for cases and deaths across all years was observed with Moran I values above 0.4 (<i>p</i> < 0.05). There was a positive association of COVID-19 incidence rates with the population density (RR = 0.02, CI: 0.01–0.04, <i>p</i> = 0.03), percentage aged 60 years and above (RR = 0.03, CI: 0.01–0.05, <i>p</i> = 0.01), smoking prevalence (women) (RR = 0.79, CI: 0.54–1.04, <i>p</i> = 0.01), and diabetes prevalence (women) (RR = 0.51, CI: 0.32–0.71, <i>p</i> = 0.04). Conclusions: The spatiotemporal evolution patterns of COVID-19 in Korea consisted of oscillating hot and cold spots across the pandemic period in each region. These findings provide a useful reference to the government as it continues with the routine surveillance of COVID-19 across the country. |
| format | Article |
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| institution | Kabale University |
| issn | 2673-8112 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | COVID |
| spelling | doaj-art-b60fbccc91a54cd9ba080c8ead7072c22025-08-20T03:43:15ZengMDPI AGCOVID2673-81122025-03-01534010.3390/covid5030040Yearly Spatiotemporal Patterns of COVID-19 During the Pandemic Period: An In-Depth Analysis of Regional Trends and Risk Factors in the Republic of KoreaChiara Achangwa0Jung-Hee Park1Moo-Sik Lee2Department of Public Health and Welfare, Graduate School, Konyang University, Daejeon 35365, Republic of KoreaDepartment of Paramedicine, College of Medical Science, Konyang University, Daejeon 35365, Republic of KoreaDepartment of Public Health and Welfare, Graduate School, Konyang University, Daejeon 35365, Republic of KoreaBackground: South Korea was one of the first countries to experience the Coronavirus disease (COVID-19) epidemic, and the regional-level trends and patterns in the incidence and case-fatality rates have been observed to evolve with time. This study established yearly spatiotemporal evolution patterns of COVID-19 by region and identified possible regional risk factors accounting for the observed spatial variations. Methods: COVID-19 data between 20 January 2020 and 31 August 2023 were collected from the Korean Centers for Disease Prevention and Control (KCDA). We generated epidemic curves and calculated the yearly incidence and case-fatality rates for each region. In addition, choropleth maps for the location quotient of cases and deaths to visualize yearly regional intensities were generated and the Moran’s I calculated. Associations between the incidence and case-fatality rates with regional risk factors were estimated using regression models. All analyses were performed in R version 4.4.2. Results: We noted a significant difference in the incidence rate by year, with 2022 recording the highest for all regions. A consistent and significant spatial autocorrelation for cases and deaths across all years was observed with Moran I values above 0.4 (<i>p</i> < 0.05). There was a positive association of COVID-19 incidence rates with the population density (RR = 0.02, CI: 0.01–0.04, <i>p</i> = 0.03), percentage aged 60 years and above (RR = 0.03, CI: 0.01–0.05, <i>p</i> = 0.01), smoking prevalence (women) (RR = 0.79, CI: 0.54–1.04, <i>p</i> = 0.01), and diabetes prevalence (women) (RR = 0.51, CI: 0.32–0.71, <i>p</i> = 0.04). Conclusions: The spatiotemporal evolution patterns of COVID-19 in Korea consisted of oscillating hot and cold spots across the pandemic period in each region. These findings provide a useful reference to the government as it continues with the routine surveillance of COVID-19 across the country.https://www.mdpi.com/2673-8112/5/3/40COVID-19regional trendsspatial analysisrisk factorsSouth Korea |
| spellingShingle | Chiara Achangwa Jung-Hee Park Moo-Sik Lee Yearly Spatiotemporal Patterns of COVID-19 During the Pandemic Period: An In-Depth Analysis of Regional Trends and Risk Factors in the Republic of Korea COVID COVID-19 regional trends spatial analysis risk factors South Korea |
| title | Yearly Spatiotemporal Patterns of COVID-19 During the Pandemic Period: An In-Depth Analysis of Regional Trends and Risk Factors in the Republic of Korea |
| title_full | Yearly Spatiotemporal Patterns of COVID-19 During the Pandemic Period: An In-Depth Analysis of Regional Trends and Risk Factors in the Republic of Korea |
| title_fullStr | Yearly Spatiotemporal Patterns of COVID-19 During the Pandemic Period: An In-Depth Analysis of Regional Trends and Risk Factors in the Republic of Korea |
| title_full_unstemmed | Yearly Spatiotemporal Patterns of COVID-19 During the Pandemic Period: An In-Depth Analysis of Regional Trends and Risk Factors in the Republic of Korea |
| title_short | Yearly Spatiotemporal Patterns of COVID-19 During the Pandemic Period: An In-Depth Analysis of Regional Trends and Risk Factors in the Republic of Korea |
| title_sort | yearly spatiotemporal patterns of covid 19 during the pandemic period an in depth analysis of regional trends and risk factors in the republic of korea |
| topic | COVID-19 regional trends spatial analysis risk factors South Korea |
| url | https://www.mdpi.com/2673-8112/5/3/40 |
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