Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates
Objectives Although it is widely used as a measure for mortality, the case fatality rate (CFR) of coronavirus disease 2019 (COVID-19) can vary over time and fluctuate for many reasons other than viral characteristics. To compare the CFRs of different countries in equal measure, we estimated comparab...
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| Format: | Article |
| Language: | English |
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Korea Disease Control and Prevention Agency
2022-12-01
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| Series: | Osong Public Health and Research Perspectives |
| Subjects: | |
| Online Access: | http://ophrp.org/upload/pdf/j-phrp-2022-0212.pdf |
| _version_ | 1797700688566812672 |
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| author | Yongmoon Kim Bryan Inho Kim Sangwoo Tak |
| author_facet | Yongmoon Kim Bryan Inho Kim Sangwoo Tak |
| author_sort | Yongmoon Kim |
| collection | DOAJ |
| description | Objectives Although it is widely used as a measure for mortality, the case fatality rate (CFR) of coronavirus disease 2019 (COVID-19) can vary over time and fluctuate for many reasons other than viral characteristics. To compare the CFRs of different countries in equal measure, we estimated comparable CFRs after adjusting for multiple covariates and examined the main factors that contributed to variability in the CFRs among 21 countries. Methods For statistical analysis, time-series cross-sectional data were collected from Our World in Data, CoVariants.org, and GISAID. Biweekly CFRs of COVID-19 were estimated by pooled generalized linear squares regression models for the panel data. Covariates included the predominant virus variant, reproduction rate, vaccination, national economic status, hospital beds, diabetes prevalence, and population share of individuals older than age 65. In total, 21 countries were eligible for analysis. Results Adjustment for covariates reduced variation in the CFRs of COVID-19 across countries and over time. Regression results showed that the dominant spread of the Omicron variant, reproduction rate, and vaccination were associated with lower country-level CFRs, whereas age, the extreme poverty rate, and diabetes prevalence were associated with higher country-level CFRs. Conclusion A direct comparison of crude CFRs among countries may be fallacious, especially in a cross-sectional analysis. Our study presents an adjusted comparison of CFRs over time for a more proper comparison. In addition, our findings suggest that comparing CFRs among different countries without considering their context, such as the epidemic phase, medical capacity, surveillance strategy, and socio-demographic traits, should be avoided. |
| first_indexed | 2024-03-12T04:25:15Z |
| format | Article |
| id | doaj.art-bd19303c57124ab786a273c9ef9a6023 |
| institution | Directory Open Access Journal |
| issn | 2233-6052 |
| language | English |
| last_indexed | 2024-03-12T04:25:15Z |
| publishDate | 2022-12-01 |
| publisher | Korea Disease Control and Prevention Agency |
| record_format | Article |
| series | Osong Public Health and Research Perspectives |
| spelling | doaj.art-bd19303c57124ab786a273c9ef9a60232023-09-03T10:27:39ZengKorea Disease Control and Prevention AgencyOsong Public Health and Research Perspectives2233-60522022-12-0113642443410.24171/j.phrp.2022.0212690Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariatesYongmoon KimBryan Inho Kim0Sangwoo Tak1 Division of Risk Assessment, Bureau of Public Health Emergency Preparedness, Korea Disease Control and Prevention Agency, Cheongju, Korea Division of Risk Assessment, Bureau of Public Health Emergency Preparedness, Korea Disease Control and Prevention Agency, Cheongju, KoreaObjectives Although it is widely used as a measure for mortality, the case fatality rate (CFR) of coronavirus disease 2019 (COVID-19) can vary over time and fluctuate for many reasons other than viral characteristics. To compare the CFRs of different countries in equal measure, we estimated comparable CFRs after adjusting for multiple covariates and examined the main factors that contributed to variability in the CFRs among 21 countries. Methods For statistical analysis, time-series cross-sectional data were collected from Our World in Data, CoVariants.org, and GISAID. Biweekly CFRs of COVID-19 were estimated by pooled generalized linear squares regression models for the panel data. Covariates included the predominant virus variant, reproduction rate, vaccination, national economic status, hospital beds, diabetes prevalence, and population share of individuals older than age 65. In total, 21 countries were eligible for analysis. Results Adjustment for covariates reduced variation in the CFRs of COVID-19 across countries and over time. Regression results showed that the dominant spread of the Omicron variant, reproduction rate, and vaccination were associated with lower country-level CFRs, whereas age, the extreme poverty rate, and diabetes prevalence were associated with higher country-level CFRs. Conclusion A direct comparison of crude CFRs among countries may be fallacious, especially in a cross-sectional analysis. Our study presents an adjusted comparison of CFRs over time for a more proper comparison. In addition, our findings suggest that comparing CFRs among different countries without considering their context, such as the epidemic phase, medical capacity, surveillance strategy, and socio-demographic traits, should be avoided.http://ophrp.org/upload/pdf/j-phrp-2022-0212.pdfcovid-19least-squares analysislinear modelsmortality |
| spellingShingle | Yongmoon Kim Bryan Inho Kim Sangwoo Tak Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates Osong Public Health and Research Perspectives covid-19 least-squares analysis linear models mortality |
| title | Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates |
| title_full | Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates |
| title_fullStr | Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates |
| title_full_unstemmed | Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates |
| title_short | Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates |
| title_sort | time series comparison of covid 19 case fatality rates across 21 countries with adjustment for multiple covariates |
| topic | covid-19 least-squares analysis linear models mortality |
| url | http://ophrp.org/upload/pdf/j-phrp-2022-0212.pdf |
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