Osong Public Health and Research Perspectives

Original Articles

Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates: Yongmoon Kim, Bryan Inho Kim, Sangwoo Tak; Osong Public Health Res Perspect. 2022;13(6):424-434. Published online November 28, 2022; DOI: https://doi.org/10.24171/j.phrp.2022.0212

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Objectives
Although it is widely used as a measure for mortality, the case fatality rate (CFR) ofcoronavirus disease 2019 (COVID-19) can vary over time and fluctuate for many reasons otherthan viral characteristics. To compare the CFRs of different countries in equal measure, weestimated comparable CFRs after adjusting for multiple covariates and examined the mainfactors that contributed to variability in the CFRs among 21 countries.Methods: For statistical analysis, time-series cross-sectional data were collected from OurWorld in Data, CoVariants.org, and GISAID. Biweekly CFRs of COVID-19 were estimated bypooled generalized linear squares regression models for the panel data. Covariates includedthe predominant virus variant, reproduction rate, vaccination, national economic status,hospital beds, diabetes prevalence, and population share of individuals older than age 65. Intotal, 21 countries were eligible for analysis.Results: Adjustment for covariates reduced variation in the CFRs of COVID-19 across countriesand over time. Regression results showed that the dominant spread of the Omicron variant,reproduction rate, and vaccination were associated with lower country-level CFRs, whereasage, the extreme poverty rate, and diabetes prevalence were associated with higher countrylevel CFRs.Conclusion: A direct comparison of crude CFRs among countries may be fallacious, especiallyin a cross-sectional analysis. Our study presents an adjusted comparison of CFRs over timefor a more proper comparison. In addition, our findings suggest that comparing CFRs amongdifferent countries without considering their context, such as the epidemic phase, medicalcapacity, surveillance strategy, and socio-demographic traits, should be avoided.

Citations

Citations to this article as recorded by

From mono to multi-causality: Towards a comprehensive perspective on understanding death
Peter Harteloh
Health Policy.2024; 147: 105121. CrossRef
Comments on the article "Time-series comparison of COVID-19 case fatality rates across 21 countries with adjustment for multiple covariates"
Gaetano Perone
Osong Public Health and Research Perspectives.2023; 14(2): 146. CrossRef

Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?: Maengseok Noh, Youngjo Lee, Chaeshin Chu, Jin Gwack, Seung-Ki Youn, Sun Huh; Osong Public Health Res Perspect. 2013;4(1):39-44. Published online February 28, 2013; DOI: https://doi.org/10.1016/j.phrp.2013.01.002

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Abstract PDF

Objectives
A hierarchical generalized linear model (HGLM) was applied to estimate the transmission pattern of scrub typhus from 2001 to 2011 in the Republic of Korea, based on spatial and temporal correlation.
Methods
Based on the descriptive statistics of scrub typhus incidence from 2001 to 2011 reported to the Korean Centers for Disease Control and Prevention, the spatial and temporal correlations were estimated by HGLM. Incidences according to age, sex, and year were also estimated by the best-fit model out of nine HGLMs. A disease map was drawn to view the annual regional spread of the disease.
Results
The total number of scrub typhus cases reported from 2001 to 2011 was 51,136: male, 18,628 (36.4%); female, 32,508 (63.6%). The best-fit model selected was a combination of the spatial model (Markov random-field model) and temporal model (first order autoregressive model) of scrub typhus transmission. The peak incidence was 28.80 per 100,000 persons in early October and the peak incidence was 40.17 per 100,000 persons in those aged 63.3 years old by the best-fit HGLM. The disease map showed the spread of disease from the southern central area to a nationwide area, excepting Gangwon-do (province), Gyeongsangbuk-do (province), and Seoul.
Conclusion
In the transmission of scrub typhus in Korea, there was a correlation to the incidence of adjacent areas, as well as that of the previous year. According to the disease map, we are unlikely to see any decrease in the incidence in the near future, unless ongoing aggressive measures to prevent the exposure to the vector, chigger mites, in rural areas, are put into place.

Citations

Citations to this article as recorded by

Prevalence of chigger mites and Orientia tsutsugamushi strains in northern regions of Gangwon-do, Korea
Soojin Kim, In Yong Lee, Sezim Monoldorova, Jiro Kim, Jang Hoon Seo, Tai-Soon Yong, Bo Young Jeon
Parasites, Hosts and Diseases.2023; 61(3): 263. CrossRef
Urine Metabolite of Mice with Orientia tsutsugamushi Infection
Sangho Choi, Do-Hwan Ahn, Min-Gyu Yoo, Hye-Ja Lee, Seong Beom Cho, Hee-Bin Park, Sung Soon Kim, Hyuk Chu
The American Journal of Tropical Medicine and Hygi.2023; 108(2): 296. CrossRef
Spatiotemporal dynamics and environmental determinants of scrub typhus in Anhui Province, China, 2010–2020
Xianyu Wei, Junyu He, Wenwu Yin, Ricardo J. Soares Magalhaes, Yanding Wang, Yuanyong Xu, Liang Wen, Yehuan Sun, Wenyi Zhang, Hailong Sun
Scientific Reports.2023;[Epub] CrossRef
Epidemiological characteristics of cases with scrub typhus and their correlation with chigger mite occurrence (2019–2021): A focus on case occupation and activity locations
Se‐Jin Jeong, Jin‐Hwan Jeon, Kyung won Hwang
Entomological Research.2023; 53(7): 247. CrossRef
Epidemiological characteristics and spatiotemporal patterns of scrub typhus in Yunnan Province from 2006 to 2017
Pei-Ying Peng, Lei Xu, Gu-Xian Wang, Wen-Yuan He, Ting-Liang Yan, Xian-Guo Guo
Scientific Reports.2022;[Epub] CrossRef
Clinical and Laboratory Predictors associated with Complicated Scrub Typhus
Mi-Hee Kim, Si-Hyun Kim, Jung-Hyun Choi, Seong-Heon Wie
Infection & Chemotherapy.2019; 51(2): 161. CrossRef
Awareness and Work-Related Factors Associated with Scrub Typhus: A Case-Control Study from South Korea
Dong-Seob Kim, Dilaram Acharya, Kwan Lee, Seok-Ju Yoo, Ji-Hyuk Park, Hyun-Sul Lim
International Journal of Environmental Research an.2018; 15(6): 1143. CrossRef
Estimating the burden of scrub typhus: A systematic review
Ana Bonell, Yoel Lubell, Paul N. Newton, John A. Crump, Daniel H. Paris, Janet Foley
PLOS Neglected Tropical Diseases.2017; 11(9): e0005838. CrossRef
Spatiotemporal Dynamics of Scrub Typhus Transmission in Mainland China, 2006-2014
Yi-Cheng Wu, Quan Qian, Ricardo J. Soares Magalhaes, Zhi-Hai Han, Wen-Biao Hu, Ubydul Haque, Thomas A. Weppelmann, Yong Wang, Yun-Xi Liu, Xin-Lou Li, Hai-Long Sun, Yan-Song Sun, Archie C. A. Clements, Shen-Long Li, Wen-Yi Zhang, Mathieu Picardeau
PLOS Neglected Tropical Diseases.2016; 10(8): e0004875. CrossRef
Larval Chigger Mites Collected from Small Mammals in 3 Provinces, Korea
In-Yong Lee, Hyeon-Je Song, Yeon-Joo Choi, Sun-Hye Shin, Min-Kyung Choi, So-Hyun Kwon, E-Hyun Shin, Chan Park, Heung-Chul Kim, Terry A. Klein, Kyung-Hee Park, Won-Jong Jang
The Korean Journal of Parasitology.2014; 52(2): 225. CrossRef

Article

Spatial and Temporal Distribution of Plasmodium vivax Malaria in Korea Estimated with a Hierarchical Generalized Linear Model: Maengseok Noh, Youngjo Lee, Seungyoung Oh, Chaeshin Chu, Jin Gwack, Seung-Ki Youn, Shin Hyeong Cho, Won Ja Lee, Sun Huh; Osong Public Health Res Perspect. 2012;3(4):192-198. Published online December 31, 2012; DOI: https://doi.org/10.1016/j.phrp.2012.11.003

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Abstract PDF

Objectives
The spatial and temporal correlations were estimated to determine Plasmodium vivax malarial transmission pattern in Korea from 2001–2011 with the hierarchical generalized linear model.
Methods
Malaria cases reported to the Korea Centers for Disease Control and Prevention from 2001 to 2011 were analyzed with descriptive statistics and the incidence was estimated according to age, sex, and year by the hierarchical generalized linear model. Spatial and temporal correlation was estimated and the best model was selected from nine models. Results were presented as diseases map according to age and sex.
Results
The incidence according to age was highest in the 20–25-year-old group (244.52 infections/100,000). Mean ages of infected males and females were 31.0 years and 45.3 years with incidences 7.8 infections/100,000 and 7.1 infections/100,000 after estimation. The mean month for infection was mid-July with incidence 10.4 infections/100,000. The best-fit model showed that there was a spatial and temporal correlation in the malarial transmission. Incidence was very low or negligible in areas distant from the demilitarized zone between Republic of Korea and Democratic People’s Republic of Korea (North Korea) if the 20–29-year-old male group was omitted in the diseases map.
Conclusion
Malarial transmission in a region in Korea was influenced by the incidence in adjacent regions in recent years. Since malaria in Korea mainly originates from mosquitoes from North Korea, there will be continuous decrease if there is no further outbreak in North Korea.

Citations

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Source separation in municipal solid waste management: Practical means to its success in Asian cities
Premakumara Jagath Dickella Gamaralalage, Sadhan Kumar Ghosh, Kazunobu Onogawa
Waste Management & Research: The Journal for a Sus.2022; 40(3): 360. CrossRef
Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions
Sophie A. Lee, Christopher I. Jarvis, W. John Edmunds, Theodoros Economou, Rachel Lowe
Journal of The Royal Society Interface.2021; 18(178): 20210096. CrossRef
Effects of climate change on Plasmodium vivax malaria transmission dynamics: A mathematical modeling approach
Jung Eun Kim, Yongin Choi, Chang Hyeong Lee
Applied Mathematics and Computation.2019; 347: 616. CrossRef
Spatially Filtered Multilevel Analysis on Spatial Determinants for Malaria Occurrence in Korea
Sehyeong Kim, Youngho Kim
International Journal of Environmental Research an.2019; 16(7): 1250. CrossRef
Is it necessary to take anthelmintics every year in Korea?
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Journal of the Korean Medical Association.2018; 61(3): 198. CrossRef
Research on Factors Influencing Municipal Household Solid Waste Separate Collection: Bayesian Belief Networks
Zhujie Chu, Wenna Wang, Bairong Wang, Jun Zhuang
Sustainability.2016; 8(2): 152. CrossRef
Chemotherapeutic drugs for common parasitic diseases in Korea
Sun Huh
Journal of the Korean Medical Association.2013; 56(6): 513. CrossRef
Are There Spatial and Temporal Correlations in the Incidence Distribution of Scrub Typhus in Korea?
Maengseok Noh, Youngjo Lee, Chaeshin Chu, Jin Gwack, Seung-Ki Youn, Sun Huh
Osong Public Health and Research Perspectives.2013; 4(1): 39. CrossRef
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Hae-Wol Cho, Chaeshin Chu
Osong Public Health and Research Perspectives.2013; 4(3): 125. CrossRef
A New Statistical Approach to Analyze Plasmodium vivax Malaria Endemic in Korea
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