Osong Public Health and Research Perspectives

Original Article

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.

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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

Review Article

COVID-19 prediction models: a systematic literature review: Sheikh Muzaffar Shakeel, Nithya Sathya Kumar, Pranita Pandurang Madalli, Rashmi Srinivasaiah, Devappa Renuka Swamy; Osong Public Health Res Perspect. 2021;12(4):215-229. Published online August 13, 2021; DOI: https://doi.org/10.24171/j.phrp.2021.0100

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Abstract PDF

As the world grapples with the problem of the coronavirus disease 2019 (COVID-19) pandemic and its devastating effects, scientific groups are working towards solutions to mitigate the effects of the virus. This paper aimed to collate information on COVID-19 prediction models. A systematic literature review is reported, based on a manual search of 1,196 papers published from January to December 2020. Various databases such as Google Scholar, Web of Science, and Scopus were searched. The search strategy was formulated and refined in terms of subject keywords, geographical purview, and time period according to a predefined protocol. Visualizations were created to present the data trends according to different parameters. The results of this systematic literature review show that the study findings are critically relevant for both healthcare managers and prediction model developers. Healthcare managers can choose the best prediction model output for their organization or process management. Meanwhile, prediction model developers and managers can identify the lacunae in their models and improve their data-driven approaches.

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Original Articles

Factors Associated with Cesarean Section in Tehran, Iran using Multilevel Logistic Regression Model: Payam Amini, Maryam Mohammadi, Reza Omani-Samani, Amir Almasi-Hashiani, Saman Maroufizadeh; Osong Public Health Res Perspect. 2018;9(2):86-92. Published online April 30, 2018; DOI: https://doi.org/10.24171/j.phrp.2018.9.2.08

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Abstract PDF

Objectives

Over the past few decades, the prevalence of cesarean sections (CS) have risen dramatically worldwide, particularly in Iran. The aim of this study was to determine the prevalence of CS in Tehran, and to examine the associated risk factors.

Methods

A cross-sectional study of 4,308 pregnant women with singleton live-births in Tehran, Iran, between July 6–21, 2015 was performed. Multilevel logistic regression analysis was performed using demographic and obstetrical variables at the first level, and hospitals as a variable at the second level.

Results

The incidence of CS was 72.0%. Multivariate analysis showed a significant relationship between CS and the mother’s age, socioeconomic status, body mass index, parity, type of pregnancy, preeclampsia, infant height, and baby’s head circumference. The intra-class correlation using the second level variable, the hospital was 0.292, indicating approximately 29.2% of the total variation in the response variable accounted for by the hospital.

Conclusion

The incidence of CS was substantially higher than other countries. Therefore, educational and psychological interventions are necessary to reduce CS rates amongst pregnant Iranian women.

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Determinants of cesarean mode of childbirth among Rwandan women of childbearing age: Evidence from the 2019–2020 Rwanda Demographic and Health Survey (RDHS)
Nsereko Etienne, Uwase Aline, Mpinganzima Ornella, Usanzineza Henriette, Niyitegeka Jean Pierre, Turabayo Jean Léonard, Mwiseneza Marie Josee, Mugeni Girimpundu Candide, Moreland Patricia
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The double burden of maternal overweight and short stature and the likelihood of cesarean deliveries in South Asia: An analysis of national datasets from Bangladesh, India, Maldives, Nepal, and Pakistan
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Birth.2022; 49(4): 661. CrossRef
Geospatial analysis of cesarean section in Iran (2016–2020): exploring clustered patterns and measuring spatial interactions of available health services
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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.

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Urine Metabolite of Mice with Orientia tsutsugamushi Infection
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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.

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Maengseok Noh, Youngjo Lee, Chaeshin Chu, Jin Gwack, Seung-Ki Youn, Sun Huh
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Invited Original Article

Incubation Period of Ebola Hemorrhagic Virus Subtype Zaire: Martin Eichner, Scott F. Dowell, Nina Firese; Osong Public Health Res Perspect. 2011;2(1):3-7. Published online June 30, 2011; DOI: https://doi.org/10.1016/j.phrp.2011.04.001

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Abstract PDF

Objectives
Ebola hemorrhagic fever has killed over 1300 people, mostly in equatorial Africa. There is still uncertainty about the natural reservoir of the virus and about some of the factors involved in disease transmission. Until now, a maximum incubation period of 21 days has been assumed.
Methods
We analyzed data collected during the Ebola outbreak (subtype Zaire) in Kikwit, Democratic Republic of the Congo, in 1995 using maximum likelihood inference and assuming a log-normally distributed incubation period.
Results
The mean incubation period was estimated to be 12.7 days (standard deviation 4.31 days), indicating that about 4.1% of patients may have incubation periods longer than 21 days.
Conclusion
If the risk of new cases is to be reduced to 1% then 25 days should be used when investigating the source of an outbreak, when determining the duration of surveillance for contacts, and when declaring the end of an outbreak.

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