Epidemiology and Health

Original Articles

Association of group-level segregation with cardiovascular health in older adults: an analysis of data from the Korean Social Life, Health, and Aging Project: Sung-Ha Lee, Hyeok-Hee Lee, Kiho Sung, Yoosik Youm, Hyeon Chang Kim; Epidemiol Health. 2023;45:e2023041. Published online April 4, 2023; DOI: https://doi.org/10.4178/epih.e2023041

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Abstract

OBJECTIVES
The adverse health effects of individual-level social isolation (e.g., perceived loneliness) have been well documented in older adults. However, little is known about the impact of collective-level social isolation on health outcomes. We sought to examine the association of group-level segregation with cardiovascular health (CVH) in older adults.

METHODS

From the prospective Korean Social Life, Health, and Aging Project database, we identified 528 community-dwelling older adults who were aged ≥60 years or were married to those aged ≥60 years. Participants who belonged to smaller social groups separate from the major social group were defined as group-level-segregated. The CVH score was calculated as the number of ideal non-dietary CVH metrics (0-6), as modified from the American Heart Association’s Life’s Simple 7. Using ordinal logistic regression models, we assessed cross-sectional and longitudinal associations between group-level segregation and CVH.

RESULTS

Of the 528 participants (mean age, 71.7 years; 60.0% female), 108 (20.5%) were segregated at baseline. In the crosssectional analysis, group-level segregation was significantly associated with lower odds of having a higher CVH score at baseline after adjusting for socio-demographic factors and cognitive function (odds ratio [OR], 0.64; 95% confidence interval [CI], 0.43 to 0.95). Among 274 participants who completed an 8-year follow-up, group-level segregation at baseline was marginally associated with lower odds of having a higher CVH score at 8 years (OR, 0.49; 95% CI, 0.24 to 1.02).

CONCLUSIONS

Group-level segregation was associated with worse CVH. These findings imply that the social network structure of a community may influence its members’ health status.

Summary

Korean summary
본 연구는 “한국인의 사회적 삶, 건강과 노화에 대한 조사”(Korean Social Life, Health and Aging Project, KSHAP)에서 측정한 한 지역 내의 사회적 연결망 자료를 이용하여 사회적 분리와 심혈관 건강 사이의 관계를 살펴보았다. 그 결과, 사회적 분리는 비만, 고혈압, 콜레스테롤, 흡연, 음주 신체적 활동 등을 종합한 ‘라이프 심플 7’ 지표와 부정적인 관련성을 보였으며, 8년 후 추적 조사에서도 이 패턴이 유지되었다. 본 연구 결과는 사회적, 집단적 분리 현상이 신체적 건강에도 악영향을 초래할 수 있음을 시사한다.

Key Message
Using the prospective Korean Social Life, Health, and Aging Project (KSHAP) database, we discovered that group-level segregation was significantly associated with worse cardiovascular health (CVH). Also, we observed a tendency for baseline group-level segregation to be linked to worse CVH after an 8-year follow-up period. These findings emphasize the significance of group-level segregation as a potential contributing factor in the health outcomes of older adults.

Citations

Citations to this article as recorded by

Association of social isolation and loneliness with the risk of hypertension in middle aged and older adults: Findings from a national representative longitudinal survey
Shiqi Wang, Hao Zhang, Yiling Lou, Qiqi You, Qingqing Jiang, Shiyi Cao
Journal of Affective Disorders.2024; 349: 577. CrossRef

Dynamic changes in clinical biomarkers of cardiometabolic diseases by changes in exercise behavior, and network comparisons: a community-based prospective cohort study in Korea: JooYong Park, Jaesung Choi, Ji-Eun Kim, Sang-Min Park, Joo-Youn Cho, Daehee Kang, Miyoung Lee, Ji-Yeob Choi; Epidemiol Health. 2023;45:e2023026. Published online February 16, 2023; DOI: https://doi.org/10.4178/epih.e2023026

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Abstract Summary PDF Supplementary Material: Abstract
OBJECTIVES
Lifestyles, including exercise behaviors, change continually over time. This study examined whether the clinical biomarkers (CBs) related to cardiometabolic diseases (CMDs) and their relationships differed with changes in exercise behavior.
METHODS
The Ansan-Ansung cohort study (third to fifth phases; n=2,668) was used in the current study. Regular exercise behavior was investigated using a yes/no questionnaire. Changes in exercise behavior were classified into 4 groups: Y-N, N-Y, Y-Y, and N-N, with “Y” indicating that a participant regularly engaged in exercise at a given time point and “N” indicating that he or she did not. Fourteen CBs related to CMDs were used, and the associations between changes in exercise behavior and relative changes in CBs were examined. CB networks were constructed and topological comparisons were conducted.
RESULTS
Y-N was associated with increases in fasting blood sugar and insulin levels in men, and increased total cholesterol and low-density lipoprotein cholesterol levels in women. Meanwhile, N-Y was inversely associated with body fat percentage, visceral fat percentage, fasting insulin, and triglyceride level. Waist circumference played a central role in most networks. In men, more edges were found in the N-Y and Y-Y groups than in the N-N and Y-N groups, whereas women in the N-Y and Y-Y groups had more edges than those in the N-N and Y-N groups.
CONCLUSIONS
Consistent exercise or starting to engage in regular exercise had favorable effects on CBs related to CMDs, although their network patterns differed between the sexes.; Summary

Korean summary
한국 지역사회기반 코호트 자료를 이용하여, 운동 행태 변화에 따른 심혈관대사질환 관련 임상 생체 지표들의 변화가 남녀에 따라, 변화 행태에 따라 다르게 나타남을 확인하였다. 이런 변화와 차이는 네트워크 분석을 통한 구조적인 차이로도 확인되었다.

Key Message
This study examined that changes in the clinical biomarkers related to cardiometabolic diseases differed with changes in exercise behavior using a community-based prospective cohort study in Korea. Consistent exercise or change into exercise behavior had favorable effects on CB related to CMD, although their network patterns differed between the sexes.

Multimorbidity patterns by health-related quality of life status in older adults: an association rules and network analysis utilizing the Korea National Health and Nutrition Examination Survey: Thi-Ngoc Tran, Sanghee Lee, Chang-Mo Oh, Hyunsoon Cho; Epidemiol Health. 2022;44:e2022113. Published online November 29, 2022; DOI: https://doi.org/10.4178/epih.e2022113

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Abstract Summary PDF Supplementary Material

Abstract

OBJECTIVES
Improved life expectancy has increased the prevalence of older adults living with multimorbidity which likely deteriorates their health-related quality of life (HRQoL). However, relatively little is known about patterns and the relationships of multimorbidity by HRQoL status in older adults.

METHODS

Individuals aged 65 or older from the Korea National Health and Nutrition Examination Survey V-VII (2010-2018) were analyzed. HRQoL was assessed by the EuroQoL-5 dimensions questionnaire and categorized as poor, normal, or good. The impact of multimorbidity on HRQoL was evaluated using logistic regression. The patterns and inter-relationships between multimorbidity, stratified by HRQoL groups, were analyzed using the association rules and network analysis approach.

RESULTS

Multimorbidity was significantly associated with poor HRQoL (3 or more diseases vs. none; adjusted odds ratio, 2.70; 95% confidence interval, 2.10 to 3.46). Hypertension, arthritis, hyperlipidemia, and diabetes were the most prevalent diseases across all HRQoL groups. Complex interrelationships of morbidities, higher prevalence, and node strengths in all diseases were observed in the poor HRQoL group, particularly for arthritis, depression, and stroke, compared to other groups (1.5-3.0 times higher, p<0.05 for all). Apart from hypertension, arthritis and hyperlipidemia had a higher prevalence and stronger connections with other diseases in females, whereas this was the case for diabetes and stroke in males with poor HRQoL.

CONCLUSIONS

Multimorbidity patterns formed complicatedly inter-correlated disease networks in the poor HRQoL group with differences according to sex. These findings enhance the understanding of multimorbidity connections and provide information on the healthcare needs of older adults, especially those with poor HRQoL.

Summary

Korean summary
기대 수명의 증가에 따라 고령인구에서 건강관련 삶의 질을 저하시킬 수 있는 복합질환의 유병률도 함께 증가하고 있다. 본 연구에서는 국민건강영양조사 자료를 이용하여 65세 이상 우리나라 고령인구에서 건강관련 삶의 질 (HRQoL)에 따른 복합만성질환 패턴을 분석하였다. 복합만성질환은 건강관련 삶의 질 저하와 통계적으로 유의하게 연관되어 있으며, 연관성 및 네크워크 분석 결과 건강관련 삶의 질이 낮을수록 복합질환의 패턴이 복잡한 것으로 나타났다. 전체적으로 고혈압, 관절염, 고지혈증, 당뇨병이 가장 높은 발생률을 보였다. 건강관련 삶의 질이 낮은 그룹에서는 관절염, 우울증, 뇌졸중 등의 질병이 높은 발생률과 상호관련성을 보였으며, 이는 성별에 따라 차이가 있었다. 연구 결과는 고령자, 특히 건강관련 삶의 질이 낮은 노인의 의료 서비스 요구에 대해 정보를 제공해 줄 수 있을 것이다,

Key Message
Network analysis of older adults (65 or older) in Korea showed that hypertension, arthritis, hyperlipidemia, and diabetes were the most common multimorbidity regardless of HRQoL status. However, as HRQoL deteriorated, multimorbidity patterns formed complicatedly inter-correlated disease networks; the prevalence and the node strength of arthritis, depression, and stroke increased considerably and be diversified by sex.

Citations

Citations to this article as recorded by

Chronic Disease Patterns and Their Relationship With Health-Related Quality of Life in South Korean Older Adults With the 2021 Korean National Health and Nutrition Examination Survey: Latent Class Analysis
Mi-Sun Lee, Hooyeon Lee
JMIR Public Health and Surveillance.2024; 10: e49433. CrossRef
Health-promoting behavior to enhance perceived meaning and control of life in chronic disease patients with role limitations and depressive symptoms: a network approach
Je-Yeon Yun, Young Ho Yun
Scientific Reports.2023;[Epub] CrossRef

Reconstructing a COVID-19 outbreak within a religious group using social network analysis simulation in Korea: Namje Kim, Su Jin Kang, Sangwoo Tak; Epidemiol Health. 2021;43:e2021068. Published online September 16, 2021; DOI: https://doi.org/10.4178/epih.e2021068

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Abstract Summary PDF

Abstract

OBJECTIVES
We reconstructed a coronavirus disease 2019 (COVID-19) outbreak to examine how a large cluster at a church setting spread before being detected and estimate the potential effectiveness of complying with mask-wearing guidelines recommended by the government.

METHODS

A mathematical model with a social network analysis (SNA) approach was used to simulate a COVID-19 outbreak. A discrete-time stochastic simulation model was used to simulate the spread of COVID-19 within the Sarang Jeil church. A counterfactual experiment using a calibrated baseline model was conducted to examine the potential benefits of complying with a mask-wearing policy.

RESULTS

Simulations estimated a mask-wearing ratio of 67% at the time of the outbreak, which yielded 953.8 (95% confidence interval [CI], 937.3 to 970.4) cases and was most consistent with the confirmed data. The counterfactual experiment with 95% mask-wearing estimated an average of 45.6 (95% CI, 43.4 to 47.9) cases with a standard deviation of 20.1. The result indicated that if the church followed government mask-wearing guidelines properly, the outbreak might have been one-twentieth the size.

CONCLUSIONS

SNA is an effective tool for monitoring and controlling outbreaks of COVID-19 and other infectious diseases. Although our results are based on simulations and are thus limited, the precautionary implications of social distancing and mask-wearing are still relevant. Since person-to-person contacts and interactions are unavoidable in social and economic life, it may be beneficial to develop precise measures and guidelines for particular organizations or places that are susceptible to cluster outbreaks.

Summary

Korean summary
본 연구는 구조화된 확률적 네트워크 시뮬레이션모형을 이용하여 국내에서 발생했던 사랑제일교회 발 코로나19 집단 감염 사례의 일별 확진자 데이터를 설명하고자, 마스크 착용 비율 추정과 반사실적 실험을 통해 방역지침을 준수한 경우 발생할 수 있었을 확진자의 규모를 추정하였다. 시뮬레이션 결과 추정된 당시 사랑제일교회의 마스크 착용 비율은 약 67% 수준이며, 만약 참석자의 95%가 마스크를 착용한 경우 확진자 규모는 실제의 20분의 1 수준에 그쳤을 것으로 예상된다. 마스크 착용은 예방접종과 함께 코로나 감염증을 극복하기 위한 가장 효과적인 예방활동이며 가장 마지막까지 강조되어야 할 것이다.

Key Message
To better understand the transmission of COVID-19 in a church setting, a stochastic social network analysis with a focus on mask-wearing practice was constructed. The results showed that if mask-wearing were to increase from 67% (at the time of the outbreak) to 95%, the outbreak could have been one-twentieth the size. Among the many measures of non-pharmaceutical intervention which may be withdrawn, mask-wearing is still one of the most effective precautionary measure and should continue to be emphasized.

Citations

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Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature
Hyojung Lee, Sol Kim, Minyoung Jeong, Eunseo Choi, Hyeonjeong Ahn, Jeehyun Lee
Yonsei Medical Journal.2023; 64(1): 1. CrossRef
A Social Network Analysis Approach to Evaluate the Relationship Between the Mobility Network Metrics and the COVID-19 Outbreak
Sadegh Ilbeigipour, Babak Teimourpour
Health Services Insights.2023; 16: 117863292311738. CrossRef
The effect of shortening the quarantine period and lifting the indoor mask mandate on the spread of COVID-19: a mathematical modeling approach
Jung Eun Kim, Heejin Choi, Minji Lee, Chang Hyeong Lee
Frontiers in Public Health.2023;[Epub] CrossRef
Investigation of Statistical Machine Learning Models for COVID-19 Epidemic Process Simulation: Random Forest, K-Nearest Neighbors, Gradient Boosting
Dmytro Chumachenko, Ievgen Meniailov, Kseniia Bazilevych, Tetyana Chumachenko, Sergey Yakovlev
Computation.2022; 10(6): 86. CrossRef

The anatomy of COVID-19 comorbidity networks among hospitalized Korean patients: Eun Kyong Shin, Hyo Young Choi, Neil Hayes; Epidemiol Health. 2021;43:e2021035. Published online May 7, 2021; DOI: https://doi.org/10.4178/epih.e2021035

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Abstract Summary PDF

Abstract

OBJECTIVES
We aimed to examine how comorbidities were associated with outcomes (illness severity or death) among hospitalized patients with coronavirus disease 2019 (COVID-19).

METHODS

Data were provided by the National Medical Center of the Korea Disease Control and Prevention Agency. These data included the clinical and epidemiological information of all patients hospitalized with COVID-19 who were discharged on or before April 30, 2020 in Korea. We conducted comorbidity network and multinomial logistic regression analyses to identify risk factors associated with COVID-19 disease severity and mortality. The outcome variable was the clinical severity score (CSS), categorized as mild (oxygen treatment not needed), severe (oxygen treatment needed), or death.

RESULTS

In total, 5,771 patients were included. In the fully adjusted model, chronic kidney disease (CKD) (odds ratio [OR], 2.58; 95% confidence interval [CI], 1.19 to 5.61) and chronic obstructive pulmonary disease (COPD) (OR, 3.19; 95% CI, 1.35 to 7.52) were significantly associated with disease severity. CKD (OR, 5.35; 95% CI, 2.00 to 14.31), heart failure (HF) (OR, 3.15; 95% CI, 1.22 to 8.15), malignancy (OR, 3.38; 95% CI, 1.59 to 7.17), dementia (OR, 2.62; 95% CI, 1.45 to 4.72), and diabetes mellitus (OR, 2.26; 95% CI, 1.46 to 3.49) were associated with an increased risk of death. Asthma and hypertension showed statistically insignificant associations with an increased risk of death.

CONCLUSIONS

Underlying diseases contribute differently to the severity of COVID-19. To efficiently allocate limited medical resources, underlying comorbidities should be closely monitored, particularly CKD, COPD, and HF.

Summary

Korean summary
본 연구는 2019 년 코로나 바이러스 질환 (COVID-19)으로 입원 한 환자의 합병증이 결과 (질병 중증도 또는 사망)와 어떤 관련이 있는지를 동반 질환 네트워크 및 다항 로지스틱 회귀 분석을 통해 분석하였다. 기저 질환은 COVID-19의 중증도 및 사망에 차별적으로 영향을 미친다. 제한된 의료 자원을 효율적으로 활용하기 위해서 환자의 기저 동반 질환 중, 특히 만성 신장 질환 (CKD), 만성 폐쇄성 폐 질환 (COPD), 심부전 (HF)을 더욱 면밀히 모니터링해야 한다.

Key Message
We examined how comorbidities were associated with outcomes (illness severity or death) among hospitalized patients with coronavirus disease 2019 (COVID-19), implementing comorbidity network and multinomial logistic regression analyses. Underlying diseases contribute differently to the severity of COVID-19. To efficiently allocate limited medical resources, underlying comorbidities should be closely monitored, particularly chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), and heart failure (HF).

Citations

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SARS-CoV-2 susceptibility and COVID-19 illness course and outcome in people with pre-existing neurodegenerative disorders: systematic review with frequentist and Bayesian meta-analyses
Muhannad Smadi, Melina Kaburis, Youval Schnapper, Gabriel Reina, Patricio Molero, Marc L. Molendijk
The British Journal of Psychiatry.2023; 223(2): 348. CrossRef
Asthma and COPD as co-morbidities in patients hospitalised with Covid-19 disease: a global systematic review and meta-analysis
James Patrick Finnerty, A. B. M. Arad Hussain, Aravind Ponnuswamy, Hafiz Gulzeb Kamil, Ammar Abdelaziz
BMC Pulmonary Medicine.2023;[Epub] CrossRef
The Role of Diabetes and Hyperglycemia on COVID-19 Infection Course—A Narrative Review
Evangelia Tzeravini, Eleftherios Stratigakos, Chris Siafarikas, Anastasios Tentolouris, Nikolaos Tentolouris
Frontiers in Clinical Diabetes and Healthcare.2022;[Epub] CrossRef

Comorbidity network analysis related to obesity in middle-aged and older adults: findings from Korean population-based survey data: Hye Ah Lee, Hyesook Park; Epidemiol Health. 2021;43:e2021018. Published online March 5, 2021; DOI: https://doi.org/10.4178/epih.e2021018

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Abstract Summary PDF

Abstract

OBJECTIVES
We conducted a comorbidity network analysis using data from the seventh Korea National Health and Nutrition Examination Survey to systematically quantify obesity-related comorbidities.

METHODS

The study included 11,712 subjects aged 45 to 80 (5,075 male and 6,637 female). A prevalent disease was defined as a specific disease for which a subject had been diagnosed by a doctor and was being treated. Comorbidity network analysis was performed for diseases with a prevalence of 1% or more, including overweight and obesity. We estimated the observed-to-expected ratio of all possible disease pairs with comorbidity strength and visualized the network of obesity-related comorbidities.

RESULTS

In subjects over 45 years old, 37.3% of people had a body mass index over 25.0 kg/m2. The most common prevalent disease was hypertension (42.3%), followed by dyslipidemia (17.4%) and diabetes (17.0%). Overweight and obese subjects were 2.1 times (95% confidence interval, 1.9 to 2.3) more likely to have a comorbidity (i.e., 2 or more diseases) than normal-weight subjects. Metabolic diseases such as hypertension, dyslipidemia, diabetes, and osteoarthritis were directly associated with overweight and obesity. The probability of coexistence for each of those 4 diseases was 1.3 times higher than expected. In addition, hypertension and dyslipidemia frequently coexisted in overweight and obese female along with other diseases. In obese male, dyslipidemia and diabetes were the major diseases in the comorbidity network.

CONCLUSIONS

Our results provide evidence justifying the management of metabolic components in obese individuals. In addition, our results will help prioritize interventions for comorbidity reduction as a public health goal.

Summary

Korean summary
본 연구는 비만 관련 동반질환을 체계적으로 정량화하기 위해, 제7차 (2016-2018) 국민건강영양조사 자료를 이용하여 동반질환 네트워크 분석을 수행하였습니다. 45세 이상 성인에서 비만(체질량지수≥25.0 kg/m²)은 정상체중에 비해 동반질환에 대한 위험이 2.1배 높은 것으로 나타났습니다. 동반질환 네트워크에서는 고혈압과 이상지질혈증이 비만 여성의 주요 질환 이였으며, 이상지질혈증과 당뇨병은 비만 남성의 주요 질환인 것으로 나타났습니다. 본 연구결과는 비만 관련 동반질환 감소를 위한 중재의 우선 순위를 정하는데 도움이 될 것이라고 생각됩니다.

Key Message
We conducted a comorbidity network analysis using data from the seventh (2016-2018) Korea National Health and Nutrition Examination Survey to systematically quantify obesity-related comorbidities. In subjects over 45 years old, obese (body mass index ≥ 25.0 kg/m²) subjects were 2.1 times more likely to have a comorbidity than normal-weight subjects. In the comorbidity network, hypertension and dyslipi¬demia were the major diseases in obese females, and dyslipidemia and diabetes were the major diseases in obese males. Our results will help prioritize interventions for reducing obesity-related comorbidities.

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Association of social network size and composition with physical activity in Korean middle-aged adults: Moon Su Kwak, So Mi Jemma Cho, Jee-Seon Shim, Dae Jung Kim, Yoosik Youm, Hyeon Chang Kim; Epidemiol Health. 2020;42:e2020070. Published online November 25, 2020; DOI: https://doi.org/10.4178/epih.e2020070

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Abstract Summary PDF Supplementary Material: Abstract
OBJECTIVES
Physical activity (PA) is an established protective factor for many chronic diseases. Numerous studies have established positive relationships between social networks and PA. Accordingly, this study examined the relationship between social network structures (specifically the network size and the number and proportion of same-sex alters) and self-reported PA in Korean middle-age adults, where the term “alter” refers to a respondent’s social network members.
METHODS
We analyzed 8,092 participants of the Cardiovascular and Metabolic Diseases Etiology Research Center cohort. We assessed the association between each network structure variable and PA level using a linear regression model. Then, we employed logistic regression to evaluate associations between social network structure and adherence to guideline-recommended exercise levels. Socio-demographic factors and health status measures were used as covariates.
RESULTS
In both sexes, the social network size and proportion of same-sex network members showed positive relationships with total and moderate-to-vigorous PA. Notably, female participants with a greater number of kin were more likely to satisfy the recommended amount of total PA.
CONCLUSIONS
These findings suggest that large scale, same-sex intervention programs can help to achieve recommended PA regimens.; Summary

Korean summary
이 연구는 30-64세 중년의 한국인 8,092(남자 2,805, 여자 5,207)명에서 사회연결망 특성과 신체활동량의 관련성을 평가했다. 남녀 모두에서 사회연결망의 크기가 클수록, 연결망내 동성인 사람의 비중이 높을수록 신체활동량이 많았다. 사회연결망 크기와 연결망내 동성인 사람의 비중은 권장 신체활동량을 충족률과도 양의 관련성을 보였다. 반면, 연결망내 친족의 비중이 높은 경우는 오히려 권장신체활동량을 충족할 가능성이 낮았다.

Intervention effects in the transmission of COVID-19 depending on the detection rate and extent of isolation: Okyu Kwon, Woo-Sik Son, Jin Yong Kim, Jong-Hun Kim; Epidemiol Health. 2020;42:e2020045. Published online June 23, 2020; DOI: https://doi.org/10.4178/epih.e2020045

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Abstract Summary PDF Supplementary Material

Abstract

Objectives
In 2020, the coronavirus disease 2019 (COVID-19) respiratory infection is spreading in Korea. In order to prevent the spread of an infectious disease, infected people must be quickly identified and isolated, and contact with the infected must be blocked early. This study attempted to verify the intervention effects on the spread of an infectious disease by using these measures in a mathematical model.

Methods

We used the susceptible-infectious-recovery (SIR) model for a virtual population group connected by a special structured network. In the model, the infected state (I) was divided into I in which the infection is undetected and Ix in which the infection is detected. The probability of transitioning from an I state to Ix can be viewed as the rate at which an infected person is found. We assumed that only those connected to each other in the network can cause infection. In addition, this study attempted to evaluate the effects of isolation by temporarily removing the connection among these people.

Results

In Scenario 1, only the infected are isolated; in Scenario 2, those who are connected to an infected person and are also found to be infected are isolated as well. In Scenario 3, everyone connected to an infected person are isolated. In Scenario 3, it was possible to effectively suppress the infectious disease even with a relatively slow rate of diagnosis and relatively high infection rate.

Conclusions

During the epidemic, quick identification of the infected is helpful. In addition, it was possible to quantitatively show through a simulation evaluation that the management of infected individuals as well as those who are connected greatly helped to suppress the spread of infectious diseases.

Summary

Korean summary
본 연구는 행위자 기반 모형의 시뮬레이션 평가를 통해 COVID-19 유행 상황에서 비약물적 중재 효과를 정량적으로 제시하였다. 비약물적 중재에 관한 세 가지 시나리오를 통해 제시한 결과에서, COVID-19 감염자를 신속하게 진단하고, 감염자 본인과 접촉자들을 가능한 한 빨리 모두 격리하여 관리하는 것이 감염병 확산을 억제하는데 있어서 보다 효과적이었다.

Citations

Citations to this article as recorded by

Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature
Hyojung Lee, Sol Kim, Minyoung Jeong, Eunseo Choi, Hyeonjeong Ahn, Jeehyun Lee
Yonsei Medical Journal.2023; 64(1): 1. CrossRef
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Methods

Network meta-analysis: application and practice using R software: Sung Ryul Shim, Seong-Jang Kim, Jonghoo Lee, Gerta Rücker; Epidemiol Health. 2019;41:e2019013. Published online April 8, 2019; DOI: https://doi.org/10.4178/epih.e2019013

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Abstract Summary PDF Supplementary Material

Abstract

The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software. We conducted a network meta-analysis using two approaches: Bayesian and frequentist methods. The corresponding R packages were “gemtc” for the Bayesian approach and “netmeta” for the frequentist approach. In estimating a network meta-analysis model using a Bayesian framework, the “rjags” package is a common tool. “rjags” implements Markov chain Monte Carlo simulation with a graphical output. The estimated overall effect sizes, test for heterogeneity, moderator effects, and publication bias were reported using R software. The authors focus on two flexible models, Bayesian and frequentist, to determine overall effect sizes in network meta-analysis. This study focused on the practical methods of network meta-analysis rather than theoretical concepts, making the material easy to understand for Korean researchers who did not major in statistics. The authors hope that this study will help many Korean researchers to perform network meta-analyses and conduct related research more easily with R software.

Summary

Korean summary
통계프로그램으로서의 R이 대세인 연구환경에서 R을 활용한 체계적인 메타분석 안내서가 요구되어지며 본 연구는 이에 대한 좋은 해답이 될 것이다. 더욱이 본 연구는 네트워크 메타분석 (Network meta-analysis)의 이론과 더불어 R을 활용한 실습위주의 내용으로 구성되어져 있어 누구나 쉽게 실행할 수 있을 것이다. 본 연구를 통하여 많은 연구자들이 보다 쉽게 본인의 연구분야에 적용하여 관련 연구가 활성화되기를 바란다.

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Review Paper

Population data science: advancing the safe use of population data for public benefit: Kerina Helen Jones, David Vincent Ford; Epidemiol Health. 2018;40:e2018061. Published online December 25, 2018; DOI: https://doi.org/10.4178/epih.e2018061

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Abstract

The value of using population data to answer important questions for individual and societal benefit has never been greater. Governments and research funders world-wide are recognizing this potential and making major investments in data-intensive initiatives. However, there are challenges to overcome so that safe, socially-acceptable data sharing can be achieved. This paper outlines the field of population data science, the International Population Data Linkage Network (IPDLN), and their roles in advancing data-intensive research. We provide an overview of core concepts and major challenges for data-intensive research, with a particular focus on ethical, legal, and societal implications (ELSI). Using international case studies, we show how challenges can be addressed and lessons learned in advancing the safe, socially-acceptable use of population data for public benefit. Based on the case studies, we discuss the common ELSI principles in operation, we illustrate examples of a data scrutiny panel and a consumer panel, and we propose a set of ELSI-based recommendations to inform new and developing data-intensive initiatives.We conclude that although there are many ELSI issues to be overcome, there has never been a better time or more potential to leverage the benefits of population data for public benefit. A variety of initiatives, with different operating models, have pioneered the way in addressing many challenges. However, the work is not static, as the ELSI environment is constantly evolving, thus requiring continual mutual learning and improvement via the IPDLN and beyond.

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Review Article

A review of methods to estimate the visibility factor for bias correction in network scale-up studies: Aliakbar Haghdoost, Milad Ahmadi Gohari, Ali Mirzazadeh, Farzaneh Zolala, Mohammad Reza Baneshi; Epidemiol Health. 2018;40:e2018041. Published online August 16, 2018; DOI: https://doi.org/10.4178/epih.e2018041

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Abstract PDF

Abstract

Network scale-up is an indirect size estimation method, in which participants are questioned on sensitive behaviors of their social network members. Therefore, the visibility of the behavior affects the replies and estimates. Many attempts to estimate visibility have been made. The aims of this study were to review the main methods used to address visibility and to provide a summary of reported visibility factors (VFs) across populations. We systematically searched relevant databases and Google. In total, 15 studies and reports that calculated VFs were found. VF calculation studies have been applied in 9 countries, mostly in East Asia and Eastern Europe. The methods applied were expert opinion, comparison of NSU with another method, the game of contacts, social respect, and the coming-out rate. The VF has been calculated for heavy drug users, people who inject drugs (PWID), female sex workers (FSWs) and their clients, male who have sex with male (MSM), alcohol and methamphetamine users, and those who have experienced extra-/pre-marital sex and abortion. The VF varied from 1.4% in Japan to 52.0% in China for MSM; from 34.0% in Ukraine to 111.0% in China for FSWs; and from 12.0% among Iranian students to 57.0% in Ukraine for PWID. Our review revealed that VF estimates were heterogeneous, and were not available for most settings, in particular the Middle East and North Africa region, except Iran. More concrete methodologies to estimate the VF are required.

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Original Article

Factors affecting satisfaction with cancer information provided through the social networking services of the National Cancer Information Center in Korea: Su Yeon Kye, Min Hee Lee, Jisu Yoo, Kyung Hee Oh, Jae Kwan Jun; Epidemiol Health. 2017;39:e2017057. Published online December 11, 2017; DOI: https://doi.org/10.4178/epih.e2017057

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Abstract

OBJECTIVES
This study aimed to identify the characteristics of social networking service (SNS) users and to assess the relationship of those factors to user satisfaction with the SNSs of the National Cancer Information Center (NCIC) in South Korea.

METHODS

A Web-based survey was completed by 1,670 users of the NCIC SNSs, who provided data on the sources they consulted for information about cancer, determinants of SNS use, sources of NCIC SNS awareness, the time of day they used the SNS, and their satisfaction level.

RESULTS

Facebook users mainly became aware of the NCIC SNSs through an acquaintance’s recommendation, while Twitter was accessed through other SNSs or blogs. Users in their 30s were less satisfied with the NCIC SNSs than those in their teens and 20s. Browsing for cancer-related information on the Internet, prioritizing information quality, and engaging in active use were related to a high level of satisfaction with the NCIC SNSs. Individuals who were exposed to the NCIC SNSs through other SNSs or printed materials were less satisfied with their experience of the NCIC SNSs than those who received a recommendation from an acquaintance.

CONCLUSIONS

These findings may act as a catalyst to guide public health agencies to enhance their use of SNSs.

Summary

Korean summary
본 연구는 소셜네트워크서비스 사용자의 특성을 파악하고 우리나라 국가암정보센터 소셜네트워크서비스 사용자의 만족도에 영향을 주는 요인을 파악하고자 하였다. 국가암정보센터 소셜네트워크서비스 사용자 1,670명을 대상으로 암정보원, 서비스사용동기, 서비스를 알게된 경위, 사용시간대, 서비스 사용 만족도를 조사하였다. 분석결과, 페이스북은 주로 주변 아는 사람들의 권유로 사용하기 시작하였고, 트위터는 다른 사람의 소셜네트워크서비스를 통해 접근하고 있었다. 국가암정보센터에 대한 만족도에 영향을 주는 요인을 살펴보면, 10-20대에 비하여 30대의 만족도가 낮았으며, 인터넷을 통해 암정보를 얻고 있는 경우, 암정보의 질을 중시 여기는 경우, 활발하게 소셜네트워크서비스를 사용하고 있는 경우에 만족도가 높았다. 또한, 다른 사람들의 소셜네트워크서비스나 인쇄물을 통해 국가암정보센터 소셜네트워크서비스를 알게 된 경우 주변 사람들의 권고로 사용하게 된 경우에 비해 만족도가 낮았다. 공공보건의료기관들은 자 기관의 소셜네트워크 서비스 접근도 및 만족도 향상을 위하여 본 결과를 활용할 수 있을 것이다

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Methods

Network meta-analysis: application and practice using Stata: Sungryul Shim, Byung-Ho Yoon, In-Soo Shin, Jong-Myon Bae; Epidemiol Health. 2017;39:e2017047. Published online October 27, 2017; DOI: https://doi.org/10.4178/epih.e2017047

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Abstract Summary PDF Supplementary Material

Abstract

This review aimed to arrange the concepts of a network meta-analysis (NMA) and to demonstrate the analytical process of NMA using Stata software under frequentist framework. The NMA tries to synthesize evidences for a decision making by evaluating the comparative effectiveness of more than two alternative interventions for the same condition. Before conducting a NMA, 3 major assumptions—similarity, transitivity, and consistency—should be checked. The statistical analysis consists of 5 steps. The first step is to draw a network geometry to provide an overview of the network relationship. The second step checks the assumption of consistency. The third step is to make the network forest plot or interval plot in order to illustrate the summary size of comparative effectiveness among various interventions. The fourth step calculates cumulative rankings for identifying superiority among interventions. The last step evaluates publication bias or effect modifiers for a valid inference from results. The synthesized evidences through five steps would be very useful to evidence-based decision-making in healthcare. Thus, NMA should be activated in order to guarantee the quality of healthcare system.

Summary

Korean summary
같은 치료 목적을 가진 여러 치료법들 간의 효과를 상호 비교한 결과들을 통합하기 위해 개발된 네트워크 메타분석 (NMA) 결과는 의사결정의 우선순위를 정하는데 있어 가장 상위의 과학적 설득력을 갖는다. STATA 통계프로그램에서 제공하는 빈도주의 틀에 기반한 NMA를 수행하는데 점검해야 할 가정들과 실제 적용 과정을 소개한다.

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Original Articles

Using Bayesian Networks to Model Hierarchical Relationships in Epidemiological Studies: Georges Nguefack-Tsague; Epidemiol Health. 2011;33:e2011006. Published online June 17, 2011; DOI: https://doi.org/10.4178/epih/e2011006

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Abstract

<sec><title>OBJECTIVES</title>To propose an alternative procedure, based on a Bayesian network (BN), for estimation and prediction, and to discuss its usefulness for taking into account the hierarchical relationships among covariates.</sec><sec><title>METHODS</title>The procedure is illustrated by modeling the risk of diarrhea infection for 2,740 children aged 0 to 59 months in Cameroon. We compare the procedure with a standard logistic regression and with a model based on multi-level logistic regression.</sec><sec><title>RESULTS</title>The standard logistic regression approach is inadequate, or at least incomplete, in that it does not attempt to account for potentially causal relationships between risk factors. The multi-level logistic regression does model the hierarchical structure, but does so in a piecewise manner; the resulting estimates and interpretations differ from those of the BN approach proposed here. An advantage of the BN approach is that it enables one to determine the probability that a risk factor (and/or the outcome) is in any specific state, given the states of the others. The currently available approaches can only predict the outcome (disease), given the states of the covariates.</sec><sec><title>CONCLUSION</title>A major advantage of BNs is that they can deal with more complex interrelationships between variables whereas competing approaches deal at best only with hierarchical ones. We propose that BN be considered as well as a worthwhile method for summarizing the data in epidemiological studies whose aim is understanding the determinants of diseases and quantifying their effects.</sec>

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Modeling and Simulations for Infectious Diseases.: Mo ran Ki; Korean J Epidemiol. 2006;28(1):64-68.

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Abstract PDF: Abstract
Modeling and simulations of infectious diseases are useful tools to estimate epidemic size and determine effective intervention methods. Models are idealized, simplified representations of reality. Therefore, a simple model should be the first design, with complex models always able to be added later to better represent reality. The following recommendations are made to ensure accurate simulations: (1) minimal feasible complexity, (2) mathematically well-defined, models should be constructed with well characterized stochastic processes rather than 'ad-hoc'behavioral models, (3) if predictions are being made, unknown parameters need to be robustly estimated using the model from epidemiological data, (4) where data is unavailable, a detailed sensitivity analysis needs to be undertaken, and (5) even if models are only being used to explore dynamics, sensitivity analysis is important to understand mechanisms. For the effective control of infectious diseases with models and simulations, we need effective information systems (laboratory and clinical data) for communicable disease control as a permanent infrastructure, closer collaboration between academic and service providers on new developments in communicable disease control, and enhanced monitoring of veterinary infections and 'minor' zoonoses, particularly in resources poor settings.; Summary

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