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Na-young Kim 4 Articles
Early Intervention Reduces the Spread of COVID-19 in Long-Term Care Facilities in the Republic of Korea
Shin Young Park, Gawon Choi, Hyeyoung Lee, Na-young Kim, Seon-young Lee, Kyungnam Kim, Soyoung Shin, Eunsu Jang, YoungSin Moon, KwangHwan Oh, JaeRin Choi, Sangeun Lee, Young-Man Kim, Jieun Kim, Seonju Yi, Jin Gwack, Ok Park, Young Joon Park
Osong Public Health Res Perspect. 2020;11(4):259-264.   Published online August 31, 2020
DOI: https://doi.org/10.24171/j.phrp.2020.11.4.16
  • 4,800 View
  • 138 Download
  • 8 Citations
AbstractAbstract PDF

This study describes the epidemiological characteristics of coronavirus disease 2019 (COVID-19) based on reported cases from long-term care facilities. As of April 20th, 2020, 3 long-term care facilities in a metropolitan area of South Korea had reported cases of COVID-19. These facilities’ employees were presumed to be the sources of infection. There were 2 nursing hospitals that did not report any additional cases. One nursing home had a total of 25 cases, with an attack rate of 51.4% (95% CI 35.6–67.0), and a fatality rate of 38.9% (95% CI 20.3–61.4) among residents. The results from this study suggest that early detection and maintenance of infection control minimizes the risk of rapid transmission.

Citations

Citations to this article as recorded by  
  • Impact of the COVID-19 pandemic and corresponding control measures on long-term care facilities: a systematic review and meta-analysis
    Jun Zhang, Yushan Yu, Mirko Petrovic, Xiaomei Pei, Qing-Bao Tian, Lei Zhang, Wei-Hong Zhang
    Age and Ageing.2023;[Epub]     CrossRef
  • Staffing Levels and COVID-19 Infections and Deaths in Korean Nursing Homes
    Jiyeon Lee, Juh Hyun Shin, Kyeong Hun Lee, Charlene A. Harrington, Sun Ok Jung
    Policy, Politics, & Nursing Practice.2022; 23(1): 15.     CrossRef
  • An Experience of the Early Stage of COVID-19 Outbreak in Nursing Homes in Gyeonggi Province, Korea
    Gawon Choi, Na-young Kim, Seon-young Lee, Hae Deun Noh, Heeyoung Lee
    Korean Journal of Clinical Geriatrics.2022; 23(1): 27.     CrossRef
  • The implications of the COVID-19 pandemic for long term care facilities
    Muh-Yong Yen, Jonathan Schwartz, Po-Ren Hsueh
    Current Opinion in Infectious Diseases.2022; 35(4): 370.     CrossRef
  • Health impact of the first and second wave of COVID-19 and related restrictive measures among nursing home residents: a scoping review
    Marjolein E. A. Verbiest, Annerieke Stoop, Aukelien Scheffelaar, Meriam M. Janssen, Leonieke C. van Boekel, Katrien G. Luijkx
    BMC Health Services Research.2022;[Epub]     CrossRef
  • Epidemiology and clinical features of COVID-19 outbreaks in aged care facilities: A systematic review and meta-analysis
    Mohammad Rashidul Hashan, Nicolas Smoll, Catherine King, Hannah Ockenden-Muldoon, Jacina Walker, Andre Wattiaux, Julieanne Graham, Robert Booy, Gulam Khandaker
    EClinicalMedicine.2021; 33: 100771.     CrossRef
  • Protecting Nursing Homes and Long-Term Care Facilities From COVID-19: A Rapid Review of International Evidence
    Sally Hall Dykgraaf, Sethunya Matenge, Jane Desborough, Elizabeth Sturgiss, Garang Dut, Leslee Roberts, Alison McMillan, Michael Kidd
    Journal of the American Medical Directors Associat.2021; 22(10): 1969.     CrossRef
  • Dementia Risk among Coronavirus Disease Survivors: A Nationwide Cohort Study in South Korea
    Hye-Yoon Park, In-Ae Song, Tak-Kyu Oh
    Journal of Personalized Medicine.2021; 11(10): 1015.     CrossRef
The Recency Period for Estimation of Human Immunodeficiency Virus Incidence by the AxSYM Avidity Assay and BED-Capture Enzyme Immunoassay in the Republic of Korea
Hye-Kyung Yu, Tae-Young Heo, Na-Young Kim, Jin-Sook Wang, Jae-Kyeong Lee, Sung Soon Kim, Mee-Kyung Kee
Osong Public Health Res Perspect. 2014;5(4):187-192.   Published online August 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.06.002
  • 1,961 View
  • 16 Download
  • 1 Citations
AbstractAbstract PDF
Objectives
Measurement of the incidence of the human immunodeficiency virus (HIV) is very important for epidemiological studies. Here, we determined the recency period with the AxSYM avidity assay and the BED-capture enzyme immunoassay (BED-CEIA) in Korean seroconverters.
Methods
Two hundred longitudinal specimens from 81 seroconverters with incident HIV infections that had been collected at the Korea National Institute of Health were subjected to the AxSYM avidity assay (cutoff = 0.8) and BED-CEIA (cutoff = 0.8). The statistical method used to estimate the recency period in recent HIV infections was nonparametric survival analyses. Sensitivity and specificity were calculated for 10-day increments from 120 days to 230 days to determine the recency period.
Results
The mean recency period of the avidity assay and BED-CEIA using a survival method was 158 days [95% confidence interval (CI), 135–181 days] and 189 days (95% CI, 170–208 days), respectively. Based on the use of sensitivity and specificity, the mean recency period for the avidity assay and BED-CEIA was 150 days and 200 days, respectively.
Conclusion
We determined the recency period to estimate HIV incidence in Korea. These data showed that the nonparametric survival analysis often led to shorter recency periods than analysis of sensitivity and specificity as a new method. These findings suggest that more data from seroconverters and other methodologies are needed to determine the recency period for estimating HIV incidence.

Citations

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  • Western Blot-Based Logistic Regression Model for the Identification of Recent HIV-1 Infection: A Promising HIV-1 Surveillance Approach for Resource-Limited Regions
    Jiegang Huang, Minlian Wang, Chunyuan Huang, Bingyu Liang, Junjun Jiang, Chuanyi Ning, Ning Zang, Hui Chen, Jie Liu, Rongfeng Chen, Yanyan Liao, Li Ye, Hao Liang
    BioMed Research International.2018; 2018: 1.     CrossRef
Forecasting the Number of Human Immunodeficiency Virus Infections in the Korean Population Using the Autoregressive Integrated Moving Average Model
Hye-Kyung Yu, Na-Young Kim, Sung Soon Kim, Chaeshin Chu, Mee-Kyung Kee
Osong Public Health Res Perspect. 2013;4(6):358-362.   Published online December 31, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.10.009
  • 2,032 View
  • 15 Download
  • 21 Citations
AbstractAbstract PDF
Objectives
From the introduction of HIV into the Republic of Korea in 1985 through 2012, 9,410 HIV-infected Koreans have been identified. Since 2000, there has been a sharp increase in newly diagnosed HIV-infected Koreans. It is necessary to estimate the changes in HIV infection to plan budgets and to modify HIV/AIDS prevention policy. We constructed autoregressive integrated moving average (ARIMA) models to forecast the number of HIV infections from 2013 to 2017.
Methods
HIV infection data from 1985 to 2012 were used to fit ARIMA models. Akaike Information Criterion and Schwartz Bayesian Criterion statistics were used to evaluate the constructed models. Estimation was via the maximum likelihood method. To assess the validity of the proposed models, the mean absolute percentage error (MAPE) between the number of observed and fitted HIV infections from 1985 to 2012 was calculated. Finally, the fitted ARIMA models were used to forecast the number of HIV infections from 2013 to 2017.
Results
The fitted number of HIV infections was calculated by optimum ARIMA (2,2,1) model from 1985–2012. The fitted number was similar to the observed number of HIV infections, with a MAPE of 13.7%. The forecasted number of new HIV infections in 2013 was 962 (95% confidence interval (CI): 889–1,036) and in 2017 was 1,111 (95% CI: 805–1,418). The forecasted cumulative number of HIV infections in 2013 was 10,372 (95% CI: 10,308–10,437) and in 2017 was14,724 (95% CI: 13,893–15,555) by ARIMA (1,2,3).
Conclusion
Based on the forecast of the number of newly diagnosed HIV infections and the current cumulative number of HIV infections, the cumulative number of HIV-infected Koreans in 2017 would reach about 15,000.

Citations

Citations to this article as recorded by  
  • Deep learning-based forecasting model for COVID-19 outbreak in Saudi Arabia
    Ammar H. Elsheikh, Amal I. Saba, Mohamed Abd Elaziz, Songfeng Lu, S. Shanmugan, T. Muthuramalingam, Ravinder Kumar, Ahmed O. Mosleh, F.A. Essa, Taher A. Shehabeldeen
    Process Safety and Environmental Protection.2021; 149: 223.     CrossRef
  • Forecasting future HIV infection cases: evidence from Indonesia
    Maria Dyah Kurniasari, Andrian Dolfriandra Huruta, Hsiu Ting Tsai, Cheng-Wen Lee
    Social Work in Public Health.2021; 36(1): 12.     CrossRef
  • Forecasting Confirmed Malaria Cases in Northwestern Province of Zambia: A Time Series Analysis Using 2014–2020 Routine Data
    Dhally M. Menda, Mukumbuta Nawa, Rosemary K. Zimba, Catherine M. Mulikita, Jim Mwandia, Henry Mwaba, Karen Sichinga, Hamidreza Karimi-Sari
    Advances in Public Health.2021; 2021: 1.     CrossRef
  • An Adaptive Variational Mode Decomposition Technique with Differential Evolution Algorithm and Its Application Analysis
    Yuanxin Wang, Chaoqun Duan
    Shock and Vibration.2021; 2021: 1.     CrossRef
  • A comparative study on the prediction of the BP artificial neural network model and the ARIMA model in the incidence of AIDS
    Zeming Li, Yanning Li
    BMC Medical Informatics and Decision Making.2020;[Epub]     CrossRef
  • Hybrid Decomposition Time-Series Forecasting by DirRec Strategy: Electric Load Forecasting Using Machine-Learning
    Branislav Vuksanovic, Davoud Rahimi Ardali
    International Journal of Computer and Electrical E.2019; 11(1): 1.     CrossRef
  • Exploring an Ensemble of Methods that Combines Fuzzy Cognitive Maps and Neural Networks in Solving the Time Series Prediction Problem of Gas Consumption in Greece
    Papageorgiou, Poczeta, Papageorgiou, Gerogiannis, Stamoulis
    Algorithms.2019; 12(11): 235.     CrossRef
  • APLIKASI METODE DOUBLE EXPONENTIAL SMOOTHING HOLT DAN ARIMA UNTUK MERAMALKAN VOLUNTARY COUNSELING AND TESTING (VCT) ODHA DI PROVINSI JAWA TIMUR
    Suci Retno Ningtiyas
    The Indonesian Journal of Public Health.2019; 13(2): 158.     CrossRef
  • Research into the high-precision marine integrated navigation method using INS and star sensors based on time series forecasting BPNN
    Qiu Ying Wang, Kaiyue Liu, Zhiguo Sun, Minghui Zhang
    Optik.2018; 172: 494.     CrossRef
  • Real-time predictive seasonal influenza model in Catalonia, Spain
    Luca Basile, Manuel Oviedo de la Fuente, Nuria Torner, Ana Martínez, Mireia Jané, Jeffrey Shaman
    PLOS ONE.2018; 13(3): e0193651.     CrossRef
  • Using an Autoregressive Integrated Moving Average Model to Predict the Incidence of Hemorrhagic Fever with Renal Syndrome in Zibo, China, 2004–2014
    Tao Wang, Yunping Zhou, Ling Wang, Zhenshui Huang, Feng Cui, Shenyong Zhai
    Japanese Journal of Infectious Diseases.2016; 69(4): 279.     CrossRef
  • Time series analysis of influenza incidence in Chinese provinces from 2004 to 2011
    Xin Song, Jun Xiao, Jiang Deng, Qiong Kang, Yanyu Zhang, Jinbo Xu
    Medicine.2016; 95(26): e3929.     CrossRef
  • Modelling the prevalence of hepatitis C virus amongst blood donors in Libya: An investigation of providing a preventive strategy
    Mohamed A Daw
    World Journal of Virology.2016; 5(1): 14.     CrossRef
  • Forecast analysis of any opportunistic infection among HIV positive individuals on antiretroviral therapy in Uganda
    John Rubaihayo, Nazarius M. Tumwesigye, Joseph Konde-Lule, Fredrick Makumbi
    BMC Public Health.2016;[Epub]     CrossRef
  • The Use of an Autoregressive Integrated Moving Average Model for Prediction of the Incidence of Dysentery in Jiangsu, China
    Kewei Wang, Wentao Song, Jinping Li, Wu Lu, Jiangang Yu, Xiaofeng Han
    Asia Pacific Journal of Public Health.2016; 28(4): 336.     CrossRef
  • Prevalence of hemorrhagic fever with renal syndrome in Yiyuan County, China, 2005–2014
    Tao Wang, Jie Liu, Yunping Zhou, Feng Cui, Zhenshui Huang, Ling Wang, Shenyong Zhai
    BMC Infectious Diseases.2015;[Epub]     CrossRef
  • Application of an autoregressive integrated moving average model for predicting injury mortality in Xiamen, China
    Yilan Lin, Min Chen, Guowei Chen, Xiaoqing Wu, Tianquan Lin
    BMJ Open.2015; 5(12): e008491.     CrossRef
  • Back propagation neural network with adaptive differential evolution algorithm for time series forecasting
    Lin Wang, Yi Zeng, Tao Chen
    Expert Systems with Applications.2015; 42(2): 855.     CrossRef
  • Direct Medical Costs of Hospitalizations for Cardiovascular Diseases in Shanghai, China
    Shengnan Wang, Max Petzold, Junshan Cao, Yue Zhang, Weibing Wang
    Medicine.2015; 94(20): e837.     CrossRef
  • Changing Patterns of HIV Epidemic in 30 Years in East Asia
    S. Pilar Suguimoto, Teeranee Techasrivichien, Patou Masika Musumari, Christina El-saaidi, Bhekumusa Wellington Lukhele, Masako Ono-Kihara, Masahiro Kihara
    Current HIV/AIDS Reports.2014; 11(2): 134.     CrossRef
  • What is Next for HIV/AIDS in Korea?
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2013; 4(6): 291.     CrossRef
Immune Status and Epidemiological Characteristics of Human Immunodeficiency Virus Seroconverters in Korea, 1999–2009
Jin-Sook Wang, Na-young Kim, Hyo Jung Sim, Byeong-Sun Choi, Mee-Kyung Kee
Osong Public Health Res Perspect. 2012;3(4):245-249.   Published online December 31, 2012
DOI: https://doi.org/10.1016/j.phrp.2012.11.001
  • 1,979 View
  • 21 Download
  • 3 Citations
AbstractAbstract PDF
Objectives
The detection of HIV seroconverters increased annually since HIV antigen/antibody testing kits have been available widely in South Korea. This study aimed to identify the epidemiological characteristics of HIV seroconverters and their immune level at HIV diagnosis.
Method
We analyzed the epidemiological and immunological characteristics of 341 HIV seroconverters among 6,008 HIV-diagnosed individuals from 1999 and 2009. The analysis of immune level and epidemiological factors of HIV seroconverters was conducted by using chi-square test on SAS version 9.1.
Results
The seroconverters among newly-identified HIV cases each year increased from 0.5% in 1999 to over 5% or in 2009. The sex ratio of seroconverters was 18:1 (male:female), and 33% were in their 30s, and 28% were in their 20s. Reasons for HIV testing were involvement in voluntary test due to risky behaviors (43%), and health check-up (36%). Discovery of HIV infection occurred primarily in hospitals (84%). Among seroconverters, 55 percent had a CD4 T-cell count of more than 350/μl.
Conclusion
Korean HIV seroconverters tended to be younger at diagnosis, diagnosed during a voluntary test, and their CD4+ T-cell counts at HIV diagnosis were higher than those of non-seroconverters aall HIV-infected individuals. This study of HIV seroconverters will be important foundational in future studies on HIV incidence, disease progress, and survival rate.

Citations

Citations to this article as recorded by  
  • Characteristics of recent HIV infection among individuals newly diagnosed as HIV-positive in South Korea (2008–2015)
    Myeongsu Yoo, Jin-Sook Wang, Su-Jin Park, Jeong-ok Cha, Yoonhee Jung, Yoon-Seok Chung, Myung Guk Han, Byeong-Sun Choi, Sung-Soon Kim, Mee-Kyung Kee
    Scientific Reports.2022;[Epub]     CrossRef
  • Evaluation of the Bio-Rad Geenius HIV 1/2 Confirmation Assay as an Alternative to Western Blot in the Korean Population: A Multi-Center Study
    Hee-Won Moon, Hee Jin Huh, Gwi Young Oh, Sang Gon Lee, Anna Lee, Yeo-Min Yun, Mina Hur, Herman Tse
    PLOS ONE.2015; 10(9): e0139169.     CrossRef
  • Interferon-inducible protein 10 (IP-10) is associated with viremia of early HIV-1 infection in Korean patients
    SoYong Lee, Yoon-Seok Chung, Cheol-Hee Yoon, YoungHyun Shin, SeungHyun Kim, Byeong-Sun Choi, Sung Soon Kim
    Journal of Medical Virology.2015; 87(5): 782.     CrossRef

PHRP : Osong Public Health and Research Perspectives