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Chaeshin Chu 65 Articles
KCDC Risk Assessments on the Initial Phase of the COVID-19 Outbreak in Korea
Inho Kim, Jia Lee, Jihee Lee, Eensuk Shin, Chaeshin Chu, Seon Kui Lee
Osong Public Health Res Perspect. 2020;11(2):67-73.   Published online April 30, 2020
DOI: https://doi.org/10.24171/j.phrp.2020.11.2.02
  • 13,880 View
  • 635 Download
  • 18 Web of Science
  • 17 Crossref
AbstractAbstract PDF
Objectives

This study aims to evaluate the risk assessments of coronavirus 2019 (COVID-19) in the Korea Centers for Disease Control and Prevention (KCDC), from the point of detection to the provision of basic information to the relevant public health authorities.

Methods

To estimate the overall risk of specific public health events, probability, and impact at the country-level were evaluated using available information. To determine the probability of particular public health events, the risk of importation and risk of transmission were taken into consideration. KCDC used 5 levels (“very low,” “low,” “moderate,” “high,” and “very high”) for each category and overall risk was eventually decided.

Results

A total of 8 risk assessments were performed on 8 separate occasions between January 8th to February 28th, 2020, depending on the detection and report of COVID-19 cases in other countries. The overall risk of the situation in each assessment increased in severity over this period: “low” (first), “moderate” (second), “high” (third), “high” (fourth), “high” (fifth), “high” (sixth), “high” (seventh), and “very high” (eighth).

Conclusion

The KCDC’s 8 risk assessments were utilized to activate national emergency response mechanisms and eventually prepare for the pandemic to ensure the containment and mitigation of COVID-19 with non-pharmaceutical public health measures.

Citations

Citations to this article as recorded by  
  • COVID-19 Pandemic Risk Assessment: Systematic Review
    Amanda Chu, Patrick Kwok, Jacky Chan, Mike So
    Risk Management and Healthcare Policy.2024; Volume 17: 903.     CrossRef
  • COVID-19 Cases and Deaths among Healthcare Personnel with the Progression of the Pandemic in Korea from March 2020 to February 2022
    Yeonju Kim, Sung-Chan Yang, Jinhwa Jang, Shin Young Park, Seong Sun Kim, Chansoo Kim, Donghyok Kwon, Sang-Won Lee
    Tropical Medicine and Infectious Disease.2023; 8(6): 308.     CrossRef
  • A resposta da Coreia do Sul à pandemia de COVID-19: lições aprendidas e recomendações a gestores
    Thais Regis Aranha Rossi, Catharina Leite Matos Soares, Gerluce Alves Silva, Jairnilson Silva Paim, Lígia Maria Vieira-da-Silva
    Cadernos de Saúde Pública.2022;[Epub]     CrossRef
  • Nursing Experience of New Nurses Caring for COVID-19 Patients in Military Hospitals: A Qualitative Study
    Young-Hoon Kwon, Hye-Ju Han, Eunyoung Park
    Healthcare.2022; 10(4): 744.     CrossRef
  • South Korea’s fast response to coronavirus disease: implications on public policy and public management theory
    Pan Suk Kim
    Public Management Review.2021; 23(12): 1736.     CrossRef
  • Detection of SARS-CoV-2 in Fecal Samples From Patients With Asymptomatic and Mild COVID-19 in Korea
    Soo-kyung Park, Chil-Woo Lee, Dong-Il Park, Hee-Yeon Woo, Hae Suk Cheong, Ho Cheol Shin, Kwangsung Ahn, Min-Jung Kwon, Eun-Jeong Joo
    Clinical Gastroenterology and Hepatology.2021; 19(7): 1387.     CrossRef
  • Systematic assessment of South Korea’s capabilities to control COVID-19
    Katelyn J. Yoo, Soonman Kwon, Yoonjung Choi, David M. Bishai
    Health Policy.2021; 125(5): 568.     CrossRef
  • Environmental risk assessment and comprehensive index model of disaster loss for COVID-19 transmission
    Sulin Pang, Xiaofeng Hu, Zhiming Wen
    Environmental Technology & Innovation.2021; 23: 101597.     CrossRef
  • Transmission dynamics and control of two epidemic waves of SARS-CoV-2 in South Korea
    Sukhyun Ryu, Sheikh Taslim Ali, Eunbi Noh, Dasom Kim, Eric H. Y. Lau, Benjamin J. Cowling
    BMC Infectious Diseases.2021;[Epub]     CrossRef
  • Identifying and Prioritizing Ways to Improve Oman’s Tourism Sector in the Corona Period
    Zakiya Salim Al-Hasni
    Journal of Intercultural Management.2021; 13(1): 144.     CrossRef
  • Decreased Use of Broad-Spectrum Antibiotics During the Coronavirus Disease 2019 Epidemic in South Korea
    Sukhyun Ryu, Youngsik Hwang, Sheikh Taslim Ali, Dong-Sook Kim, Eili Y Klein, Eric H Y Lau, Benjamin J Cowling
    The Journal of Infectious Diseases.2021; 224(6): 949.     CrossRef
  • COVID-19 and Cancer Therapy: Interrelationships and Management of Cancer Cases in the Era of COVID-19
    Simon N. Mbugua, Lydia W. Njenga, Ruth A. Odhiambo, Shem O. Wandiga, Martin O. Onani, Nenad Ignjatovic
    Journal of Chemistry.2021; 2021: 1.     CrossRef
  • Challenges to manage pandemic of coronavirus disease (COVID-19) in Iran with a special situation: a qualitative multi-method study
    Hamidreza Khankeh, Mehrdad Farrokhi, Juliet Roudini, Negar Pourvakhshoori, Shokoufeh Ahmadi, Masoumeh Abbasabadi-Arab, Nader Majidi Bajerge, Babak Farzinnia, Pirhossain Kolivand, Vahid Delshad, Mohammad Saeed Khanjani, Sadegh Ahmadi-Mazhin, Ali Sadeghi-Mo
    BMC Public Health.2021;[Epub]     CrossRef
  • Effect of Nonpharmaceutical Interventions on Transmission of Severe Acute Respiratory Syndrome Coronavirus 2, South Korea, 2020
    Sukhyun Ryu, Seikh Taslim Ali, Cheolsun Jang, Baekjin Kim, Benjamin J. Cowling
    Emerging Infectious Diseases.2020; 26(10): 2406.     CrossRef
  • Early Trend of Imported COVID-19 Cases in South Korea

    Osong Public Health and Research Perspectives.2020; 11(3): 140.     CrossRef
  • Effect of Underlying Comorbidities on the Infection and Severity of COVID-19 in Korea: a Nationwide Case-Control Study
    Wonjun Ji, Kyungmin Huh, Minsun Kang, Jinwook Hong, Gi Hwan Bae, Rugyeom Lee, Yewon Na, Hyoseon Choi, Seon Yeong Gong, Yoon-Hyeong Choi, Kwang-Pil Ko, Jeong-Soo Im, Jaehun Jung
    Journal of Korean Medical Science.2020;[Epub]     CrossRef
  • Innovative countermeasures can maintain cancer care continuity during the coronavirus disease-2019 pandemic in Korea
    Soohyeon Lee, Ah-reum Lim, Min Ja Kim, Yoon Ji Choi, Ju Won Kim, Kyong Hwa Park, Sang Won Shin, Yeul Hong Kim
    European Journal of Cancer.2020; 136: 69.     CrossRef
Estimation of the Size of Dengue and Zika Infection Among Korean Travelers to Southeast Asia and Latin America, 2016–2017
Chaeshin Chu, Een Suk Shin
Osong Public Health Res Perspect. 2019;10(6):394-398.   Published online December 31, 2019
DOI: https://doi.org/10.24171/j.phrp.2019.10.6.10
  • 4,743 View
  • 74 Download
AbstractAbstract PDF
Objectives

To estimate the number and risk of imported infections resulting from people visiting Asian and Latin American countries.

Methods

The dataset of visitors to 5 Asian countries with dengue were analyzed for 2016 and 2017, and in the Philippines, Thailand and Vietnam, imported cases of zika virus infection were also reported. For zika virus, a single imported case was reported from Brazil in 2016, and 2 imported cases reported from the Maldives in 2017. To understand the transmissibility in 5 Southeast Asian countries, the estimate of the force of infection, i.e., the hazard of infection per year and the average duration of travel has been extracted. Outbound travel numbers were retrieved from the World Tourism Organization, including business travelers.

Results

The incidence of imported dengue in 2016 was estimated at 7.46, 15.00, 2.14, 4.73 and 2.40 per 100,000 travelers visiting Philippines, Indonesia, Thailand, Malaysia and Vietnam, respectively. Similarly, 2.55, 1.65, 1.53, 1.86 and 1.70 per 100,000 travelers in 2017, respectively. It was estimated that there were 60.1 infections (range: from 16.8 to 150.7 infections) with zika virus in Brazil, 2016, and 345.6 infections (range: from 85.4 to 425.5 infections) with zika virus in the Maldives, 2017.

Conclusion

This study emphasizes that dengue and zika virus infections are mild in their nature, and a substantial number of infections may go undetected. An appropriate risk assessment of zika virus infection must use the estimated total size of infections.

Watch Your Waistline
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2018;9(2):43-44.   Published online April 30, 2018
DOI: https://doi.org/10.24171/j.phrp.2018.9.2.01
  • 4,647 View
  • 74 Download
  • 1 Crossref
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Citations

Citations to this article as recorded by  
  • Establishment of hypertension risk nomograms based on physical fitness parameters for men and women: a cross-sectional study
    Yining Xu, Zhiyong Shi, Dong Sun, Goran Munivrana, Minjun Liang, Bíró István, Zsolt Radak, Julien S. Baker, Yaodong Gu
    Frontiers in Cardiovascular Medicine.2023;[Epub]     CrossRef
A Joint Exercise against Intentional Biothreats
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2018;9(1):1-2.   Published online December 31, 2017
DOI: https://doi.org/10.24171/j.phrp.2018.9.1.01
  • 5,865 View
  • 42 Download
  • 1 Crossref
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Citations

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  • Artificial intelligence in public health: the potential of epidemic early warning systems
    Chandini Raina MacIntyre, Xin Chen, Mohana Kunasekaran, Ashley Quigley, Samsung Lim, Haley Stone, Hye-young Paik, Lina Yao, David Heslop, Wenzhao Wei, Ines Sarmiento, Deepti Gurdasani
    Journal of International Medical Research.2023;[Epub]     CrossRef
Adolescents in Multi-Ethnic Families under Korean Ethnic Nationalism
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2017;8(6):367-368.   Published online December 31, 2017
DOI: https://doi.org/10.24171/j.phrp.2017.8.6.01
  • 3,973 View
  • 39 Download
  • 1 Crossref
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Citations

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  • Suicide attempt and violence victimization in Korean adolescents with migrant parents: A nationwide study
    Woorim Kim, Sungyoun Chun, Sang Ah Lee
    Journal of Affective Disorders.2021; 290: 164.     CrossRef
Not One for All
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2017;8(5):293-294.   Published online October 31, 2017
DOI: https://doi.org/10.24171/j.phrp.2017.8.5.01
  • 3,289 View
  • 18 Download
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The Story of Korean Health Insurance System
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2017;8(4):235-236.   Published online August 31, 2017
DOI: https://doi.org/10.24171/j.phrp.2017.8.4.01
  • 3,859 View
  • 29 Download
  • 3 Crossref
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Citations

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  • An Additional Model to Control Risk in Mastering Defense Technology in Indonesia
    Faried Jaendar Muda, Rajesri Govindaraju, Iwan Inrawan Wiratmadja
    Sustainability.2022; 14(3): 1658.     CrossRef
  • How to Reduce Excessive Use of the Health Care Service in Medical Aid Beneficiaries: Effectiveness of Community-Based Case Management
    Myung Ja Kim, Eunhee Lee
    International Journal of Environmental Research an.2020; 17(7): 2503.     CrossRef
  • Lessons learned for reducing out of pocket health payment in Afghanistan: a comparative case study of three Asian countries
    Fatima Akbari, Munehito Machida, Hiroyuki Nakamura, Keisuke Nagase, Aya Goto, Akinori Hara
    Journal of Global Health Science.2019;[Epub]     CrossRef
To Be or Not to Be
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2017;8(3):157-158.   Published online June 30, 2017
DOI: https://doi.org/10.24171/j.phrp.2017.8.3.01
  • 3,266 View
  • 21 Download
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Depression among Middle-aged Persons
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2017;8(2):105-107.   Published online April 30, 2017
DOI: https://doi.org/10.24171/j.phrp.2017.8.2.01
  • 3,667 View
  • 25 Download
  • 1 Crossref
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Citations

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  • Research Progress in the Correlation and Mechanism between High-Fat Diet and Depression
    晓娜 李
    Advances in Clinical Medicine.2023; 13(05): 7754.     CrossRef
What Matters in the Performance of a Medial Institution?
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2017;8(1):1-2.   Published online February 28, 2017
DOI: https://doi.org/10.24171/j.phrp.2017.8.1.01
  • 3,499 View
  • 25 Download
  • 1 Crossref
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Citations

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  • Cancer care patterns in South Korea: Types of hospital where patients receive care and outcomes using national health insurance claims data
    Dong‐Woo Choi, Sun Jung Kim, Seungju Kim, Dong Wook Kim, Wonjeong Jeong, Kyu‐Tae Han
    Cancer Medicine.2023; 12(13): 14707.     CrossRef
What Affects Chronic Obstructive Pulmonary Disease in Korea?
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2016;7(6):339-340.   Published online December 31, 2016
DOI: https://doi.org/10.1016/j.phrp.2016.12.001
  • 2,570 View
  • 35 Download
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Fallen Flowers
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2016;7(5):279-280.   Published online October 31, 2016
DOI: https://doi.org/10.1016/j.phrp.2016.09.002
  • 2,880 View
  • 25 Download
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A moment of truth
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2016;7(4):211-212.   Published online August 31, 2016
DOI: https://doi.org/10.1016/j.phrp.2016.08.001
  • 2,834 View
  • 20 Download
PDF
What Would Be a Better Strategy for National University Hospital Management?
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2016;7(3):139-140.   Published online June 30, 2016
DOI: https://doi.org/10.1016/j.phrp.2016.05.003
  • 2,708 View
  • 18 Download
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Evaluation of Self-assessment in Cardiovascular Diseases Among Korean Older Population
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2016;7(2):75-76.   Published online April 30, 2016
DOI: https://doi.org/10.1016/j.phrp.2016.03.001
  • 3,072 View
  • 24 Download
  • 4 Crossref
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  • A 10-year trend in income disparity of cardiovascular health among older adults in South Korea
    Chiyoung Lee, Qing Yang, Eun-Ok Im, Eleanor Schildwachter McConnell, Sin-Ho Jung, Hyeoneui Kim
    SSM - Population Health.2020; 12: 100682.     CrossRef
  • Measurement of Socioeconomic Position in Research on Cardiovascular Health Disparities in Korea: A Systematic Review
    Chi-Young Lee, Yong-Hwan Lee
    Journal of Preventive Medicine and Public Health.2019; 52(5): 281.     CrossRef
  • Evaluación del riesgo cardiovascular en adultos mayores utilizando el modelo SCORE OP en una población latinoamericana: experiencia en Ecuador
    Ivan Sisa
    Medicina Clínica.2018; 150(3): 92.     CrossRef
  • Cardiovascular risk assessment in elderly adults using SCORE OP model in a Latin American population: The experience from Ecuador
    Ivan Sisa
    Medicina Clínica (English Edition).2018; 150(3): 92.     CrossRef
A Disease Around the Corner
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2016;7(1):1-2.   Published online February 28, 2016
DOI: https://doi.org/10.1016/j.phrp.2016.02.001
  • 3,291 View
  • 32 Download
  • 3 Crossref
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Citations

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  • Geographically Weighted Regression on dengue epidemic in Peninsular Malaysia
    Ayuna Sulekan, Jamaludin Suhaila, Nurmarni Athirah Abdul Wahid
    Journal of Physics: Conference Series.2021; 1988(1): 012099.     CrossRef
  • A Two-Patch Mathematical Model for Temperature-Dependent Dengue Transmission Dynamics
    Jung Kim, Yongin Choi, James Kim, Sunmi Lee, Chang Lee
    Processes.2020; 8(7): 781.     CrossRef
  • Potential effects of climate change on dengue transmission dynamics in Korea
    Hyojung Lee, Jung Eun Kim, Sunmi Lee, Chang Hyeong Lee, Shamala Devi Sekaran
    PLOS ONE.2018; 13(6): e0199205.     CrossRef
The Characteristics of Middle Eastern Respiratory Syndrome Coronavirus Transmission Dynamics in South Korea
Yunhwan Kim, Sunmi Lee, Chaeshin Chu, Seoyun Choe, Saeme Hong, Youngseo Shin
Osong Public Health Res Perspect. 2016;7(1):49-55.   Published online February 28, 2016
DOI: https://doi.org/10.1016/j.phrp.2016.01.001
  • 5,007 View
  • 29 Download
  • 68 Crossref
AbstractAbstract PDF
Objectives
The outbreak of Middle Eastern respiratory syndrome coronavirus (MERS-CoV) was one of the major events in South Korea in 2015. In particular, this study pays attention to formulating a mathematical model for MERS transmission dynamics and estimating transmission rates.
Methods
Incidence data of MERS-CoV from the government authority was analyzed for the first aim and a mathematical model was built and analyzed for the second aim of the study. A mathematical model for MERS-CoV transmission dynamics is used to estimate the transmission rates in two periods due to the implementation of intensive interventions.
Results
Using the estimates of the transmission rates, the basic reproduction number was estimated in two periods. Due to the superspreader, the basic reproduction number was very large in the first period; however, the basic reproduction number of the second period has reduced significantly after intensive interventions.
Conclusion
It turned out to be the intensive isolation and quarantine interventions that were the most critical factors that prevented the spread of the MERS outbreak. The results are expected to be useful to devise more efficient intervention strategies in the future.

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    Attaullah, Muhammad Jawad, Sultan Alyobi, Mansour F. Yassen, Wajaree Weera
    AIMS Mathematics.2023; 8(2): 3763.     CrossRef
  • Insight into Oncogenic Viral Pathways as Drivers of Viral Cancers: Implication for Effective Therapy
    Ahmed M. E. Elkhalifa, Showkat Ul Nabi, Ovais Shabir Shah, Showkeen Muzamil Bashir, Umar Muzaffer, Sofi Imtiyaz Ali, Imtiyaz Ahmad Wani, Nasser A. N. Alzerwi, Abozer Y. Elderdery, Awadh Alanazi, Fawaz O. Alenazy, Abdulaziz Hamdan A. Alharbi
    Current Oncology.2023; 30(2): 1924.     CrossRef
  • A Theoretical Investigation of the SARS-CoV-2 Model via Fractional Order Epidemiological Model
    Tahir Khan, Rahman Ullah, Thabet Abdeljawad, Manar A. Alqudah, Faizullah Faiz
    Computer Modeling in Engineering & Sciences.2023; 135(2): 1295.     CrossRef
  • Modeling the epidemic trend of middle eastern respiratory syndrome coronavirus with optimal control
    Bibi Fatima, Mehmet Yavuz, Mati ur Rahman, Fuad S. Al-Duais
    Mathematical Biosciences and Engineering.2023; 20(7): 11847.     CrossRef
  • Predictive Modeling and Control Strategies for the Transmission of Middle East Respiratory Syndrome Coronavirus
    Bibi Fatima, Mehmet Yavuz, Mati ur Rahman, Ali Althobaiti, Saad Althobaiti
    Mathematical and Computational Applications.2023; 28(5): 98.     CrossRef
  • A pandemic by novel corona virus, seventh member of human coronavirus
    Sohan A Patel, Nishith Patel
    IP International Journal of Comprehensive and Adva.2023; 8(4): 231.     CrossRef
  • On the analysis of Caputo fractional order dynamics of Middle East Lungs Coronavirus (MERS-CoV) model
    Qura Tul Ain, Naveed Anjum, Anwarud Din, Anwar Zeb, Salih Djilali, Zareen A. Khan
    Alexandria Engineering Journal.2022; 61(7): 5123.     CrossRef
  • The transmission dynamics of Middle East Respiratory Syndrome coronavirus
    Jia Rui, Qiupeng Wang, Jinlong Lv, Bin Zhao, Qingqing Hu, Heng Du, Wenfeng Gong, Zeyu Zhao, Jingwen Xu, Yuanzhao Zhu, Xingchun Liu, Yao Wang, Meng Yang, Li Luo, Qiuping Chen, Benhua Zhao, Yanhua Su, Jing-An Cui, Tianmu Chen
    Travel Medicine and Infectious Disease.2022; 45: 102243.     CrossRef
  • The asymptotic analysis of novel coronavirus disease via fractional-order epidemiological model
    Tahir Khan, Saeed Ahmad, Rahman Ullah, Ebenezer Bonyah, Khursheed J. Ansari
    AIP Advances.2022;[Epub]     CrossRef
  • MODELING FRACTIONAL-ORDER DYNAMICS OF MERS-COV VIA MITTAG-LEFFLER LAW
    HAIDONG QU, MATI UR RAHMAN, YE WANG, MUHAMMAD ARFAN, ADNAN
    Fractals.2022;[Epub]     CrossRef
  • Distinguishing viruses responsible for influenza-like illness
    Julie A. Spencer, Deborah P. Shutt, S. Kane Moser, Hannah Clegg, Helen J. Wearing, Harshini Mukundan, Carrie A. Manore
    Journal of Theoretical Biology.2022; 545: 111145.     CrossRef
  • ON THE ANALYSIS OF FRACTAL-FRACTIONAL ORDER MODEL OF MIDDLE EAST RESPIRATION SYNDROME CORONAVIRUS (MERS-CoV) UNDER CAPUTO OPERATOR
    LEI ZHANG, TAREQ SAEED, MIAO-KUN WANG, NUDRAT AAMIR, MUHAMMAD IBRAHIM
    Fractals.2022;[Epub]     CrossRef
  • Dynamics of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) involving fractional derivative with Mittag-Leffler kernel
    Tariq Mahmood, Fuad S. Al-Duais, Mei Sun
    Physica A: Statistical Mechanics and its Applicati.2022; 606: 128144.     CrossRef
  • Approximate solution for the nonlinear fractional order mathematical model
    Kahkashan Mahreen, Qura Tul Ain, Gauhar Rahman, Bahaaeldin Abdalla, Kamal Shah, Thabet Abdeljawad
    AIMS Mathematics.2022; 7(10): 19267.     CrossRef
  • Modeling and Dynamics of the Fractional Order SARS‐CoV‐2 Epidemiological Model
    Tahir Khan, Roman Ullah, Ali Yousef, Gul Zaman, Qasem M. Al-Mdallal, Yasser Alraey, M. De Aguiar
    Complexity.2022;[Epub]     CrossRef
  • Mathematical Modeling of COVID-19 Transmission in the Form of System of Integro-Differential Equations
    Alexander Domoshnitsky, Alexander Sitkin, Lea Zuckerman
    Mathematics.2022; 10(23): 4500.     CrossRef
  • A New Mathematical Model of COVID-19 with Quarantine and Vaccination
    Ihtisham Ul Haq, Numan Ullah, Nigar Ali, Kottakkaran Sooppy Nisar
    Mathematics.2022; 11(1): 142.     CrossRef
  • Product of natural evolution (SARS, MERS, and SARS-CoV-2); deadly diseases, from SARS to SARS-CoV-2
    Mohamad Hesam Shahrajabian, Wenli Sun, Qi Cheng
    Human Vaccines & Immunotherapeutics.2021; 17(1): 62.     CrossRef
  • Analysis of the fractional corona virus pandemic via deterministic modeling
    Nguyen Huy Tuan, Vo Viet Tri, Dumitru Baleanu
    Mathematical Methods in the Applied Sciences.2021; 44(1): 1086.     CrossRef
  • Mathematical analysis of SIRD model of COVID-19 with Caputo fractional derivative based on real data
    Kottakkaran Sooppy Nisar, Shabir Ahmad, Aman Ullah, Kamal Shah, Hussam Alrabaiah, Muhammad Arfan
    Results in Physics.2021; 21: 103772.     CrossRef
  • COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model
    Rachel Waema Mbogo, John W. Odhiambo
    Afrika Matematika.2021; 32(5-6): 757.     CrossRef
  • Fractal-fractional mathematical modeling and forecasting of new cases and deaths of COVID-19 epidemic outbreaks in India
    Mansour A. Abdulwasaa, Mohammed S. Abdo, Kamal Shah, Taher A. Nofal, Satish K. Panchal, Sunil V. Kawale, Abdel-Haleem Abdel-Aty
    Results in Physics.2021; 20: 103702.     CrossRef
  • Mathematical analysis of COVID-19 via new mathematical model
    Abdullah, Saeed Ahmad, Saud Owyed, Abdel-Haleem Abdel-Aty, Emad E. Mahmoud, Kamal Shah, Hussam Alrabaiah
    Chaos, Solitons & Fractals.2021; 143: 110585.     CrossRef
  • Modeling the transmission dynamics of middle eastern respiratory syndrome coronavirus with the impact of media coverage
    BiBi Fatima, Manar A. Alqudah, Gul Zaman, Fahd Jarad, Thabet Abdeljawad
    Results in Physics.2021; 24: 104053.     CrossRef
  • Theoretical and numerical analysis for transmission dynamics of COVID-19 mathematical model involving Caputo–Fabrizio derivative
    Sabri T. M. Thabet, Mohammed S. Abdo, Kamal Shah
    Advances in Difference Equations.2021;[Epub]     CrossRef
  • A computational tool for trend analysis and forecast of the COVID-19 pandemic
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    Applied Soft Computing.2021; 105: 107289.     CrossRef
  • Assessment of Prediction Models of Confirmed, Recovered and Deceased cases due to COVID-19
    P Rakshit, S Debnath, J Mistri, S Kumar
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  • Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model
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    Results in Physics.2021; 24: 104004.     CrossRef
  • Middle East respiratory syndrome coronavirus – The need for global proactive surveillance, sequencing and modeling
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    Travel Medicine and Infectious Disease.2021; 43: 102118.     CrossRef
  • Mathematical model of COVID-19 in Nigeria with optimal control
    Adesoye Idowu Abioye, Olumuyiwa James Peter, Hammed Abiodun Ogunseye, Festus Abiodun Oguntolu, Kayode Oshinubi, Abdullahi Adinoyi Ibrahim, Ilyas Khan
    Results in Physics.2021; 28: 104598.     CrossRef
  • The Effect of Feedback Controls on Stability in a Fractional-Order SI Epidemic Model
    Saad Z. Rida, Ahmed A. Farghaly, Fatma Hussien
    International Journal of Applied and Computational.2021;[Epub]     CrossRef
  • Superspreading and heterogeneity in transmission of SARS, MERS, and COVID-19: A systematic review
    Jingxuan Wang, Xiao Chen, Zihao Guo, Shi Zhao, Ziyue Huang, Zian Zhuang, Eliza Lai-yi Wong, Benny Chung-Ying Zee, Marc Ka Chun Chong, Maggie Haitian Wang, Eng Kiong Yeoh
    Computational and Structural Biotechnology Journal.2021; 19: 5039.     CrossRef
  • Middle East Respiratory Syndrome Coronavirus
    Jaffar A. Al-Tawfiq, Esam I. Azhar, Ziad A. Memish, Alimuddin Zumla
    Seminars in Respiratory and Critical Care Medicine.2021; 42(06): 828.     CrossRef
  • Early warning signal reliability varies with COVID-19 waves
    Duncan A. O'Brien, Christopher F. Clements
    Biology Letters.2021;[Epub]     CrossRef
  • Epidemiology of Coronavirus COVID-19: Forecasting the Future Incidence in Different Countries
    Johannes Stübinger, Lucas Schneider
    Healthcare.2020; 8(2): 99.     CrossRef
  • Super-spreading events and contribution to transmission of MERS, SARS, and SARS-CoV-2 (COVID-19)
    J.A. Al-Tawfiq, A.J. Rodriguez-Morales
    Journal of Hospital Infection.2020; 105(2): 111.     CrossRef
  • Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan
    Faïçal Ndaïrou, Iván Area, Juan J. Nieto, Delfim F.M. Torres
    Chaos, Solitons & Fractals.2020; 135: 109846.     CrossRef
  • A Generalized Overview of SARS-CoV-2: Where Does the Current Knowledge Stand?
    Hiya Islam, Ahsab Rahman, Jaasia Masud, Dipita Saha Shweta, Yusha Araf, Md. Asad Ullah, Syed Muktadir Al Sium, Bishajit Sarkar
    Electronic Journal of General Medicine.2020; 17(6): em251.     CrossRef
  • Optimal control strategies for the transmission risk of COVID-19
    Legesse Lemecha Obsu, Shiferaw Feyissa Balcha
    Journal of Biological Dynamics.2020; 14(1): 590.     CrossRef
  • A data-driven model to describe and forecast the dynamics of COVID-19 transmission
    Henrique Mohallem Paiva, Rubens Junqueira Magalhães Afonso, Igor Luppi de Oliveira, Gabriele Fernandes Garcia, Martin Chtolongo Simuunza
    PLOS ONE.2020; 15(7): e0236386.     CrossRef
  • SEIR model for COVID-19 dynamics incorporating the environment and social distancing
    Samuel Mwalili, Mark Kimathi, Viona Ojiambo, Duncan Gathungu, Rachel Mbogo
    BMC Research Notes.2020;[Epub]     CrossRef
  • Controlling the Spread of COVID-19: Optimal Control Analysis
    Chinwendu E. Madubueze, Sambo Dachollom, Isaac Obiajulu Onwubuya
    Computational and Mathematical Methods in Medicine.2020; 2020: 1.     CrossRef
  • Fractional order mathematical modeling of COVID-19 transmission
    Shabir Ahmad, Aman Ullah, Qasem M. Al-Mdallal, Hasib Khan, Kamal Shah, Aziz Khan
    Chaos, Solitons & Fractals.2020; 139: 110256.     CrossRef
  • Exploration of Superspreading Events in 2015 MERS-CoV Outbreak in Korea by Branching Process Models
    Seoyun Choe, Hee-Sung Kim, Sunmi Lee
    International Journal of Environmental Research an.2020; 17(17): 6137.     CrossRef
  • Study of transmission dynamics of COVID-19 mathematical model under ABC fractional order derivative
    Sabri T.M. Thabet, Mohammed S. Abdo, Kamal Shah, Thabet Abdeljawad
    Results in Physics.2020; 19: 103507.     CrossRef
  • A New Compartmental Epidemiological Model for COVID-19 with a Case Study of Portugal
    Ana P. Lemos-Paião, Cristiana J. Silva, Delfim F.M. Torres
    Ecological Complexity.2020; 44: 100885.     CrossRef
  • Mathematical modeling, analysis, and simulation of the COVID-19 pandemic with explicit and implicit behavioral changes
    Comfort Ohajunwa, Kirthi Kumar, Padmanabhan Seshaiyer
    Computational and Mathematical Biophysics.2020; 8(1): 216.     CrossRef
  • COVID-19 (Coronavirus Disease) Outbreak Prediction Using a Susceptible-Exposed-Symptomatic Infected-Recovered-Super Spreaders-Asymptomatic Infected-Deceased-Critical (SEIR-PADC) Dynamic Model
    Ahmad Sedaghat, Amir Mosavi
    SSRN Electronic Journal .2020;[Epub]     CrossRef
  • Comparative Analysis of Eleven Healthcare-Associated Outbreaks of Middle East Respiratory Syndrome Coronavirus (Mers-Cov) from 2015 to 2017
    Sibylle Bernard-Stoecklin, Birgit Nikolay, Abdullah Assiri, Abdul Aziz Bin Saeed, Peter Karim Ben Embarek, Hassan El Bushra, Moran Ki, Mamunur Rahman Malik, Arnaud Fontanet, Simon Cauchemez, Maria D. Van Kerkhove
    Scientific Reports.2019;[Epub]     CrossRef
  • Development of a recombinant replication-deficient rabies virus-based bivalent-vaccine against MERS-CoV and rabies virus and its humoral immunogenicity in mice
    Hirofumi Kato, Mutsuyo Takayama-Ito, Itoe Iizuka-Shiota, Shuetsu Fukushi, Guillermo Posadas-Herrera, Madoka Horiya, Masaaki Satoh, Tomoki Yoshikawa, Souichi Yamada, Shizuko Harada, Hikaru Fujii, Miho Shibamura, Takuya Inagaki, Kinjiro Morimoto, Masayuki S
    PLOS ONE.2019; 14(10): e0223684.     CrossRef
  • Healthcare-associated infections: the hallmark of Middle East respiratory syndrome coronavirus with review of the literature
    J.A. Al-Tawfiq, P.G. Auwaerter
    Journal of Hospital Infection.2019; 101(1): 20.     CrossRef
  • Middle East respiratory syndrome coronavirus in pediatrics: a report of seven cases from Saudi Arabia
    Sarah H. Alfaraj, Jaffar A. Al-Tawfiq, Talal A. Altuwaijri, Ziad A. Memish
    Frontiers of Medicine.2019; 13(1): 126.     CrossRef
  • Asymptomatic Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection: Extent and implications for infection control: A systematic review
    Jaffar A. Al-Tawfiq, Philippe Gautret
    Travel Medicine and Infectious Disease.2019; 27: 27.     CrossRef
  • Clinical predictors of mortality of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) infection: A cohort study
    Sarah H. Alfaraj, Jaffar A. Al-Tawfiq, Ayed Y. Assiri, Nojoom A. Alzahrani, Amal A. Alanazi, Ziad A. Memish
    Travel Medicine and Infectious Disease.2019; 29: 48.     CrossRef
  • Practical Guidance for Clinical Microbiology Laboratories: Viruses Causing Acute Respiratory Tract Infections
    Carmen L. Charlton, Esther Babady, Christine C. Ginocchio, Todd F. Hatchette, Robert C. Jerris, Yan Li, Mike Loeffelholz, Yvette S. McCarter, Melissa B. Miller, Susan Novak-Weekley, Audrey N. Schuetz, Yi-Wei Tang, Ray Widen, Steven J. Drews
    Clinical Microbiology Reviews.2018;[Epub]     CrossRef
  • Agent-Based Modeling for Super-Spreading Events: A Case Study of MERS-CoV Transmission Dynamics in the Republic of Korea
    Yunhwan Kim, Hohyung Ryu, Sunmi Lee
    International Journal of Environmental Research an.2018; 15(11): 2369.     CrossRef
  • Evaluation of visual triage for screening of Middle East respiratory syndrome coronavirus patients
    S.H. Alfaraj, J.A. Al-Tawfiq, P. Gautret, M.G. Alenazi, A.Y. Asiri, Z.A. Memish
    New Microbes and New Infections.2018; 26: 49.     CrossRef
  • A multi-faceted approach of a nursing led education in response to MERS-CoV infection
    Jaffar A. Al-Tawfiq, Siobhan Rothwell, Heather A. Mcgregor, Zeina A. Khouri
    Journal of Infection and Public Health.2018; 11(2): 260.     CrossRef
  • MERS transmission and risk factors: a systematic review
    Ji-Eun Park, Soyoung Jung, Aeran Kim, Ji-Eun Park
    BMC Public Health.2018;[Epub]     CrossRef
  • Working experiences of nurses during the Middle East respiratory syndrome outbreak
    Hee Sun Kang, Ye Dong Son, Sun‐Mi Chae, Colleen Corte
    International Journal of Nursing Practice.2018;[Epub]     CrossRef
  • Disaster medicine: current status and future directions of emergency medical team for overseas disaster crisis
    Minhong Choa, Jiyoung Noh, Hyun Soo Chung
    Journal of the Korean Medical Association.2017; 60(2): 149.     CrossRef
  • Estimating and modelling the transmissibility of Middle East Respiratory Syndrome CoronaVirus during the 2015 outbreak in the Republic of Korea
    Xu‐Sheng Zhang, Richard Pebody, Andre Charlett, Daniela de Angelis, Paul Birrell, Hunseok Kang, Marc Baguelin, Yoon Hong Choi
    Influenza and Other Respiratory Viruses.2017; 11(5): 434.     CrossRef
  • Influenza is more common than Middle East Respiratory Syndrome Coronavirus (MERS-CoV) among hospitalized adult Saudi patients
    Jaffar A. Al-Tawfiq, Ali A. Rabaan, Kareem Hinedi
    Travel Medicine and Infectious Disease.2017; 20: 56.     CrossRef
  • Dynamics of scientific publications on the MERS-CoV outbreaks in Saudi Arabia
    Ali A. Rabaan, Shamsah H. Al-Ahmed, Ali M. Bazzi, Jaffar A. Al-Tawfiq
    Journal of Infection and Public Health.2017; 10(6): 702.     CrossRef
  • Effects of Timely Control Intervention on the Spread of Middle East Respiratory Syndrome Coronavirus Infection
    Ilsu Choi, Dong Ho Lee, Yongkuk Kim
    Osong Public Health and Research Perspectives.2017; 8(6): 373.     CrossRef
  • Serologic responses of 42 MERS-coronavirus-infected patients according to the disease severity
    Jae-Hoon Ko, Marcel A. Müller, Hyeri Seok, Ga Eun Park, Ji Yeon Lee, Sun Young Cho, Young Eun Ha, Jin Yang Baek, So Hyun Kim, Ji-Man Kang, Yae-Jean Kim, Ik Joon Jo, Chi Ryang Chung, Myong-Joon Hahn, Christian Drosten, Cheol-In Kang, Doo Ryeon Chung, Jae-H
    Diagnostic Microbiology and Infectious Disease.2017; 89(2): 106.     CrossRef
  • Predictive factors for pneumonia development and progression to respiratory failure in MERS-CoV infected patients
    Jae-Hoon Ko, Ga Eun Park, Ji Yeon Lee, Ji Yong Lee, Sun Young Cho, Young Eun Ha, Cheol-In Kang, Ji-Man Kang, Yae-Jean Kim, Hee Jae Huh, Chang-Seok Ki, Byeong-Ho Jeong, Jinkyeong Park, Chi Ryang Chung, Doo Ryeon Chung, Jae-Hoon Song, Kyong Ran Peck
    Journal of Infection.2016; 73(5): 468.     CrossRef
  • Middle East respiratory syndrome coronavirus disease is rare in children: An update from Saudi Arabia
    Jaffar A Al-Tawfiq, Rana F Kattan, Ziad A Memish
    World Journal of Clinical Pediatrics.2016; 5(4): 391.     CrossRef
Two Epidemics and Global Health Security Agenda
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2015;6(6 Suppl):S1-S2.   Published online December 31, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.12.008
  • 3,046 View
  • 26 Download
  • 2 Crossref
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  • Successes and challenges of health systems governance towards universal health coverage and global health security: a narrative review and synthesis of the literature
    Ayal Debie, Resham B. Khatri, Yibeltal Assefa
    Health Research Policy and Systems.2022;[Epub]     CrossRef
  • Towards Resilient Health Systems in Sub-Saharan Africa: A Systematic Review of the English Language Literature on Health Workforce, Surveillance, and Health Governance Issues for Health Systems Strengthening
    Martin Amogre Ayanore, Norbert Amuna, Mark Aviisah, Adam Awolu, Daniel Dramani Kipo-Sunyehzi, Victor Mogre, Richard Ofori-Asenso, Jonathan Mawutor Gmanyami, Nuworza Kugbey, Margaret Gyapong
    Annals of Global Health.2019;[Epub]     CrossRef
To Be Imported or to Be Endemic? That is the Question
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2015;6(6):327-328.   Published online December 31, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.11.006
  • 2,656 View
  • 21 Download
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Norovirus outbreaks occurred in different settings in the Republic of Korea
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2015;6(5):281-282.   Published online October 31, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.11.001
  • 3,344 View
  • 20 Download
  • 5 Crossref
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  • Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020
    Yanwei Chen, Baiwei Liu, Yu Wang, Yewu Zhang, Hanqiu Yan, Weihong Li, Lingyu Shen, Yi Tian, Lei Jia, Daitao Zhang, Peng Yang, Zhiyong Gao, Quanyi Wang
    BMC Infectious Diseases.2023;[Epub]     CrossRef
  • Molecular Epidemiological Characteristics of Gastroenteritis Outbreaks Caused by Norovirus GII.4 Sydney [P31] Strains — China, October 2016–December 2020
    Xi Zhu, Yaqing He, Xingyan Wei, Xiangyu Kong, Qing Zhang, Jingxin Li, Miao Jin, Zhaojun Duan
    China CDC Weekly.2021; 3(53): 1127.     CrossRef
  • Norovirus Outbreak Surveillance, China, 2016–2018
    Miao Jin, Shuyu Wu, Xiangyu Kong, Huaping Xie, Jianguang Fu, Yaqing He, Weihong Feng, Na Liu, Jingxin Li, Jeanette J. Rainey, Aron J. Hall, Jan Vinjé, Zhaojun Duan
    Emerging Infectious Diseases.2020; 26(3): 437.     CrossRef
  • An increasing prevalence of non-GII.4 norovirus genotypes in acute gastroenteritis outbreaks in Huzhou, China, 2014-2018
    Liping Chen, Deshun Xu, Xiaofang Wu, Guangtao Liu, Lei Ji
    Archives of Virology.2020; 165(5): 1121.     CrossRef
  • Genotypic and Epidemiological Trends of Acute Gastroenteritis Associated with Noroviruses in China from 2006 to 2016
    Shu-Wen Qin, Ta-Chien Chan, Jian Cai, Na Zhao, Zi-Ping Miao, Yi-Juan Chen, She-Lan Liu
    International Journal of Environmental Research an.2017; 14(11): 1341.     CrossRef
Discrimination and Stigma
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2015;6(3):141-142.   Published online June 30, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.06.004
  • 2,630 View
  • 19 Download
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A Study on the Characteristics of Infrequent and Frequent Outpatients Visiting Korean Traditional Medical Facilities
Jinwon Yoon, Haemo Park, Chaeshin Chu, Sung-Yong Choi, Kibum Lee, Sundong Lee
Osong Public Health Res Perspect. 2015;6(3):170-183.   Published online June 30, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.06.001
  • 3,048 View
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AbstractAbstract PDF
Objectives
This study was intended to analyze the characteristics of infrequent and frequent outpatients visiting Korean medical facilities, and find the related variables of frequent users.
Methods
The data source was the Report on the Usage and Consumption of Korean Medicine (2011) published by the Ministry of Health and Welfare and Korea Institute for Health and Social Affairs. We analyzed outpatient data using SAS 9.2.
Results
As much as 46.6% of the patients used Korean medical services over 11 times in 3 months. The proportion of frequent users increased depending on age, and their proportion was high in the low-income and low-education group. People with musculoskeletal disease, stroke, hypertension, and obesity were more likely to use Korean medical services. In general, patients were satisfied with their treatment, with frequent outpatients being more satisfied than infrequent outpatients. In logistic regression analysis, age and musculoskeletal disease were significant determinants of frequency of use of Korean medical services.
Conclusion
Age, musculoskeletal disease, and specific diseases were highly associated with frequent Korean medical utilization.

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  • Identifying the Relationship between the Korean Medicine and Western Medicine in Factors Affecting Medical Service Use
    Young-eun Choi, Chul-woung Kim
    Healthcare.2022; 10(9): 1697.     CrossRef
  • Association between subjective health status and frequency of visits to acupuncture clinic: A cross-sectional study
    Takumi Kayo, Masao Suzuki, Ryuji Kato, Naoto Ishizaki, Tadamichi Mitsuma, Fumihiko Fukuda, Vijay S. Gc
    PLOS ONE.2022; 17(11): e0277686.     CrossRef
  • Characteristics of Herbal Medicine Users and Adverse Events Experienced in South Korea: A Survey Study
    Soobin Jang, Kyeong Han Kim, Seung-Ho Sun, Ho-Yeon Go, Eun-Kyung Lee, Bo-Hyoung Jang, Yong-Cheol Shin, Seong-Gyu Ko, Karin Kraft
    Evidence-Based Complementary and Alternative Medic.2017;[Epub]     CrossRef
  • Utilization Patterns of Korean Medicine: An Analysis of the National Health Insurance Cohort Database from 2002 to 2013
    Sunju Park, In-Hwan Oh, Bo-Hyoung Jang, Minjung Park, YongCheol Shin, Kanghee Moon, Seong-Gyu Ko
    The Journal of Alternative and Complementary Medic.2016; 22(10): 824.     CrossRef
From Seoul to Lima: Korean Doctors in Peru
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2015;6(2):71-72.   Published online April 30, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.04.001
  • 2,549 View
  • 23 Download
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Doing Mathematics with Aftermath of Pandemic Influenza 2009
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2015;6(1):1-2.   Published online February 28, 2015
DOI: https://doi.org/10.1016/j.phrp.2015.01.001
  • 2,859 View
  • 26 Download
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Assessment of Intensive Vaccination and Antiviral Treatment in 2009 Influenza Pandemic in Korea
Chaeshin Chu, Sunmi Lee
Osong Public Health Res Perspect. 2015;6(1):47-51.   Published online February 28, 2015
DOI: https://doi.org/10.1016/j.phrp.2014.11.007
  • 3,182 View
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AbstractAbstract PDF
Objectives
We characterized and assessed public health measures, including intensive vaccination and antiviral treatment, implemented during the 2009 influenza pandemic in the Republic of Korea.
Methods
A mathematical model for the 2009 influenza pandemic is formulated. The transmission rate, the vaccination rate, the antiviral treatment rate, and the hospitalized rate are estimated using the least-squares method for the 2009 data of the incidence curves of the infected, vaccinated, treated, and hospitalized.
Results
The cumulative number of infected cases has reduced significantly following the implementation of the intensive vaccination and antiviral treatment. In particular, the intensive vaccination was the most critical factor that prevented severe outbreak.
Conclusion
We have found that the total infected proportion would increase by approximately six times under the half of vaccination rates.

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  • Modeling influenza transmission dynamics with media coverage data of the 2009 H1N1 outbreak in Korea
    Yunhwan Kim, Ana Vivas Barber, Sunmi Lee, Roberto Barrio
    PLOS ONE.2020; 15(6): e0232580.     CrossRef
  • Doing Mathematics with Aftermath of Pandemic Influenza 2009
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2015; 6(1): 1.     CrossRef
Is Tuberculosis Still the Number One Infectious Disease in Korea?
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2014;5(Suppl):S1-S2.   Published online December 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.11.003
  • 2,844 View
  • 25 Download
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Trends and Characteristics of HIV Infection among Suspected Tuberculosis Cases in Public Health Centers in Korea: 2001–2013
Meekyung Kee, Kyoung-Ho Lee, Sae-Young Lee, Chun Kang, Chaeshin Chu
Osong Public Health Res Perspect. 2014;5(Suppl):S37-S42.   Published online December 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.11.002
  • 3,352 View
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AbstractAbstract PDF
Objectives
The Republic of Korea reports approximately 35,000 new tuberculosis (TB) patients each year, and the number of HIV-infected individuals is steadily increasing. Public health centers (PHCs) conduct TB diagnosis and treatment for risk groups in communities. This study aimed to identify possible trends and characteristics of HIV infection among suspected TB cases in PHCs.
Methods
Study subjects were suspected TB cases in PHCs who agreed to be tested for HIV from 2001 to 2013. Trends in HIV seroprevalence were assessed through a series of annual cross-sectional analyses. We analyzed suspected TB cases, and HIV-infected individuals among suspected TB cases, by gender, age, nationality, and region.
Results
The number of suspected tuberculosis cases who took an HIV test in PHCs was approximately 6,000 each year from 2001 to 2013. Among the suspected TB cases who took an HIV test, the number of those aged 20–39 is gradually decreasing, while the number of those aged 50–69 is increasing. During this period, 32 HIV-infected individuals were identified; the majority were men (94%), aged 30–49 (68%), Korean (94%), and residents in a metropolitan area (53%). HIV seroprevalence decreased from 8.2 per 10,000 persons in 2001 to 1.9 per 10,000 persons in 2013.
Conclusion
This study has identified trends and characteristics of HIV infection among suspected tuberculosis cases in PHCs. This national data provides a basis for public health policy for HIV and tuberculosis infections.

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  • Is Tuberculosis Still the Number One Infectious Disease in Korea?
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5: S1.     CrossRef
Out of Africa, Into Global Health Security Agenda
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2014;5(6):313-314.   Published online December 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.11.004
  • 3,212 View
  • 32 Download
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  • Towards Resilient Health Systems in Sub-Saharan Africa: A Systematic Review of the English Language Literature on Health Workforce, Surveillance, and Health Governance Issues for Health Systems Strengthening
    Martin Amogre Ayanore, Norbert Amuna, Mark Aviisah, Adam Awolu, Daniel Dramani Kipo-Sunyehzi, Victor Mogre, Richard Ofori-Asenso, Jonathan Mawutor Gmanyami, Nuworza Kugbey, Margaret Gyapong
    Annals of Global Health.2019;[Epub]     CrossRef
  • Assessing National Public Health Law to Prevent Infectious Disease Outbreaks: Immunization Law as a Basis for Global Health Security
    Tsion Berhane Ghedamu, Benjamin Mason Meier
    Journal of Law, Medicine & Ethics.2019; 47(3): 412.     CrossRef
  • The West Africa Disaster Preparedness Initiative: Strengthening National Capacities for All-Hazards Disaster Preparedness
    Melinda J. Morton Hamer, Paul L. Reed, Jane D. Greulich, Gabor D. Kelen, Nicole A. Bradstreet, Charles W. Beadling
    Disaster Medicine and Public Health Preparedness.2017; 11(4): 431.     CrossRef
  • Two Epidemics and Global Health Security Agenda
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2015; 6(6): S1.     CrossRef
Roll the Dice
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2014;5(5):243-244.   Published online October 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.09.001
  • 2,724 View
  • 22 Download
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Summing Up Again
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2014;5(4):177-178.   Published online August 31, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.07.001
  • 2,666 View
  • 18 Download
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A Period of Storm and Stress
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2014;5(3):117-118.   Published online June 30, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.05.001
  • 2,429 View
  • 33 Download
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Sound in the Air
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2014;5(2):75-76.   Published online April 30, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.04.001
  • 2,836 View
  • 22 Download
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A Study of High-Risk Drinking Patterns Among Generations Based on the 2009 Korea National Health and Nutrition Examination Survey
Yeongseon Hong, Sungsoo Chun, Mieun Yun, Lydia Sarponmaa Asante, Chaeshin Chu
Osong Public Health Res Perspect. 2014;5(1):46-53.   Published online February 28, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.01.006
  • 3,213 View
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AbstractAbstract PDF
Objectives
The aim of this study was to identify how the drinking patterns of a generation on the paternal side affect those of the next generations by estimating the number of high-risk drinkers by generation according to the Alcohol Use Disorder Identification Test.
Methods
Data were selected from the 2009 Korea National Health and Nutrition Examination Survey conducted by the Korea Centers for Disease Control and Prevention and were analyzed using SPSS 18.0.
Results
Later generations started drinking earlier (62.4%, 71.8% and 91.1%, respectively). The majority of the second generation consumed more than 2–4 drinks a month (83.7%), but only a small proportion experienced difficulty in everyday life (9.6%), felt repentance (9.6%), or experienced memory loss (17.9%) after drinking. Unmarried third-generation adults with high-risk-drinking fathers reported more frequent alcohol consumption [odds ratio (OR) 1.441), greater amounts on one occasion (>7 cups for men, OR 1.661; > 5 cups for women, OR 2.078), temperance failure (OR 2.377), and repentance after drinking (OR 1.577). Unmarried third-generation adults with high-risk-drinking grandfathers consumed greater amounts of alcohol on one occasion (OR 3.642), and unmarried third-generation women more frequently consumed large amounts of alcohol (>5 cups, OR 4.091). Unmarried third-generation adults with high-risk-drinking fathers were more likely to exhibit high-risk drinking patterns (OR 1.608). Second-generation individuals from a high-risk-drinking first generation were more likely to engage in high-risk drinking (OR 3.705).
Conclusion
High-risk drinking by a generation significantly affects the high-risk drinking patterns of subsequent generations.

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  • Age at onset of alcohol consumption and its association with alcohol misuse in adulthood
    Soo Y. Kim, Sung H. Jeong, Eun‐Cheol Park
    Neuropsychopharmacology Reports.2023; 43(1): 40.     CrossRef
  • Alcohol consumption frequency or alcohol intake per drinking session: Which has a larger impact on the metabolic syndrome and its components?
    Sarah Soyeon Oh, Woorim Kim, Kyu-Tae Han, Eun-Cheol Park, Sung-In Jang
    Alcohol.2018; 71: 15.     CrossRef
Journal Publishing: Never Ending Saga
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2014;5(1):1-2.   Published online February 28, 2014
DOI: https://doi.org/10.1016/j.phrp.2014.01.005
  • 3,086 View
  • 22 Download
  • 1 Crossref
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  • Summing Up Again
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(4): 177.     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
  • 3,260 View
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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.

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  • Intelligent Health Care and Diseases Management System: Multi-Day-Ahead Predictions of COVID-19
    Ahed Abugabah, Farah Shahid
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  • Prevalence of HIV in Kazakhstan 2010–2020 and Its Forecasting for the Next 10 Years
    Kamilla Mussina, Shirali Kadyrov, Ardak Kashkynbayev, Sauran Yerdessov, Gulnur Zhakhina, Yesbolat Sakko, Amin Zollanvari, Abduzhappar Gaipov
    HIV/AIDS - Research and Palliative Care.2023; Volume 15: 387.     CrossRef
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    Process Safety and Environmental Protection.2021; 149: 223.     CrossRef
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    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;[Epub]     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
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  • 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
    Konstantinos I. Papageorgiou, Katarzyna Poczeta, Elpiniki Papageorgiou, Vassilis C. Gerogiannis, George 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
What is Next for HIV/AIDS in Korea?
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2013;4(6):291-292.   Published online December 31, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.11.001
  • 2,720 View
  • 31 Download
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How to Manage a Public Health Crisis and Bioterrorism in Korea
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2013;4(5):223-224.   Published online October 31, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.09.010
  • 3,222 View
  • 27 Download
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  • Global overview of early public policies towards the Covid-19 pandemic: Specific case review of Lebanon
    Martin Raad, Sandra El Rafii, Farah Doumani, Nour Doumani, Mohamed el Cheikh
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    Hazhir Moradi, Atefeh Vaezi
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Introduction of the Republic of Korea–the United States of America's Joint Exercise Against Biothreats in 2013: Able Response 13
Seong Sun Kim, Dong Whan Oh, Hyun Jung Jo, Chaeshin Chu
Osong Public Health Res Perspect. 2013;4(5):285-290.   Published online October 31, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.09.009
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AbstractAbstract PDF
The Republic of Korea (ROK) and the the United States of America (USA) has held joint exercises to respond to biothreats in the Korean Peninsula since 2011. The exercise was called Able Response (AR) and it aims to coordinate interministerial procedures inside Korea and international procedures in requesting the medical resources urgently between ROK and USA, and among ROK and the United Nations, and nongovernmental organizations. AR13 was a functional exercise with a scenario that presumed a series of attack by terrorists, dispersing Bacillus anthracis in Seoul. The participants conducted exercises with action cells and using point-to-point communication system. It was followed by Senior Leadership Seminar participated by high-ranking officials in ROK and USA to discuss possible collaboration in advance. AR and its following actions will fortify collaboration between ROK and USA and enhance the capability of countermeasures against biothreats in Korea.

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    Disaster Medicine and Public Health Preparedness.2022; 16(5): 2149.     CrossRef
  • Biodefence research two decades on: worth the investment?
    Carrie M Long, Andrea Marzi
    The Lancet Infectious Diseases.2021; 21(8): e222.     CrossRef
  • Militaries and global health: peace, conflict, and disaster response
    Joshua Michaud, Kellie Moss, Derek Licina, Ron Waldman, Adam Kamradt-Scott, Maureen Bartee, Matthew Lim, Jamie Williamson, Frederick Burkle, Christina S Polyak, Nicholas Thomson, David L Heymann, Louis Lillywhite
    The Lancet.2019; 393(10168): 276.     CrossRef
  • A Joint Exercise against Intentional Biothreats
    Hae-Wol Cho, Chaeshin Chu
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    Sangwoo Tak, Anton Jareb, Suon Choi, Marvin Sikes, Yeon Hwa Choi, Hyeong-wook Boo
    Osong Public Health and Research Perspectives.2018; 9(1): 32.     CrossRef
  • What is the value of health emergency preparedness exercises? A scoping review study
    Elena Skryabina, Gabriel Reedy, Richard Amlôt, Peter Jaye, Paul Riley
    International Journal of Disaster Risk Reduction.2017; 21: 274.     CrossRef
  • Syndromic Surveillance System for Korea–US Joint Biosurveillance Portal: Design and Lessons Learned
    Chulwoo Rhee, Howard Burkom, Chang-gyo Yoon, Miles Stewart, Yevgeniy Elbert, Aaron Katz, Sangwoo Tak
    Health Security.2016; 14(3): 152.     CrossRef
  • How to Manage a Public Health Crisis and Bioterrorism in Korea
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Public Health Crisis Preparedness and Response in Korea
Hye-Young Lee, Mi-Na Oh, Yong-Shik Park, Chaeshin Chu, Tae-Jong Son
Osong Public Health Res Perspect. 2013;4(5):278-284.   Published online October 31, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.09.008
  • 3,880 View
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AbstractAbstract PDF
Since the 2006 Pandemic Influenza Preparedness and Response Plan according to the World Health Organization’s recommendation, the Republic of Korea has prepared and periodically evaluated the plan to respond to various public health crises including pandemic influenza. Korea has stockpiled 13,000,000 doses of antiviral drugs covering 26% of the Korean population and runs 519 isolated beds in 16 medical institutions. The division of public health crisis response in Korea Centers for Disease Control and Prevention are in charge of responding to public health crises caused by emerging infectious diseases including severe acute respiratory syndrome, avian influenza human infection, and pandemic influenza. Its job description includes preparing for emerging infectious diseases, securing medical resources during a crisis, activating the emergency response during the crisis, and fortification of capabilities of public health personnel. It could evolve into a comprehensive national agency to deal with public health crisis based on the experience of previous national emerging infectious diseases.

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  • The Evolution of Vigilance and Its Atrophy Preceding the COVID-19 Global Pandemic
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  • The Korean government’s public health responses to the COVID-19 epidemic through the lens of industrial policy
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    International Journal of Environmental Research an.2020; 17(9): 3181.     CrossRef
  • Lessons learned from Korea: COVID-19 pandemic
    Hazhir Moradi, Atefeh Vaezi
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  • Lesson Learned from the Power of Open Data: Resolving the Mask Shortage Problem Caused by COVID-19 in South Korea
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  • A Systematic Narrative Review of Comprehensive Preparedness Strategies of Healthcare Resources for a Large Resurgence of COVID-19 Nationally, with Local or Regional Epidemics: Present Era and Beyond
    Young Kyung Yoon, Jacob Lee, Sang Il Kim, Kyong Ran Peck
    Journal of Korean Medical Science.2020;[Epub]     CrossRef
  • Metapopulation model using commuting flow for national spread of the 2009 H1N1 influenza virus in the Republic of Korea
    Jonggul Lee, Bo Youl Choi, Eunok Jung
    Journal of Theoretical Biology.2018; 454: 320.     CrossRef
  • Enhancing ‘Whole-of-Government’ Response to Biological Events in Korea: Able Response 2014
    Sangwoo Tak, Anton Jareb, Suon Choi, Marvin Sikes, Yeon Hwa Choi, Hyeong-wook Boo
    Osong Public Health and Research Perspectives.2018; 9(1): 32.     CrossRef
  • Mathematical model of transmission dynamics and optimal control strategies for 2009 A/H1N1 influenza in the Republic of Korea
    Soyoung Kim, Jonggul Lee, Eunok Jung
    Journal of Theoretical Biology.2017; 412: 74.     CrossRef
  • Syndromic Surveillance System for Korea–US Joint Biosurveillance Portal: Design and Lessons Learned
    Chulwoo Rhee, Howard Burkom, Chang-gyo Yoon, Miles Stewart, Yevgeniy Elbert, Aaron Katz, Sangwoo Tak
    Health Security.2016; 14(3): 152.     CrossRef
  • Changes of Global Infectious Disease Governance in 2000s: Rise of Global Health Security and Transformation of Infectious Disease Control System in South Korea
    Eun Kyung CHOI, Jong-Koo LEE
    Korean Journal of Medical History.2016; 25(3): 489.     CrossRef
  • Crisis prevention and management by infection control nurses during the Middle East respiratory coronavirus outbreak in Korea
    Jeong Sil Choi, Kyung Mi Kim
    American Journal of Infection Control.2016; 44(4): 480.     CrossRef
  • Ebola virus disease in nonendemic countries
    Samson Sai-Yin Wong, Sally Cheuk-Ying Wong
    Journal of the Formosan Medical Association.2015; 114(5): 384.     CrossRef
  • A spatial–temporal transmission model and early intervention policies of 2009 A/H1N1 influenza in South Korea
    Jonggul Lee, Eunok Jung
    Journal of Theoretical Biology.2015; 380: 60.     CrossRef
  • How to Manage a Public Health Crisis and Bioterrorism in Korea
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    Osong Public Health and Research Perspectives.2013; 4(5): 223.     CrossRef
Epidemic Intelligence Service Officers and Field Epidemiology Training Program in Korea
Geun-Yong Kwon, Shinje Moon, Wooseok Kwak, Jin Gwack, Chaeshin Chu, Seung-Ki Youn
Osong Public Health Res Perspect. 2013;4(4):215-221.   Published online August 31, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.07.001
  • 4,268 View
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AbstractAbstract PDF
Korea has adopted Epidemic Intelligence Service (EIS) officers through the Field Epidemiology Training Program (FETP) since 1999 for systematic control of emerging and re-emerging infectious diseases. Graduates of medical schools in Korea are selected and serve as public health doctors (PHDs) for their mandatory military service. The duration of service is 3 years and PHDs comprise general practitioners and specialists. Some PHDs are selected as EIS officers with 3 weeks basic FETP training and work for central and provincial public health authorities to conduct epidemiological investigations. The total number of EIS officers is 31 as of 2012. The Korea Centers for Disease Control and Prevention (KCDC) has 12 specialists, whereas specialists and each province has one or two EIS officers to administer local epidemiological investigations in 253 public health centers. The Korean EIS officers have successfully responded and prevented infectious diseases, but there is a unique limitation: the number of PHDs in Korea is decreasing and PHDs are not allowed to stay outside Korea, which makes it difficult to cope with overseas infectious diseases. Furthermore, after 3 years service, they quit and their experiences are not accumulated. KCDC has hired full-time EIS officers since 2012 to overcome this limitation.

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  • A resposta da Coreia do Sul à pandemia de COVID-19: lições aprendidas e recomendações a gestores
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    Cadernos de Saúde Pública.2022;[Epub]     CrossRef
  • Turnover Intention among Field Epidemiologists in South Korea
    Sukhyun Ryu
    International Journal of Environmental Research an.2020; 17(3): 949.     CrossRef
  • National Response to COVID-19 in the Republic of Korea and Lessons Learned for Other Countries
    Juhwan Oh, Jong-Koo Lee, Dan Schwarz, Hannah L. Ratcliffe, Jeffrey F. Markuns, Lisa R. Hirschhorn
    Health Systems & Reform.2020;[Epub]     CrossRef
  • Steering the Private Sector in COVID-19 Diagnostic Test Kit Development in South Korea
    Sora Lee
    Frontiers in Public Health.2020;[Epub]     CrossRef
  • Experience of 16 years and its associated challenges in the Field Epidemiology Training Program in Korea
    Moo-Sik Lee, Eun-Young Kim, Sang-Won Lee
    Epidemiology and Health.2017; 39: e2017058.     CrossRef
  • The direction of restructuring of a Korea field epidemiology training program through questionnaire survey among communicable disease response staff in Korea
    Moo Sik Lee, Kwan Lee, Jee-Hyuk Park, Jee-Young Hong, Min-Young Jang, Byoung-Hak Jeon, Sang-Yun Cho, Sun-Ja Choi, JeongIk Hong
    Epidemiology and Health.2017; 39: e2017032.     CrossRef
  • Review for the Korean Health Professionals and International Cooperation Doctors Dispatched to Peru by the Korea International Cooperation Agency (KOICA)
    Bongyoung Kim
    Osong Public Health and Research Perspectives.2015; 6(2): 133.     CrossRef
  • From Seoul to Lima: Korean Doctors in Peru
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2015; 6(2): 71.     CrossRef
  • Emerging Pathogens and Vehicles of Food- and Water-borne Disease Outbreaks in Korea, 2007–2012
    Shinje Moon, Il-Woong Sohn, Yeongseon Hong, Hyungmin Lee, Ji-Hyuk Park, Geun-Yong Kwon, Sangwon Lee, Seung-Ki Youn
    Osong Public Health and Research Perspectives.2014; 5(1): 34.     CrossRef
Was the Mass Vaccination Effective During the Influenza Pandemic 2009–2010 in Korea?
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2013;4(4):177-178.   Published online August 31, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.07.003
  • 3,410 View
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  • Assessment of Intensive Vaccination and Antiviral Treatment in 2009 Influenza Pandemic in Korea
    Chaeshin Chu, Sunmi Lee
    Osong Public Health and Research Perspectives.2015; 6(1): 47.     CrossRef
Evaluation of the Effectiveness of Pandemic Influenza A(H1N1) 2009 Vaccine Based on an Outbreak Investigation During the 2010–2011 Season in Korean Military Camps
Kyo-Hyun Kim, Yoon Gu Choi, Hyun-Bae Yoon, Jung-Woo Lee, Hyun-Wook Kim, Chaeshin Chu, Young-Joon Park
Osong Public Health Res Perspect. 2013;4(4):209-214.   Published online August 31, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.07.002
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AbstractAbstract PDF
Objectives
In December 2010, there was an outbreak of acute febrile respiratory disease in many Korean military camps that were not geographically related. A laboratory analysis confirmed a number of these cases to be infected by the pandemic influenza A(H1N1) 2009 (H1N1pdm09) virus. Because mass vaccination against H1N1pdm09 was implemented at the infected military camps eleven months ago, the outbreak areas in which both vaccinated and nonvaccinated individuals were well mixed, gave us an opportunity to evaluate the effectiveness of H1N1pdm09 vaccine through a retrospective cohort study design.
Methods
A self-administered questionnaire was distributed to the three military camps in which the outbreak occurred for case detection, determination of vaccination status, and characterization of other risk factors. The overall response rate was 86.8% (395/455). Case was defined as fever (≥38 °C) with cough or sore throat, influenza-like illness (ILI), and vaccination status verified by vaccination registry. Crude vaccine effectiveness (VE) was calculated as “1 − attack rate in vaccinated individuals/attack rate in nonvaccinated individuals”, and adjusted VE was calculated as “1 – odds ratio” using logistic regression adjusted for potential confounding factor. A number of ILI definitions were used to test the robustness of the result.
Results
The attack rate of ILI was 12.8% in register-verified vaccinated individuals and 24.0% in nonvaccinated individuals. The crude VE was thus calculated to be 46.8% [95% confidence interval (CI): 14.5–66.9]. The adjusted VE rate was 46.8% (95% CI: –9.4 to 74.1). Various combinations of ILI symptoms also showed similar VE rates.
Conclusion
We evaluated the effectiveness of H1N1pdm09 vaccine in the 2010–2011 season in an outbreak setting. Although the result was not sensitive to any analytical method used and ILI case definition, the magnitude of effectiveness was lower than estimated in the 2009–2010 season.

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  • Assessment of Intensive Vaccination and Antiviral Treatment in 2009 Influenza Pandemic in Korea
    Chaeshin Chu, Sunmi Lee
    Osong Public Health and Research Perspectives.2015; 6(1): 47.     CrossRef
  • Was the Mass Vaccination Effective During the Influenza Pandemic 2009–2010 in Korea?
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2013; 4(4): 177.     CrossRef
Years of Epidemics (2009–2011): Pandemic Influenza and Foot-and-Mouth Disease Epidemic in Korea
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2013;4(3):125-126.   Published online June 30, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.05.001
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  • Global Foot-and-Mouth Disease Research Update and Gap Analysis: 2 - Epidemiology, Wildlife and Economics
    T. J. D. Knight-Jones, L. Robinson, B. Charleston, L. L. Rodriguez, C. G. Gay, K. J. Sumption, W. Vosloo
    Transboundary and Emerging Diseases.2016; 63: 14.     CrossRef
Fires in the Neighborhood
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2013;4(2):67-67.   Published online April 30, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.03.007
  • 2,813 View
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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
  • 4,291 View
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AbstractAbstract 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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The Geographical and Economical Impact of Scrub Typus, the Fastest-growing Vector-borne Disease in Korea
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2013;4(1):1-3.   Published online February 28, 2013
DOI: https://doi.org/10.1016/j.phrp.2013.01.001
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  • A Study on the Public Health Disasters using Meteorological Factor: Scrub Typhus in South Korea
    Younggon Lee, Kyuhyun Choi, Jaewon Kwak
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  • Scrub Typhus Incidence Modeling with Meteorological Factors in South Korea
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Spatial Distribution Analysis of Scrub Typhus in Korea
Hong Sung Jin, Chaeshin Chu, Dong Yeob Han
Osong Public Health Res Perspect. 2013;4(1):4-15.   Published online February 28, 2013
DOI: https://doi.org/10.1016/j.phrp.2012.12.007
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AbstractAbstract PDF
Objective: This study analyzes the spatial distribution of scrub typhus in Korea.
Methods
A spatial distribution of Orientia tsutsugamushi occurrence using a geographic information system (GIS) is presented, and analyzed by means of spatial clustering and correlations.
Results
The provinces of Gangwon-do and Gyeongsangbuk-do show a low incidence throughout the year. Some districts have almost identical environmental conditions of scrub typhus incidence. The land use change of districts does not directly affect the incidence rate.
Conclusion
GIS analysis shows the spatial characteristics of scrub typhus. This research can be used to construct a spatial-temporal model to understand the epidemic tsutsugamushi.

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  • Three‐year surveillance (2016–2018) of chigger mites vector for tsutsugamushi disease in the Hwaseong‐Si area of Gyeonggi‐Do, Republic of Korea
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    Entomological Research.2020; 50(2): 63.     CrossRef
  • Surveillance of Chigger Mite Vectors for Tsutsugamushi Disease in the Hwaseong Area, Gyeonggi-do, Republic of Korea, 2015
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  • The Geographical and Economical Impact of Scrub Typus, the Fastest-growing Vector-borne Disease in Korea
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A New Statistical Approach to Analyze Plasmodium vivax Malaria Endemic in Korea
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2012;3(4):191-191.   Published online December 31, 2012
DOI: https://doi.org/10.1016/j.phrp.2012.11.004
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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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AbstractAbstract 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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  • 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
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  • Effects of climate change on Plasmodium vivax malaria transmission dynamics: A mathematical modeling approach
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    Applied Mathematics and Computation.2019; 347: 616.     CrossRef
  • Spatially Filtered Multilevel Analysis on Spatial Determinants for Malaria Occurrence in Korea
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  • Is it necessary to take anthelmintics every year in Korea?
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  • Chemotherapeutic drugs for common parasitic diseases in Korea
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Basis for Korean Genome Study
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2012;3(3):119-120.   Published online June 30, 2012
DOI: https://doi.org/10.1016/j.phrp.2012.07.011
  • 2,766 View
  • 29 Download
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Opening of the National Biobank of Korea as the Infrastructure of Future Biomedical Science in Korea
Sang Yun Cho, Eun Jung Hong, Jung Min Nam, Bogkee Han, Chaeshin Chu, Ok Park
Osong Public Health Res Perspect. 2012;3(3):177-184.
DOI: https://doi.org/10.1016/j.phrp.2012.07.004
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AbstractAbstract PDF
On April 26, 2012, the Korea National Institute of Health officially held the opening ceremony of newly dedicated biobank building, ‘National Biobank of Korea’. The stocked biospecimens and related information have been distributed for medical and public health researches. The Korea Biobank Project, which was initiated in 2008, constructed the Korea Biobank Network consisting of the National Biobank of Korea (NBK) with 17 regional biobanks in Korea. As of December 2011, a total of 525,416 biospecimens with related information have been secured: 325,952 biospecimens from the general population obtained through cohort studies and 199,464 biospecimens of patients from regional biobanks. A large scale genomic study, Korea Association Resource (KARE) and many researches utilized the biospecimens secured through Korea Genome Epidemiology Study (KoGES) and Korea Biobank Project (KBP). Construction of ‘National Biobank of Korea’, a dedicated biobank building at Osong means that NBK can manage and check quality of the biospecimens with promising distribution of 26 million vials of biospecimen, which provide the infrastructure for the development of health technology in Korea. The NBK and the National Library of Medicine (to be constructed in 2014) will play a central role in future biomedical research in Korea.

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    Open Access Macedonian Journal of Medical Sciences.2022; 10(A): 1067.     CrossRef
  • The Association of Serum High-Sensitivity C-Reactive Protein Level With the Risk of Site-Specific Cancer Mortality: The Health Examinees (HEXA) Study Cohort
    Sang-Ah Lee, Sung-Ok Kwon, Minkyo Song, Ji-Yeob Choi, Aesun Shin, Xiao-Ou Shu, Wei Zheng, Jong-Koo Lee, Daehee Kang
    American Journal of Epidemiology.2022; 191(12): 2002.     CrossRef
  • Asian-specific 3’UTR variant in CDKN2B associated with risk of pituitary adenoma
    Byeong Ju Youn, Hyun Sub Cheong, Suhg Namgoong, Lyoung Hyo Kim, In Ki Baek, Jeong-Hyun Kim, Seon-Jin Yoon, Eui Hyun Kim, Se Hoon Kim, Jong Hee Chang, Sun Ho Kim, Hyoung Doo Shin
    Molecular Biology Reports.2022; 49(11): 10339.     CrossRef
  • Two independent variants of epidermal growth factor receptor associated with risk of glioma in a Korean population
    In Ki Baek, Hyun Sub Cheong, Seok Namgoong, Jeong-Hyun Kim, Seok-Gu Kang, Seon-Jin Yoon, Se Hoon Kim, Jong Hee Chang, Lyoung Hyo Kim, Hyoung Doo Shin
    Scientific Reports.2022;[Epub]     CrossRef
  • The concept of the national information platform of biobanks of the Russian Federation
    A. N. Meshkov, O. Yu. Yartseva, A. L. Borisova, M. S. Pokrovskaya, O. M. Drapkina
    Cardiovascular Therapy and Prevention.2022; 21(11): 3417.     CrossRef
  • Prawne aspekty badań genomicznych i biobankowania w regionie Azji Wschodniej
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    Gdańskie Studia Azji Wschodniej.2022; (22): 24.     CrossRef
  • PheWAS-ME: a web-app for interactive exploration of multimorbidity patterns in PheWAS
    Nick Strayer, Jana K Shirey-Rice, Yu Shyr, Joshua C Denny, Jill M Pulley, Yaomin Xu, Lu Zhiyong
    Bioinformatics.2021; 37(12): 1778.     CrossRef
  • Introduction to the human disease resource search and distribution platform through the Korea Biobank Network portal
    Young Hwan Kim, Hong Rim Cha, Ji Eun Lee, Se Eun Cha, Yeong Jin Choi
    Journal of the Korean Medical Association.2021; 64(1): 57.     CrossRef
  • GenomeAsia100K: Singapore Builds National Science with Asian DNA
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    East Asian Science, Technology and Society: An Int.2021; 15(2): 238.     CrossRef
  • Common Data Model and Database System Development for the Korea Biobank Network
    Soo-Jeong Ko, Wona Choi, Ki-Hoon Kim, Seo-Joon Lee, Haesook Min, Seol-Whan Oh, In Young Choi
    Applied Sciences.2021; 11(24): 11825.     CrossRef
  • The emerging landscape of health research based on biobanks linked to electronic health records: Existing resources, statistical challenges, and potential opportunities
    Lauren J. Beesley, Maxwell Salvatore, Lars G. Fritsche, Anita Pandit, Arvind Rao, Chad Brummett, Cristen J. Willer, Lynda D. Lisabeth, Bhramar Mukherjee
    Statistics in Medicine.2020; 39(6): 773.     CrossRef
  • Electronic health records and polygenic risk scores for predicting disease risk
    Ruowang Li, Yong Chen, Marylyn D. Ritchie, Jason H. Moore
    Nature Reviews Genetics.2020; 21(8): 493.     CrossRef
  • Sport and exercise genomics: the FIMS 2019 consensus statement update
    Kumpei Tanisawa, Guan Wang, Jane Seto, Ioanna Verdouka, Richard Twycross-Lewis, Antonia Karanikolou, Masashi Tanaka, Mats Borjesson, Luigi Di Luigi, Michiko Dohi, Bernd Wolfarth, Jeroen Swart, James Lee John Bilzon, Victoriya Badtieva, Theodora Papadopoul
    British Journal of Sports Medicine.2020; 54(16): 969.     CrossRef
  • Cohort Profile: The Cardiovascular and Metabolic Diseases Etiology Research Center Cohort in Korea
    Jee-Seon Shim, Bo Mi Song, Jung Hyun Lee, Seung Won Lee, Ji Hye Park, Dong Phil Choi, Myung Ha Lee, Kyoung Hwa Ha, Dae Jung Kim, Sungha Park, Won-Woo Lee, Yoosik Youm, Eui-Cheol Shin, Hyeon Chang Kim
    Yonsei Medical Journal.2019; 60(8): 804.     CrossRef
  • Higher Pro-Inflammatory Dietary Score is Associated with Higher Hyperuricemia Risk: Results from the Case-Controlled Korean Genome and Epidemiology Study_Cardiovascular Disease Association Study
    Hye Sun Kim, Minji Kwon, Hyun Yi Lee, Nitin Shivappa, James R. Hébert, Cheongmin Sohn, Woori Na, Mi Kyung Kim
    Nutrients.2019; 11(8): 1803.     CrossRef
  • Association of C-Reactive Protein with Risk of Developing Type 2 Diabetes Mellitus, and Role of Obesity and Hypertension: A Large Population-Based Korean Cohort Study
    Suganya Kanmani, Minji Kwon, Moon-Kyung Shin, Mi Kyung Kim
    Scientific Reports.2019;[Epub]     CrossRef
  • Large-Scale Genomic Biobanks and Cardiovascular Disease
    Aeron M. Small, Christopher J. O’Donnell, Scott M. Damrauer
    Current Cardiology Reports.2018;[Epub]     CrossRef
  • The Rare Disease Bank of Japan: establishment, current status and future challenges
    Mayako Tada, Makoto Hirata, Mitsuho Sasaki, Ryuichi Sakate, Arihiro Kohara, Ichiro Takahashi, Yosuke Kameoka, Toru Masui, Akifumi Matsuyama
    Human Cell.2018; 31(3): 183.     CrossRef
  • Association analysis of RTEL1 variants with risk of adult gliomas in a Korean population
    Suhg Namgoong, Hyun Sub Cheong, Jeong-Hyun Kim, Lyoung Hyo Kim, Jung Yeon Seo, Seok-Gu Kang, Seon-Jin Yoon, Se Hoon Kim, Jong Hee Chang, Hyoung Doo Shin, Srinivas Mummidi
    PLOS ONE.2018; 13(11): e0207660.     CrossRef
  • Cohort Profile: The Korean Genome and Epidemiology Study (KoGES) Consortium
    Yeonjung Kim, Bok-Ghee Han
    International Journal of Epidemiology.2017; 46(2): e20.     CrossRef
  • OBIB-a novel ontology for biobanking
    Mathias Brochhausen, Jie Zheng, David Birtwell, Heather Williams, Anna Maria Masci, Helena Judge Ellis, Christian J. Stoeckert
    Journal of Biomedical Semantics.2016;[Epub]     CrossRef
  • Publicly-funded biobanks and networks in East Asia
    Sunhee Lee, Paul Eunil Jung, Yeonhee Lee
    SpringerPlus.2016;[Epub]     CrossRef
  • Biobank Regulation in South Korea
    Won Bok Lee
    Journal of Law, Medicine & Ethics.2016; 44(2): 342.     CrossRef
  • Development of an Integrated Biospecimen Database among the Regional Biobanks in Korea
    Hyun Sang Park, Hune Cho, Hwa Sun Kim
    Healthcare Informatics Research.2016; 22(2): 129.     CrossRef
  • The Qatar Biobank: background and methods
    Hanan Al Kuwari, Asma Al Thani, Ajayeb Al Marri, Abdulla Al Kaabi, Hadi Abderrahim, Nahla Afifi, Fatima Qafoud, Queenie Chan, Ioanna Tzoulaki, Paul Downey, Heather Ward, Neil Murphy, Elio Riboli, Paul Elliott
    BMC Public Health.2015;[Epub]     CrossRef
  • ELSI practices in genomic research in East Asia: implications for research collaboration and public participation
    Go Yoshizawa, Calvin Wai-Loon Ho, Wei Zhu, Chingli Hu, Yoni Syukriani, Ilhak Lee, Hannah Kim, Daniel Fu Chang Tsai, Jusaku Minari, Kazuto Kato
    Genome Medicine.2014;[Epub]     CrossRef
  • A Strategic Plan for the Second Phase (2013–2015) of the Korea Biobank Project
    Ok Park, Sang Yun Cho, So Youn Shin, Jae-Sun Park, Jun Woo Kim, Bok-Ghee Han
    Osong Public Health and Research Perspectives.2013; 4(2): 107.     CrossRef
  • Current Status, Challenges, Policies, and Bioethics of Biobanks
    Byunghak Kang, Jaesun Park, Sangyun Cho, Meehee Lee, Namhee Kim, Haesook Min, Sooyoun Lee, Ok Park, Bokghee Han
    Genomics & Informatics.2013; 11(4): 211.     CrossRef
  • Basis for Korean Genome Study
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2012; 3(3): 119.     CrossRef
Surveillance and Vector Control of Lymphatic Filariasis in the Republic of Korea
Shin Hyeong Cho, Da Won Ma, Bo Ra Koo, Hee Eun Shin, Wook Kyo Lee, Byong Suk Jeong, Chaeshin Chu, Won Ja Lee, Hyeng Il Cheun
Osong Public Health Res Perspect. 2012;3(3):145-150.   Published online June 30, 2012
DOI: https://doi.org/10.1016/j.phrp.2012.07.008
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AbstractAbstract PDF
Objectives
Until the early 2000s, lymphatic filariasis would commonly break out in the coastal areas in Korea. Through steady efforts combining investigation and treatment, filariasis was officially declared eradicated in 2008. This study surveyed the density of vector species of filariasis in past endemic areas, and inspected filariasis DNA from collected mosquitoes for protection against the reemergence of filariasis.
Methods
Between May and October 2009, mosquitoes were caught using the black night trap in past endemic coastal areas: Gyeongsangnam-do, Jeollanamdo, and Jeju-do. The collected mosquitoes were identified, and the extracted DNA from the collected vector mosquitoes was tested by polymerase chain reaction for Brugia malayi filariasis.
Results
Ochletotatus togoi, Anophel es (Hyrcanus) group and Culex pipiens were most frequently caught in Jeollanam-do (Geomun Island, Bogil Island, Heuksan Island), Jeju-do (Namone-ri, Wimi-ri). and Gyeongsangnam-do (Maemul Island). DNA of B malayi was not found in Och Togoi and An (Hyrcanus) group as main vectors of filariasis.
Conclusion
Lymphatic filariasis was not found in the vector mosquitoes collected in past endemic areas. However, considering that the proportion of vector species is quite high, there is a potential risk that filariasis could be reemerging through overseas travel or trade. Thus, there is a need to continuously monitor vector mosquitoes of lymphatic filariasis.

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    Sonia Ganassi, Antonio De Cristofaro, Dalila Di Criscio, Sonia Petrarca, Chiara Leopardi, Antonio Guarnieri, Laura Pietrangelo, Noemi Venditti, Roberto Di Marco, Giulio Petronio Petronio
    Frontiers in Microbiology.2022;[Epub]     CrossRef
  • Monitoring migrant groups as a post-validation surveillance approach to contain the potential reemergence of lymphatic filariasis in Togo
    Monique Ameyo Dorkenoo, Martin Kouame Tchankoni, Degninou Yehadji, Kossi Yakpa, Mawèké Tchalim, Efoe Sossou, Rachel Bronzan, Didier Koumavi Ekouevi
    Parasites & Vectors.2021;[Epub]     CrossRef
  • Geographical Genetic Variation and Sources of Korean Aedes albopictus (Diptera: Culicidae) Populations
    EunJung Lee, Seong-Chan Yang, Tae-Kyu Kim, Byung-Eon Noh, Hak Seon Lee, Hyunwoo Kim, Jong Yul Roh, Wook-Gyo Lee, Michel Slotman
    Journal of Medical Entomology.2020; 57(4): 1057.     CrossRef
  • A systematic review of alternative surveillance approaches for lymphatic filariasis in low prevalence settings: Implications for post-validation settings
    Nicholas Riches, Xavier Badia-Rius, Themba Mzilahowa, Louise A. Kelly-Hope, Patrick J. Lammie
    PLOS Neglected Tropical Diseases.2020; 14(5): e0008289.     CrossRef
  • An Insight into the Discovery of Potent Antifilarial Leads Against Lymphatic Filariasis
    Pone Kamdem Boniface, Ferreira Igne Elizabeth
    Current Drug Targets.2020; 21(7): 657.     CrossRef
  • Prevention and Control Strategies for Parasitic Infections in the Korea Centers for Disease Control and Prevention
    Young Yil Bahk, Eun-Hee Shin, Shin-Hyeong Cho, Jung-Won Ju, Jong-Yil Chai, Tong-Soo Kim
    The Korean Journal of Parasitology.2018; 56(5): 401.     CrossRef
  • Phylogeography of the Coastal Mosquito Aedes togoi across Climatic Zones: Testing an Anthropogenic Dispersal Hypothesis
    Teiji Sota, Peter Belton, Michelle Tseng, Hoi Sen Yong, Motoyoshi Mogi, Igor Mokrousov
    PLOS ONE.2015; 10(6): e0131230.     CrossRef
Optimal Control Strategy of Plasmodium vivax Malaria Transmission in Korea
Byul Nim Kim, Kyeongah Nah, Chaeshin Chu, Sang Uk Ryu, Yong Han Kang, Yongkuk Kim
Osong Public Health Res Perspect. 2012;3(3):128-136.   Published online June 30, 2012
DOI: https://doi.org/10.1016/j.phrp.2012.07.005
  • 3,309 View
  • 24 Download
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AbstractAbstract PDF
Objective To investigate the optimal control strategy for Plasmodium vivax malaria transmission in Korea.
Methods
A Plasmodium vivax malaria transmission model with optimal control terms using a deterministic system of differential equations is presented, and analyzed mathematically and numerically.
Results
If the cost of reducing the reproduction rate of the mosquito population is more than that of prevention measures to minimize mosquito-human contacts, the control of mosquito-human contacts needs to be taken for a longer time, comparing the other situations. More knowledge about the actual effectiveness and costs of control intervention measures would give more realistic control strategies.
Conclusion
Mathematical model and numerical simulations suggest that the use of mosquito-reduction strategies is more effective than personal protection in some cases but not always.

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  • Stochastic optimal control model for COVID-19: mask wearing and active screening/testing
    Mohcine El Baroudi, Hassan Laarabi, Samira Zouhri, Mostafa Rachik, Abdelhadi Abta
    Journal of Applied Mathematics and Computing.2024;[Epub]     CrossRef
  • Numerical Investigation of Malaria Disease Dynamics in Fuzzy Environment
    Fazal Dayan, Dumitru Baleanu, Nauman Ahmed, Jan Awrejcewicz, Muhammad Rafiq, Ali Raza, Muhammad Ozair Ahmad
    Computers, Materials & Continua.2023; 74(2): 2345.     CrossRef
  • New Trends in Fuzzy Modeling Through Numerical Techniques
    M. M. Alqarni, Muhammad Rafiq, Fazal Dayan, Jan Awrejcewicz, Nauman Ahmed, Ali Raza, Muhammad Ozair Ahmad, Witold Pawłowski, Emad E. Mahmoud
    Computers, Materials & Continua.2023; 74(3): 6371.     CrossRef
  • Optimal control analysis of hepatocytic-erythrocytic dynamics of Plasmodium falciparum malaria
    Titus Okello Orwa, Rachel Waema Mbogo, Livingstone Serwadda Luboobi
    Infectious Disease Modelling.2022; 7(1): 82.     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
  • Optimal bed net use for a dengue disease model with mosquito seasonal pattern
    Bruno Buonomo, Rossella Della Marca
    Mathematical Methods in the Applied Sciences.2018; 41(2): 573.     CrossRef
  • Optimal control in epidemiology
    Oluwaseun Sharomi, Tufail Malik
    Annals of Operations Research.2017; 251(1-2): 55.     CrossRef
  • A new analysis of infection dynamics: multi-regions discrete epidemic model with an extended optimal control approach
    Omar Zakary, Mostafa Rachik, Ilias Elmouki
    International Journal of Dynamics and Control.2017; 5(4): 1010.     CrossRef
  • On the analysis of a multi-regions discrete SIR epidemic model: an optimal control approach
    Omar Zakary, Mostafa Rachik, Ilias Elmouki
    International Journal of Dynamics and Control.2017; 5(3): 917.     CrossRef
  • Bifurcation and Sensitivity Analysis of Malaria–Schistosomiasis Co-infection Model
    E. A. Bakare, C. R. Nwozo
    International Journal of Applied and Computational.2017; 3(S1): 971.     CrossRef
  • Effect of awareness programs and travel-blocking operations in the control of HIV/AIDS outbreaks: a multi-domains SIR model
    Omar Zakary, Abdelilah Larrache, Mostafa Rachik, Ilias Elmouki
    Advances in Difference Equations.2016;[Epub]     CrossRef
  • Transmission Dynamics and Optimal Control of Malaria in Kenya
    Gabriel Otieno, Joseph K. Koske, John M. Mutiso
    Discrete Dynamics in Nature and Society.2016; 2016: 1.     CrossRef
  • Years of Epidemics (2009–2011): Pandemic Influenza and Foot-and-Mouth Disease Epidemic in Korea
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2013; 4(3): 125.     CrossRef
Can Stigma Still Distort the Spectrum of a Disease?
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2012;3(2):65-67.   Published online June 30, 2012
DOI: https://doi.org/10.1016/j.phrp.2012.04.009
  • 3,004 View
  • 27 Download
  • 1 Crossref
PDF

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  • Discrimination and Stigma
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2015; 6(3): 141.     CrossRef
Human Diseases 101: Nature Versus Nurture
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2012;3(1):1-2.   Published online December 31, 2011
DOI: https://doi.org/10.1016/j.phrp.2012.02.001
  • 2,648 View
  • 27 Download
PDF
The Name of the Game
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2011;2(Suppl 1):S1-S1.   Published online December 31, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.11.035
  • 2,610 View
  • 35 Download
PDF
Sensitivity Analysis of the Parameters of Korea’s Pandemic Influenza Preparedness Plan
Chaeshin Chu, Junehawk Lee, Dong Hoon Choi, Seung-Ki Youn, Jong-Koo Lee
Osong Public Health Res Perspect. 2011;2(3):210-215.   Published online December 31, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.11.048
  • 3,465 View
  • 21 Download
  • 10 Crossref
AbstractAbstract PDF
Objectives
Our aim was to evaluate Korea’s Pandemic Influenza Preparedness Plan.
Methods
We conducted a sensitivity analysis on the expected number of outpatients and hospital bed occupancy, with 1,000,000 parameter combinations, in a situation of pandemic influenza, using the mathematical simulation program InfluSim.
Results
Given the available resources in Korea, antiviral treatment and social distancing must be combined to reduce the number of outpatients and hospitalizations sufficiently; any single intervention is not enough. The antiviral stockpile of 4–6% is sufficient for the expected eligible number of cases to be treated. However, the eligible number assumed (30% for severe cases and 26% for extremely severe cases) is very low compared to the corresponding number in European countries, where up to 90% of the population are assumed to be eligible for antiviral treatment.
Conclusions
A combination of antiviral treatment and social distancing can mitigate a pandemic, but will only bring it under control for the most optimistic parameter combinations.

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  • Working memory capacity predicts individual differences in social-distancing compliance during the COVID-19 pandemic in the United States
    Weizhen Xie, Stephen Campbell, Weiwei Zhang
    Proceedings of the National Academy of Sciences.2020; 117(30): 17667.     CrossRef
  • Assessment of Intensive Vaccination and Antiviral Treatment in 2009 Influenza Pandemic in Korea
    Chaeshin Chu, Sunmi Lee
    Osong Public Health and Research Perspectives.2015; 6(1): 47.     CrossRef
  • Doing Mathematics with Aftermath of Pandemic Influenza 2009
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2015; 6(1): 1.     CrossRef
  • Roll the Dice
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(5): 243.     CrossRef
  • Journal Publishing: Never Ending Saga
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(1): 1.     CrossRef
  • Summing Up Again
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(4): 177.     CrossRef
  • Years of Epidemics (2009–2011): Pandemic Influenza and Foot-and-Mouth Disease Epidemic in Korea
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2013; 4(3): 125.     CrossRef
  • Public Health Crisis Preparedness and Response in Korea
    Hye-Young Lee, Mi-Na Oh, Yong-Shik Park, Chaeshin Chu, Tae-Jong Son
    Osong Public Health and Research Perspectives.2013; 4(5): 278.     CrossRef
  • Was the Mass Vaccination Effective During the Influenza Pandemic 2009–2010 in Korea?
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2013; 4(4): 177.     CrossRef
  • How to Manage a Public Health Crisis and Bioterrorism in Korea
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2013; 4(5): 223.     CrossRef
Is the Public Transportation System Safe from a Public Health Perspective?
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2011;2(3):149-150.   Published online December 31, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.11.037
  • 3,140 View
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  • Physical distancing on public transport in Mumbai, India: Policy and planning implications for unlock and post-pandemic period
    Neenu Thomas, Arnab Jana, Santanu Bandyopadhyay
    Transport Policy.2022; 116: 217.     CrossRef
Estimation of HIV Seroprevalence in Colorectal Hospitals by Questionnaire Survey in Korea, 2002–2007
Mee-Kyung Kee, Do Yeon Hwang, Jong Kyun Lee, Seung Hyun Kim, Chaeshin Chu, Jin-Hee Lee, Sung Soon Kim
Osong Public Health Res Perspect. 2011;2(2):104-108.   Published online June 30, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.08.002
  • 3,788 View
  • 19 Download
  • 4 Crossref
AbstractAbstract PDF
Objectives
The incidence of anal disease is higher among persons with human immunodeficiency virus (HIV) infection than among the general population. We surveyed the status of seroprevalence in colorectal hospitals in Korea.
Methods
The survey was conducted in colorectal hospitals in Korea from November to December 2008. The questionnaire was comprised of six topics about the status of HIV testing in colorectal hospitals. We gathered the data by website (http://hivqa.nih.go.kr/risk) or fax.
Results
Among 774 colorectal hospitals contacted, 109 (14%) hospitals participated in the survey. Among these, 48 hospitals (44%) performed HIV tests in their own hospitals and 11 (23%) took HIV testing by rapid method. The main reason for recommending an HIV test was surgical operation (54%) followed by endoscope (11%) and health checkup (9%). The annual number of HIV tests increased from 58,647 (at 21 hospitals) in 2002 to 246,709 (at 58 hospitals) in 2007. HIV seroprevalence was >3.0 per 10,000 individuals during 2002–2005, decreased to 2.2 per 10,000 individuals in 2006 and rose to 2.8 per 10,000 individuals in 2007.
Conclusions
HIV seroprevalence of colorectal hospitals was more than twice that of general hospitals in Korea. HIV surveillance systems based on colorectal hospitals for HIV/AIDS transmission prevention by early HIV diagnosis are needed.

Citations

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  • Discrimination and Stigma
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2015; 6(3): 141.     CrossRef
  • Hospital-based HIV/HSV-2 seroprevalence among male patients with anal disease in Korea: cross sectional study
    Jin-Sook Wang, Do Yeon Hwang, Hye-Kyung Yu, Sung Soon Kim, Jong Kyun Lee, Mee-Kyung Kee
    BMC Infectious Diseases.2014;[Epub]     CrossRef
  • Years of Epidemics (2009–2011): Pandemic Influenza and Foot-and-Mouth Disease Epidemic in Korea
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2013; 4(3): 125.     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
A Tale of Two Fields: Mathematical and Statistical Modeling of Infectious Diseases
Hae-Wol Cho, Chaeshin Chu
Osong Public Health Res Perspect. 2011;2(2):73-74.   Published online June 30, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.08.005
  • 3,193 View
  • 24 Download
  • 3 Crossref
PDF

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  • Modeling infectious diseases: Understanding social connectivity to control infectious diseases
    Samar Wazir, Surendra Gour, Md Tabrez Nafis, Rijwan Khan
    Informatics in Medicine Unlocked.2021; 26: 100761.     CrossRef
  • Summing Up Again
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(4): 177.     CrossRef
  • Roll the Dice
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(5): 243.     CrossRef
A Note on Obesity as Epidemic in Korea
Mun Seok Kim, Chaeshin Chu, Yongkuk Kim
Osong Public Health Res Perspect. 2011;2(2):135-140.   Published online June 30, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.08.004
  • 3,449 View
  • 18 Download
  • 9 Crossref
AbstractAbstract PDF
Objective To analyze the incidence of obesity in adults aged 19–59 years in Korea and predict its trend in the future.
Methods
We considered a two-compartmental deterministic mathematical model Susceptible-Infected-Susceptible (SIS), a system of difference equations, to predict the evolution of obesity in the population and to propose strategies to reduce its incidence.
Results
The prevention strategy on normal-weight individuals produced a greater improvement than that produced by treatment strategies.
Conclusions
Mathematical model sensitivity analysis suggests that obesity prevention strategies are more effective than obesity treatment strategies in controlling the increase of adult obesity in Korea.

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  • Quality Attributes of Fat-free Sausage Made of Chicken Breast and Liquid Egg White
    Hyun Jung Lee, Cheorun Jo, Ki Chang Nam, Kyung Haeng Lee
    The Korean Journal of Food And Nutrition.2016; 29(4): 449.     CrossRef
  • Optimal Intervention Strategies for the Spread of Obesity
    Chunyoung Oh, Masud M A
    Journal of Applied Mathematics.2015; 2015: 1.     CrossRef
  • Summing Up Again
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(4): 177.     CrossRef
  • Optimal Implementation of Intervention to Control the Self-harm Epidemic
    Byul Nim Kim, M.A. Masud, Yongkuk Kim
    Osong Public Health and Research Perspectives.2014; 5(6): 315.     CrossRef
  • A NOTE ON THE OBESITY AS AN EPIDEMIC
    Chunyoung Oh
    Honam Mathematical Journal.2014; 36(1): 131.     CrossRef
  • Journal Publishing: Never Ending Saga
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(1): 1.     CrossRef
  • Roll the Dice
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2014; 5(5): 243.     CrossRef
  • Years of Epidemics (2009–2011): Pandemic Influenza and Foot-and-Mouth Disease Epidemic in Korea
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2013; 4(3): 125.     CrossRef
  • A Tale of Two Fields: Mathematical and Statistical Modeling of Infectious Diseases
    Hae-Wol Cho, Chaeshin Chu
    Osong Public Health and Research Perspectives.2011; 2(2): 73.     CrossRef
Development of a Predictive Model for Type 2 Diabetes Mellitus Using Genetic and Clinical Data
Juyoung Lee, Bhumsuk Keam, Eun Jung Jang, Mi Sun Park, Ji Young Lee, Dan Bi Kim, Chang-Hoon Lee, Tak Kim, Bermseok Oh, Heon Jin Park, Kyu-Bum Kwack, Chaeshin Chu, Hyung-Lae Kim
Osong Public Health Res Perspect. 2011;2(2):75-82.   Published online June 30, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.07.005
  • 3,324 View
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  • 11 Crossref
AbstractAbstract PDFSupplementary Material
Objectives
Recent genetic association studies have provided convincing evidence that several novel loci and single nucleotide polymorphisms (SNPs) are associated with the risk of developing type 2 diabetes mellitus (T2DM). The aims of this study were: 1) to develop a predictive model of T2DM using genetic and clinical data; and 2) to compare misclassification rates of different models.
Methods
We selected 212 individuals with newly diagnosed T2DM and 472 controls aged in their 60s from the Korean Genome and Epidemiology Study. A total of 499 known SNPs from 87 T2DM-related genes were genotyped using germline DNA. SNPs were analyzed for significant association with T2DM using various classification algorithms including Quest (Quick, Unbiased, Efficient, Statistical tree), Support Vector Machine, C4.5, logistic regression, and K-nearest neighbor.
Results
We tested these models using the complete Korean Genome and Epidemiology Study cohort (n = 10,038) and computed the T2DM misclassification rates for each model. Average misclassification rates ranged at 28.2–52.7%. The misclassification rates for the logistic and machine-learning algorithms were lower than the statistical tree algorithms. Using 1-to-1 matched data, the misclassification rate of the statistical tree QUEST algorithm using body mass index and SNP variables was the lowest, but overall the logistic regression performed best.
Conclusions
The K-nearest neighbor method exhibited more robust results than other algorithms. For clinical and genetic data, our “multistage adjustment” model outperformed other models in yielding lower rates of misclassification. To improve the performance of these models, further studies using warranted, strategies to estimate better classifiers for the quantification of SNPs need to be developed.

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  • Population stratification in type 2 diabetes mellitus: A systematic review
    Sam Hodgson, Sukhmani Cheema, Zareena Rana, Doyinsola Olaniyan, Ellen O’Leary, Hermione Price, Hajira Dambha‐Miller
    Diabetic Medicine.2022;[Epub]     CrossRef
  • The Prediction of Diabetes
    Lalit Kumar, Prashant Johri
    International Journal of Reliable and Quality E-He.2022; 11(1): 1.     CrossRef
  • Hypertension: Constraining the Expression of ACE-II by Adopting Optimal Macronutrients Diet Predicted via Support Vector Machine
    Mohammad Farhan Khan, Gazal Kalyan, Sohom Chakrabarty, M. Mursaleen
    Nutrients.2022; 14(14): 2794.     CrossRef
  • Supervised and unsupervised algorithms for bioinformatics and data science
    Ayesha Sohail, Fatima Arif
    Progress in Biophysics and Molecular Biology.2020; 151: 14.     CrossRef
  • Medical Internet of things using machine learning algorithms for lung cancer detection
    Kanchan Pradhan, Priyanka Chawla
    Journal of Management Analytics.2020; 7(4): 591.     CrossRef
  • Perspective: Advancing Understanding of Population Nutrient–Health Relations via Metabolomics and Precision Phenotypes
    Stephanie Andraos, Melissa Wake, Richard Saffery, David Burgner, Martin Kussmann, Justin O'Sullivan
    Advances in Nutrition.2019; 10(6): 944.     CrossRef
  • Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes
    Dennis H. Murphree, Elaheh Arabmakki, Che Ngufor, Curtis B. Storlie, Rozalina G. McCoy
    Computers in Biology and Medicine.2018; 103: 109.     CrossRef
  • Machine Learning and Data Mining Methods in Diabetes Research
    Ioannis Kavakiotis, Olga Tsave, Athanasios Salifoglou, Nicos Maglaveras, Ioannis Vlahavas, Ioanna Chouvarda
    Computational and Structural Biotechnology Journal.2017; 15: 104.     CrossRef
  • Survey on clinical prediction models for diabetes prediction
    N. Jayanthi, B. Vijaya Babu, N. Sambasiva Rao
    Journal of Big Data.2017;[Epub]     CrossRef
  • Rule Extraction From Support Vector Machines Using Ensemble Learning Approach: An Application for Diagnosis of Diabetes
    Longfei Han, Senlin Luo, Jianmin Yu, Limin Pan, Songjing Chen
    IEEE Journal of Biomedical and Health Informatics.2015; 19(2): 728.     CrossRef
  • Depression among Korean Adults with Type 2 Diabetes Mellitus: Ansan-Community-Based Epidemiological Study
    Chan Young Park, So Young Kim, Jong Won Gil, Min Hee Park, Jong-Hyock Park, Yeonjung Kim
    Osong Public Health and Research Perspectives.2015; 6(4): 224.     CrossRef
Seroprevalence of Hepatitis A and E Viruses Based on the Third Korea National Health and Nutrition Survey in Korea
Haesun Yun, Hyeok-Jin Lee, Doosung Cheon, Chaeshin Chu, Kyung Won Oh, Young Taek Kim, Youngmee Jee
Osong Public Health Res Perspect. 2011;2(1):46-50.   Published online June 30, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.04.009
  • 3,625 View
  • 19 Download
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AbstractAbstract PDF
Objectives
The purpose of this study was to investigate the seroprevalence of hepatitis A virus (HAV) and hepatitis E virus (HEV) in Korea during 2005.
Methods
Study subjects were selected from across Korea using a stratified multistage probability sampling design, and HAV and HEV seroprevalence was compared on the basis of sex, age, and residency. A total of 497 rural and urban people aged 10–99 years of age (mean ± SD age = 28.87 ± 17.63 years) were selected by two-stage cluster sampling and tested serologically for anti-HAV and anti-HEV IgG using an enzyme-linked immunosorbent assay.
Results
Among this population, the overall seroprevalence of HAV was 63.80% (55.21% aged in their 20s and 95.92% in their 30s, p < 0.01) and that of HEV was 9.40% (5.21% aged in their 20s and 7.14% in their 30s, p < 0.01). Seroprevalence also varied according to area of residence. HEV prevalence in rural areas was higher than that of urban regions based on the anti-HEV antibody, odds ratio 3.22 (95% confidence interval: 1.46–7.10, p < 0.01). There were no significant differences between male and female against anti-HAV/HEV antibodies.
Conclusion
Our study suggested that the seropositive rates of HAV and HEV might be related to age and environmental conditions.

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  • A Silent Outbreak of Hepatitis E Virus (HEV) Infection or False-Positive Reaction of Anti-HEV IgM after COVID-19 Vaccination? Epidemiological Investigation of an Outbreak in a Korean Factory Complex in 2022
    Jeonghyeon Oh, Gwang Hyeon Choi, Yeonhwa Chang, Jina Kim, Kunhee Park, Hansol Yeom, Soonryu Seo, Jin Gwack, Sook-Hyang Jeong
    Gut and Liver.2024; 18(3): 531.     CrossRef
  • A Report on a Nationwide Surveillance System for Pediatric Acute Hepatitis of Unknown Etiology in Korea
    Kyung Jae Lee, Jae Sung Ko, Kie Young Park, Ki Soo Kang, Kunsong Lee, Jeana Hong, Soon Chul Kim, Yoon Lee, Ben Kang, Yu Bin Kim, Hyun Jin Kim, Byung Wook Eun, Hye-Kyung Cho, Yae-Jean Kim, Mi Jin Kim, Jin Lee, Taek-Jin Lee, Seak Hee Oh, Sowon Park, Eun Ha
    Journal of Korean Medical Science.2023;[Epub]     CrossRef
  • Factors associated with anti-hepatitis A virus immunoglobulin G seropositivity among Korean workers: a cross-sectional study
    Eunchan Mun, Yesung Lee, Byungseong Suh, Wonsul Kim, Jinsook Jeong, Hwanjin Park, Woncheol Lee, Boksoon Han, Soyoung Park, Changhwan Lee
    BMJ Open.2020; 10(6): e036727.     CrossRef
  • Seroprevalence and risk factors of hepatitis E virus infection among the Korean, Manchu, Mongol, and Han ethnic groups in Eastern and Northeastern China
    Yanan Cai, Si-Yuan Qin, Aidong Qian, Peng Xu, Ying-Tian Xu, Lin-Hong Xie, Quan Zhao, Xiao-Xuan Zhang
    Journal of Medical Virology.2017; 89(11): 1988.     CrossRef
  • Hepatitis E virus exposure in pregnant women in rural Durango, Mexico
    Cosme Alvarado-Esquivel, Luis F. Sánchez-Anguiano, Jesús Hernández-Tinoco
    Annals of Hepatology.2014; 13(5): 510.     CrossRef
  • Epidemiologic Study on Hepatitis A Virus Seroprevalence in Busan
    Kyung-Soon Cho, So-Hyun Park
    Korean Journal of Clinical Laboratory Science.2014; 46(1): 17.     CrossRef
  • A Systematic Review of Hepatitis E Virus Infection in Children
    V. P. Verghese, J. L. Robinson
    Clinical Infectious Diseases.2014; 59(5): 689.     CrossRef
  • Hepatitis E Virus (HEV) Seroprevalence in the general population of the Republic of Korea in 2007–2009: a nationwide cross-sectional study
    Youngsil Yoon, Hye Sook Jeong, Haesun Yun, Hyeokjin Lee, Yoo-Sung Hwang, Bohyun Park, Chae Jin Lee, Sangwon Lee, Ji-Yeon Hyeon
    BMC Infectious Diseases.2014;[Epub]     CrossRef
  • The Road Less Traveled
    Chaeshin Chu
    Osong Public Health and Research Perspectives.2011; 2(1): 1.     CrossRef
The Road Less Traveled
Chaeshin Chu
Osong Public Health Res Perspect. 2011;2(1):1-2.   Published online June 30, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.05.001
  • 3,093 View
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  • Assessing the impact of the environmental contamination on the transmission of Ebola virus disease (EVD)
    Berge Tsanou, Samuel Bowong, Jean Lubuma, Joseph Mbang
    Journal of Applied Mathematics and Computing.2017; 55(1-2): 205.     CrossRef
Mathematical Modeling of Vibrio vulnificus Infection in Korea and the Influence of Global Warming
Chaeshin Chu, Younghae Do, Yongkuk Kim, Yasuhisa Saito, Sun-Dong Lee, Haemo Park, Jong-Koo Lee
Osong Public Health Res Perspect. 2011;2(1):51-58.   Published online June 30, 2011
DOI: https://doi.org/10.1016/j.phrp.2011.05.002
  • 3,543 View
  • 19 Download
  • 10 Crossref
AbstractAbstract PDF
Objectives
To investigate the possible link between Vibrio vulnificus population size in seawater and water temperature.
Methods
We collected incidence and water temperature data in coastal regions of Korea and constructed a mathematical model that consisted of three classes; susceptible fish, infected fish available to humans, and infected humans.
Results
We developed a mathematical model to connect V. vulnificus incidence with water temperature using estimated bacterial population sizes and actual coastal water temperatures.
Conclusion
Increased V. vulnificus population sizes in marine environments may increase the risk of infection in people who eat at coastal restaurants in Korea. Furthermore, we estimated the near-future number of infected patients using our model, which will help to establish a public-health policy to reduce the disease burden.

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  • Years of Epidemics (2009–2011): Pandemic Influenza and Foot-and-Mouth Disease Epidemic in Korea
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  • The Road Less Traveled
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