Journal of Preventive Medicine and Public Health

COVID-19: Original Article

Sources of Infection Among Confirmed Cases of COVID-19 in Jeju Province, Korea: Moonkyong Hwang, Jong-Myon Bae; J Prev Med Public Health. 2021;54(4):245-250. Published online June 30, 2021; DOI: https://doi.org/10.3961/jpmph.21.286

3,691 View
123 Download
1 Web of Science
2 Crossref

Abstract Summary PDF Supplementary Material

Objectives
Jeju Province in Korea reported 627 coronavirus disease 2019 (COVID-19) cases between January 20, 2020, and March 31, 2021. This study analyzed the sources of infection among confirmed cases in Jeju Province, a self-governed island.
Methods
The sources of infection were broadly categorized as follows: (1) infections from overseas (confirmed patients who reported travel overseas or contact with overseas travelers); (2) infections from outside Jeju Province (confirmed patients who had visited other provinces or had contact with individuals who had traveled to other provinces in Korea); and (3) unknown sources of infection (confirmed patients who were infected following contact with an infected person whose source of infection was unknown). The chi-square test was used to analyze the differences in the distributions of related variables for each source of infection.
Results
Of the 627 confirmed cases, 38 (6.1%) were infections from overseas sources, 199 (31.7%) were from outside of Jeju Province, and 390 (62.2%) were from unknown sources. Jeju Province had no cases with an unknown source of infection during the first and second waves of the nationwide outbreak.
Conclusions
Infections from overseas sources could be blocked from spreading to local communities in Jeju Province by conducting screening at the airport, along with the preemptive suspension of visa-free entry. In addition, considering the scale of the nationwide outbreak, measures must be established to delay outbreaks from unknown sources of infection caused by sources outside Jeju Province.

Summary

Korean summary
제주도 COVID-19 확진지의 감염원은 다음의 3가지로 대분할 수 있었다. (1) 해외유입 감염원: 해외 방문력이 있거나 해외 방문력이 있는 확진자와 접촉한 적이 있는 확진자; (2) 도외유입 감염원: 국내 타시도 방문력이 있거나 타시도 확진자와 접촉한 적이 있는 확진자; (3) 감염원 미상: 감염경로를 특정할 수 없는 도내 확진자와 이들과 접촉하여 확진자가 된 경우. 이중 해외유입군에 대하여는 선제적인 무비자 중지 결정과 함께 공항만에서의 선별검사를 시행하여 해외유입에 의한 지역사회 전파 가능성을 막을 수 있음을 확인하였다. 반면, 전국의 유행 크기와 맞물러, 도외 유입군으로 인한 감염미상군 발생 시점을 최대한 미룰 수 있는 방안들을 개발할 필요가 있겠다.

Citations

Citations to this article as recorded by

The Impact of the South Korean Local Government's Public Health and Healthy Urban Planning Policies in Combating COVID-19
Fatih ULAŞAN
Kent Akademisi.2023;[Epub] CrossRef
Clinical Characteristics and Risk Factors for Severe Disease of Coronavirus Disease 2019 in a Low Case Fatality Rate Region in Korea
Misun Kim, Jeong Rae Yoo, Sang Taek Heo, Hyang Ran Lee, Hyunjoo Oh
Infection & Chemotherapy.2021; 53(4): 718. CrossRef

COVID-19: Systematic Review

Estimate of the Basic Reproduction Number for COVID-19: A Systematic Review and Meta-analysis: Yousef Alimohamadi, Maryam Taghdir, Mojtaba Sepandi; J Prev Med Public Health. 2020;53(3):151-157. Published online March 20, 2020; DOI: https://doi.org/10.3961/jpmph.20.076

24,943 View
1,251 Download
192 Crossref

Abstract PDF

Objectives
The outbreak of coronavirus disease 2019 (COVID-19) is one of the main public health challenges currently facing the world. Because of its high transmissibility, COVID-19 has already caused extensive morbidity and mortality in many countries throughout the world. An accurate estimation of the basic reproduction number (R₀) of COVID-19 would be beneficial for prevention programs. In light of discrepancies in original research on this issue, this systematic review and meta-analysis aimed to estimate the pooled R₀ for COVID-19 in the current outbreak.
Methods
International databases (including Google Scholar, Science Direct, PubMed, and Scopus) were searched to identify studies conducted regarding the R₀ of COVID-19. Articles were searched using the following keywords: “COVID-19” and “basic reproduction number” or “R₀.” The heterogeneity among studies was assessed using the I² index, the Cochran Q test, and T². A random-effects model was used to estimate R₀ in this study.
Results
The mean reported R₀ in the identified articles was 3.38±1.40, with a range of 1.90 to 6.49. According to the results of the random-effects model, the pooled R₀ for COVID-19 was estimated as 3.32 (95% confidence interval, 2.81 to 3.82). According to the results of the meta-regression analysis, the type of model used to estimate R₀ did not have a significant effect on heterogeneity among studies (p=0.81).
Conclusions
Considering the estimated R₀ for COVID-19, reducing the number of contacts within the population is a necessary step to control the epidemic. The estimated overall R₀ was higher than the World Health Organization estimate.

Summary

Citations

Citations to this article as recorded by

Optimal resource allocation model for COVID-19: a systematic review and meta-analysis
Yu-Yuan Wang, Wei-Wen Zhang, Ze-xi Lu, Jia-lin Sun, Ming-xia Jing
BMC Infectious Diseases.2024;[Epub] CrossRef
Building a Simple Model to Assess the Impact of Case Investigation and Contact Tracing for Sexually Transmitted Diseases: Lessons From COVID-19
François M. Castonguay, Harrell W. Chesson, Seonghye Jeon, Gabriel Rainisch, Leah S. Fischer, Biswha B. Adhikari, Emily B. Kahn, Bradford Greening, Thomas L. Gift, Martin I. Meltzer
AJPM Focus.2024; 3(1): 100147. CrossRef
SARS-CoV-2 incidence monitoring and statistical estimation of the basic and time-varying reproduction number at the early onset of the pandemic in 45 sub-Saharan African countries
Michael Safo Oduro, Seth Arhin-Donkor, Louis Asiedu, Damazo T. Kadengye, Samuel Iddi
BMC Public Health.2024;[Epub] CrossRef
Looking under the lamp-post: quantifying the performance of contact tracing in the United States during the SARS-CoV-2 pandemic
Henry Bayly, Madison Stoddard, Debra Van Egeren, Eleanor J Murray, Julia Raifman, Arijit Chakravarty, Laura F White
BMC Public Health.2024;[Epub] CrossRef
Dynamic analysis of generalized epidemic models with latent period, quarantine, governmental intervention and Ornstein–Uhlenbeck process
Tan Su, Xinhong Zhang, Daqing Jiang
Nonlinear Dynamics.2024; 112(9): 7749. CrossRef
A Dynamic Reaction-restore-type Transmission-rate Model for COVID-19
Fernando Córdova-Lepe, Juan Pablo Gutiérrez-Jara
WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINE.2024; 21: 118. CrossRef
Optimal non-pharmaceutical interventions considering limited healthcare system capacity and economic costs in the Republic of Korea
Yuna Lim, Youngsuk Ko, Victoria May P. Mendoza, Renier Mendoza, Jongmin Lee, Eunok Jung
Mathematical Modelling of Natural Phenomena.2024; 19: 6. CrossRef
GAME-THEORETICAL MODEL OF COVID-19 VACCINATION IN THE ENDEMIC EQUILIBRIUM
RENEE MARIA ARGANA MARQUEZ, MARIA SEANNA CABERO MINAS, JORDAN VANCE TAITANO SANTOS, KANGSAN YOON, VINCE NICOLAS S. CAMPO, HYUNJU OH, JAN RYCHTÁŘ, DEWEY TAYLOR
Journal of Biological Systems.2024; 32(02): 349. CrossRef
Estimating the COVID-19 prevalence from wastewater
Jan Mohring, Neele Leithäuser, Jarosław Wlazło, Marvin Schulte, Maximilian Pilz, Johanna Münch, Karl-Heinz Küfer
Scientific Reports.2024;[Epub] CrossRef
A tree-based explainable AI model for early detection of Covid-19 using physiological data
Manar Abu Talib, Yaman Afadar, Qassim Nasir, Ali Bou Nassif, Haytham Hijazi, Ahmad Hasasneh
BMC Medical Informatics and Decision Making.2024;[Epub] CrossRef
Airline safety: Still getting better?
Arnold Barnett, Jan Reig Torra
Journal of Air Transport Management.2024; 119: 102641. CrossRef
An SIR‐based Bayesian framework for COVID‐19 infection estimation
Haoyu Wu, David A. Stephens, Erica E. M. Moodie
Canadian Journal of Statistics.2024;[Epub] CrossRef
Data-driven mathematical modeling approaches for COVID-19: A survey
Jacques Demongeot, Pierre Magal
Physics of Life Reviews.2024; 50: 166. CrossRef
Global stability analysis of an extended SUC epidemic mathematical model
Mengxin Chen, Soobin Kwak, Seokjun Ham, Youngjin Hwang, Junseok Kim
Zeitschrift für Naturforschung A.2024;[Epub] CrossRef
Monitoring the Reproduction Number and Stringency Index of Covid-19 Pandemic in Nigeria
Edike, N., Agbedeyi, O. D.
African Journal of Mathematics and Statistics Studies.2024; 7(4): 1. CrossRef
Modeling SARS‐CoV‐2 True Infections in Catalonia through a Digital Twin
Pau Fonseca i Casas, Joan Garcia i Subirana, Victor Garcia i Carrasco
Advanced Theory and Simulations.2023;[Epub] CrossRef
Risk Mitigation Strategy against SARS-CoV-2 Infection for Healthcare Provider at Harapan Bersama General Hospital, Singkawang, Indonesia
Rizki Rahim, Andreasta Meliala
Hospital Topics.2023; 101(4): 381. CrossRef
Reducing the basic reproduction number of COVID-19: a model simulation focused on QALYs, hospitalisation, productivity costs and optimal (soft) lockdown
Jose Robles-Zurita
The European Journal of Health Economics.2023; 24(4): 647. CrossRef
Waco COVID Survey: A Community-Based SARS-CoV-2 Serological Surveillance Study in Central Texas
Michael P. Muehlenbein, Jeffrey Gassen, Tomasz J. Nowak, Alexandria D. Henderson, Sally P. Weaver, Erich J. Baker
Journal of Community Health.2023; 48(1): 104. CrossRef
COVID-19 epidemic and public health interventions in Shanghai, China: Statistical analysis of transmission, correlation and conversion
Dali Yi, Xicheng Chen, Haojia Wang, Qiuyue Song, Ling Zhang, Pengpeng Li, Wei Ye, Jia Chen, Fang Li, Dong Yi, Yazhou Wu
Frontiers in Public Health.2023;[Epub] CrossRef
Bounding pandemic spread by heat spread
Teddy Lazebnik, Uri Itai
Journal of Engineering Mathematics.2023;[Epub] CrossRef
Macroeconomic consequences of the COVID-19 pandemic
Terrie Walmsley, Adam Rose, Richard John, Dan Wei, Jakub P. Hlávka, Juan Machado, Katie Byrd
Economic Modelling.2023; 120: 106147. CrossRef
Monkeypox 2022
Suraj Kapoor, Ashvin Varadharajan
Journal of Public Health and Primary Care.2023; 4(1): 8. CrossRef
Forty‐seven year trend of measles in Iran: An interrupted time series analysis
Yousef Alimohamadi, Mojtaba Sepandi
Health Science Reports.2023;[Epub] CrossRef
A mathematical model for the spread of Omicron virus based on grey prediction algorithm
Haotian Lin, Jianze Lin, Kewei You
Highlights in Science, Engineering and Technology.2023; 36: 1386. CrossRef
Household transmission dynamics of COVID-19 among residents of Delhi, India: a prospective case-ascertained study
Farzana Islam, Yasir Alvi, Mohammad Ahmad, Faheem Ahmed, Anisur Rahman, Farishta Hannah D. Singh, Ayan Kumar Das, Mridu Dudeja, Ekta Gupta, Rashmi Agarwalla, Iqbal Alam, Sushovan Roy
IJID Regions.2023; 7: 22. CrossRef
Study of optimal vaccination strategies for early COVID-19 pandemic using an age-structured mathematical model: A case study of the USA
Giulia Luebben, Gilberto González-Parra, Bishop Cervantes
Mathematical Biosciences and Engineering.2023; 20(6): 10828. CrossRef
A Stochastic Mobility-Driven spatially explicit SEIQRD COVID-19 model with VOCs, seasonality, and vaccines
Tijs W. Alleman, Michiel Rollier, Jenna Vergeynst, Jan M. Baetens
Applied Mathematical Modelling.2023; 123: 507. CrossRef
Using advanced analysis together with fractional order derivative to investigate a smoking tobacco cancer model
Ismail Shah, Eiman, Hussam Alrabaiah, Burhanettin Ozdemir, Ateeq ur Rehman Irshad
Results in Physics.2023; 51: 106700. CrossRef
Trajectories of COVID-19: A longitudinal analysis of many nations and subnational regions
David Burg, Jesse H. Ausubel, Rajnesh Lal
PLOS ONE.2023; 18(6): e0281224. CrossRef
Influence spreading model for partial breakthrough effects on complex networks
Into Almiala, Henrik Aalto, Vesa Kuikka
Physica A: Statistical Mechanics and its Applications.2023; 630: 129244. CrossRef
A Brighton Collaboration standardized template with key considerations for a benefit/risk assessment for the Novavax COVID-19 Vaccine (NVX-CoV2373), a recombinant spike protein vaccine with Matrix-M adjuvant to prevent disease caused by SARS-CoV-2 viruses
Bethanie Wilkinson, Kinjal S. Patel, Katherine Smith, Robert Walker, Chengbin Wang, Ann M. Greene, Gale Smith, Emily R. Smith, Marc Gurwith, Robert T. Chen
Vaccine.2023; 41(45): 6762. CrossRef
Modelling influenza and SARS-CoV-2 interaction: Analysis for Catalonia region
Pau Fonseca i Casas, Victor Garcia i Carrasco, Joan Garcia i Subirana
Journal of Algorithms & Computational Technology.2023;[Epub] CrossRef
Measuring the efficacy of a vaccine during an epidemic
Antonio Scala, Pierpaolo Cavallo, Tiago Pereira
PLOS ONE.2023; 18(9): e0290652. CrossRef
Fast bilateral weighted least square for the detail enhancement of COVID-19 chest X-rays
Wenyan Bian, Yang Yang
DIGITAL HEALTH.2023;[Epub] CrossRef
Structural Econometric Estimation of the Basic Reproduction Number for COVID-19 Across U.S. States and Selected Countries
Ida Johnsson, M. Hashem Pesaran, Cynthia Fan Yang
SSRN Electronic Journal.2023;[Epub] CrossRef
SARS-CoV-2: An Update on the Biological Interplay with the Human Host
Giuseppe Lippi, Fabian Sanchis-Gomar, Camilla Mattiuzzi, Brandon M. Henry
COVID.2023; 3(10): 1586. CrossRef
A data-driven semi-parametric model of SARS-CoV-2 transmission in the United States
John M. Drake, Andreas Handel, Éric Marty, Eamon B. O’Dea, Tierney O’Sullivan, Giovanni Righi, Andrew T. Tredennick, Gerardo Chowell
PLOS Computational Biology.2023; 19(11): e1011610. CrossRef
Reaction–Diffusion Equations in Mathematical Models Arising in Epidemiology
Vasyl’ Davydovych, Vasyl’ Dutka, Roman Cherniha
Symmetry.2023; 15(11): 2025. CrossRef
Multivariate Forecasting Model for COVID-19 Spread Based on Possible Scenarios in Ecuador
Juan Guamán, Karen Portilla, Paúl Arias-Muñoz, Gabriel Jácome, Santiago Cabrera, Luis Álvarez, Bolívar Batallas, Hernán Cadena, Juan Carlos García
Mathematics.2023; 11(23): 4721. CrossRef
Direct indicators of social distancing effectiveness in COVID-19 outbreak stages: a correlational analysis of case contacts and population mobility in Korea
Sojin Choi, Chanhee Kim, Kun-Hee Park, Jong-Hun Kim
Epidemiology and Health.2023; 45: e2023065. CrossRef
Screening multi‐dimensional heterogeneous populations for infectious diseases under scarce testing resources, with application to COVID‐19
Hussein El Hajj, Douglas R. Bish, Ebru K. Bish, Hrayer Aprahamian
Naval Research Logistics (NRL).2022; 69(1): 3. CrossRef
COVID-19 Global Humanitarian Response Plan: An optimal distribution model for high-priority countries
Ibrahim M. Hezam
ISA Transactions.2022; 124: 1. CrossRef
Health and Public Health Implications of COVID‐19 in Asian Countries
Atsushi Miyawaki, Yusuke Tsugawa
Asian Economic Policy Review.2022; 17(1): 18. CrossRef
Implications for clinical dental practice during the coronavirus disease pandemic: A scoping review
Kazumichi Yonenaga, Shunsuke Itai, Kazuto Hoshi
Journal of Prosthodontic Research.2022; 66(1): 6. CrossRef
Objective Evaluation of Olfactory and Taste Dysfunction Among COVID-19 Patients: A Cross Sectional Study from Tribal India
Izhar Khan, Vikas Gupta, Sanjay Kumar Shukla
Indian Journal of Otolaryngology and Head & Neck Surgery.2022; 74(S2): 3193. CrossRef
A strict mask policy for hospital staff effectively prevents nosocomial influenza infections and mortality: monocentric data from five consecutive influenza seasons
A. Ambrosch, D. Luber, F. Klawonn, M. Kabesch
Journal of Hospital Infection.2022; 121: 82. CrossRef
Effectiveness of social distancing interventions in containing COVID-19 incidence: International evidence using Kalman filter
Navendu Prakash, Bhavya Srivastava, Shveta Singh, Seema Sharma, Sonali Jain
Economics & Human Biology.2022; 44: 101091. CrossRef
Validación preclínica de un respirador de turbina para la ventilación invasiva: el respirador ACUTE-19
J.M. Alonso-Iñigo, G. Mazzinari, M. Casañ-Pallardó, J.I. Redondo-García, J. Viscasillas-Monteagudo, A. Gutierrez-Bautista, J. Ramirez-Faz, P. Alonso-Pérez, S. Díaz-Lobato, A.S. Neto, O. Diaz-Cambronero, P. Argente-Navarro, M. Gama de Abreu, P. Pelosi, M.J
Revista Española de Anestesiología y Reanimación.2022; 69(9): 544. CrossRef
An algorithm for the direct estimation of the parameters of the SIR epidemic model from the I(t) dynamics
François G. Schmitt
The European Physical Journal Plus.2022;[Epub] CrossRef
The efficacy of deep learning based LSTM model in forecasting the outbreak of contagious diseases
Nurul Absar, Nazim Uddin, Mayeen Uddin Khandaker, Habib Ullah
Infectious Disease Modelling.2022; 7(1): 170. CrossRef
Quantifying transmissibility of SARS-CoV-2 and impact of intervention within long-term healthcare facilities
Jessica E. Stockdale, Sean C. Anderson, Andrew M. Edwards, Sarafa A. Iyaniwura, Nicola Mulberry, Michael C. Otterstatter, Naveed Z. Janjua, Daniel Coombs, Caroline Colijn, Michael A. Irvine
Royal Society Open Science.2022;[Epub] CrossRef
Cost-effective proactive testing strategies during COVID-19 mass vaccination: A modelling study
Zhanwei Du, Lin Wang, Yuan Bai, Xutong Wang, Abhishek Pandey, Meagan C. Fitzpatrick, Matteo Chinazzi, Ana Pastore y Piontti, Nathaniel Hupert, Michael Lachmann, Alessandro Vespignani, Alison P. Galvani, Benjamin J. Cowling, Lauren Ancel Meyers
The Lancet Regional Health - Americas.2022; 8: 100182. CrossRef
Epidemiological Characteristics and Transmissibility for SARS-CoV-2 of Population Level and Cluster Level in a Chinese City
Shanshan Yu, Shufeng Cui, Jia Rui, Zeyu Zhao, Bin Deng, Chan Liu, Kangguo Li, Yao Wang, Zimei Yang, Qun Li, Tianmu Chen, Shan Wang
Frontiers in Public Health.2022;[Epub] CrossRef
Real-time pandemic surveillance using hospital admissions and mobility data
Spencer J. Fox, Michael Lachmann, Mauricio Tec, Remy Pasco, Spencer Woody, Zhanwei Du, Xutong Wang, Tanvi A. Ingle, Emily Javan, Maytal Dahan, Kelly Gaither, Mark E. Escott, Stephen I. Adler, S. Claiborne Johnston, James G. Scott, Lauren Ancel Meyers
Proceedings of the National Academy of Sciences.2022;[Epub] CrossRef
Anxiety Linked to COVID-19: A Systematic Review Comparing Anxiety Rates in Different Populations
Hafsah Saeed, Ardalan Eslami, Najah T. Nassif, Ann M. Simpson, Sara Lal
International Journal of Environmental Research and Public Health.2022; 19(4): 2189. CrossRef
A simple electrical-circuit analogous phenomenological COVID-19 model valid for all observed pandemic phases
J. C. Nolasco, J. T. García, A. Castro-Chacón, A. Castro-Carranza, J. Gutowski
AIP Advances.2022;[Epub] CrossRef
SARS-CoV-2 outbreak in a Canadian suburban tertiary hospital necessitating full facility closure: a descriptive observational study
Jamil N. Kanji, Y.L. Elaine Chan, Lesia R. Boychuk, Curtiss Boyington, Sebora Turay, Melissa Kobelsky, Carolyn Doroshuk, Philana Choo, Susan Jacka, Erin Roberts, Karen Leighton, Stephanie W. Smith, Christopher Sikora, Robert Black
CMAJ Open.2022; 10(1): E137. CrossRef
Local Surveillance of the COVID-19 Outbreak
Caifen Liu, Lingfeng Xu, Yuan Bai, Xiaoke Xu, Eric H. Y. Lau, Benjamin J. Cowling, Zhanwei Du
Frontiers in Physics.2022;[Epub] CrossRef
A review on COVID-19 transmission, epidemiological features, prevention and vaccination
Yuqin Zhang, Gonghua Wu, Shirui Chen, Xu Ju, Wumitijiang Yimaer, Wangjian Zhang, Shao Lin, Yuantao Hao, Jing Gu, Jinghua Li
Medical Review.2022; 2(1): 23. CrossRef
Cost-effectiveness analysis on COVID-19 surveillance strategy of large-scale sports competition
Xuechun Wang, Yiru Cai, Bo Zhang, Xiangyu Zhang, Lianhao Wang, Xiangyu Yan, Mingchen Zhao, Yuan Zhang, Zhongwei Jia
Infectious Diseases of Poverty.2022;[Epub] CrossRef
Social and Policy Determinants of COVID-19 Infection Across 23 Countries: An Ecological Study
Kyungsik Kim, Young-Do Jeung, Jeoungbin Choi, Sue K. Park
Journal of Preventive Medicine and Public Health.2022; 55(2): 144. CrossRef
Perspectives on factors influencing transmission of COVID-19 in Zambia: a qualitative study of health workers and community members
Cephas Sialubanje, Doreen C Sitali, Nawa Mukumbuta, Libonda Liyali, Phyllis Ingutu Sumbwa, Harvey Kakoma Kamboyi, Mary Ng'andu, Fastone Matthew Goma
BMJ Open.2022; 12(4): e057589. CrossRef
Factors Associated With Mortality Among the COVID-19 Patients Treated at Gulu Regional Referral Hospital: A Retrospective Study
Steven Baguma, Christopher Okot, Nelson Onira Alema, Paska Apiyo, Paska Layet, Denis Acullu, Johnson Nyeko Oloya, Denis Ochula, Pamela Atim, Patrick Odong Olwedo, Smart Godfrey Okot, Freddy Wathum Drinkwater Oyat, Janet Oola, Eric Nzirakaindi Ikoona, Judi
Frontiers in Public Health.2022;[Epub] CrossRef
Optimal intervention strategies to mitigate the COVID-19 pandemic effects
Andreas Kasis, Stelios Timotheou, Nima Monshizadeh, Marios Polycarpou
Scientific Reports.2022;[Epub] CrossRef
COVID‐19 infection in an infant with cystic fibrosis: A case report and possible therapeutic effect of hypertonic saline
Seyed Javad Seyedi, Hossein Sadeghi, Hamid‐Reza Kianifar, Abdolkarim Hamedi, Amin Saeidinia
Clinical Case Reports.2022;[Epub] CrossRef
Data analysis and prediction of the COVID-19 outbreak in the first and second waves for top 5 affected countries in the world
Ashabul Hoque, Abdul Malek, K. M. Rukhsad Asif Zaman
Nonlinear Dynamics.2022; 109(1): 77. CrossRef
The influence of gender on COVID-19 infections and mortality in Germany: Insights from age- and gender-specific modeling of contact rates, infections, and deaths in the early phase of the pandemic
Achim Doerre, Gabriele Doblhammer, Siew Ann Cheong
PLOS ONE.2022; 17(5): e0268119. CrossRef
The impact of vaccination against the new coronavirus infection on the morbidity of university students
Sergey A. Sayganov, Anna V. Lubimova, Alexandr V. Meltser, Zakhar V. Lopatin, Olga Yu. Kuznetsova, Olga V. Kovaleva
Russian Family Doctor.2022; 26(1): 21. CrossRef
COVID-19: Clinical features, case fatality, and the effect of symptoms on mortality in hospitalized cases in Iran
Yousef Alimohamadi, Mojtaba Sepandi, Roya Rashti, Homeira Sedighinezhad, Sima Afrashteh
Journal of Taibah University Medical Sciences.2022; 17(5): 725. CrossRef
The Basic Reproduction Number and Delayed Action of T Cells for Patients Infected with SARS-CoV-2
Yingdong Yin, Yupeng Xi, Cheng Xu, Qiwen Sun
Mathematics.2022; 10(12): 2017. CrossRef
Understanding Dynamics of Pandemic Models to Support Predictions of COVID-19 Transmission: Parameter Sensitivity Analysis of SIR-Type Models
Chunfeng Ma, Xin Li, Zebin Zhao, Feng Liu, Kun Zhang, Adan Wu, Xiaowei Nie
IEEE Journal of Biomedical and Health Informatics.2022; 26(6): 2458. CrossRef
Estimating the course of the COVID-19 pandemic in Germany via spline-based hierarchical modelling of death counts
Tobias Wistuba, Andreas Mayr, Christian Staerk
Scientific Reports.2022;[Epub] CrossRef
Adding a reaction-restoration type transmission rate dynamic-law to the basic SEIR COVID-19 model
Fernando Córdova-Lepe, Katia Vogt-Geisse, Fabio A Sanchez
PLOS ONE.2022; 17(6): e0269843. CrossRef
SARS-CoV-2 Risk Quantification Model and Validation Based on Large-Scale Dutch Test Events
Bas Kolen, Laurens Znidarsic, Andreas Voss, Simon Donders, Iris Kamphorst, Maarten van Rijn, Dimitri Bonthuis, Merit Clocquet, Maarten Schram, Rutger Scharloo, Tim Boersma, Tim Stobernack, Pieter van Gelder
International Journal of Environmental Research and Public Health.2022; 19(12): 7238. CrossRef
Testing and isolation to prevent overloaded healthcare facilities and reduce death rates in the SARS-CoV-2 pandemic in Italy
Arnab Bandyopadhyay, Marta Schips, Tanmay Mitra, Sahamoddin Khailaie, Sebastian C. Binder, Michael Meyer-Hermann
Communications Medicine.2022;[Epub] CrossRef
Autoregressive count data modeling on mobility patterns to predict cases of COVID-19 infection
Jing Zhao, Mengjie Han, Zhenwu Wang, Benting Wan
Stochastic Environmental Research and Risk Assessment.2022; 36(12): 4185. CrossRef
Epidemiological investigation of the COVID-19 outbreak in Vellore district in South India using Geographic Information Surveillance (GIS)
Malathi Murugesan, Padmanaban Venkatesan, Senthil Kumar, Premkumar Thangavelu, Winsley Rose, Jacob John, Marx Castro, T. Manivannan, Venkata Raghava Mohan, Priscilla Rupali
International Journal of Infectious Diseases.2022; 122: 669. CrossRef
Burden of hospital-acquired SARS-CoV-2 infections in Germany: occurrence and outcomes of different variants
M. Bonsignore, S. Hohenstein, C. Kodde, J. Leiner, K. Schwegmann, A. Bollmann, R. Möller, R. Kuhlen, I. Nachtigall
Journal of Hospital Infection.2022; 129: 82. CrossRef
Lessons from a pandemic
Yves Eggli, Valentin Rousson, Reuben Kiggundu
PLOS Global Public Health.2022; 2(7): e0000404. CrossRef
Update on COVID-19 and Effectiveness of a Vaccination Campaign in a Global Context
Ioannis Alexandros Charitos, Andrea Ballini, Roberto Lovero, Francesca Castellaneta, Marica Colella, Salvatore Scacco, Stefania Cantore, Roberto Arrigoni, Filiberto Mastrangelo, Mario Dioguardi
International Journal of Environmental Research and Public Health.2022; 19(17): 10712. CrossRef
Overview of the Role of Spatial Factors in Indoor SARS-CoV-2 Transmission: A Space-Based Framework for Assessing the Multi-Route Infection Risk
Qi Zhen, Anxiao Zhang, Qiong Huang, Jing Li, Yiming Du, Qi Zhang
International Journal of Environmental Research and Public Health.2022; 19(17): 11007. CrossRef
Different forms of superspreading lead to different outcomes: Heterogeneity in infectiousness and contact behavior relevant for the case of SARS-CoV-2
Elise J. Kuylen, Andrea Torneri, Lander Willem, Pieter J. K. Libin, Steven Abrams, Pietro Coletti, Nicolas Franco, Frederik Verelst, Philippe Beutels, Jori Liesenborgs, Niel Hens, Miles P. Davenport
PLOS Computational Biology.2022; 18(8): e1009980. CrossRef
Adjusting non-pharmaceutical interventions based on hospital bed capacity using a multi-operator differential evolution
Victoria May P. Mendoza, Renier Mendoza, Jongmin Lee, Eunok Jung
AIMS Mathematics.2022; 7(11): 19922. CrossRef
Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2
Jana S Huisman, Jérémie Scire, Daniel C Angst, Jinzhou Li, Richard A Neher, Marloes H Maathuis, Sebastian Bonhoeffer, Tanja Stadler
eLife.2022;[Epub] CrossRef
Behavioral responses to risk promote vaccinating high‐contact individuals first
Hazhir Rahmandad
System Dynamics Review.2022; 38(3): 246. CrossRef
Pre-clinical validation of a turbine-based ventilator for invasive ventilation—The ACUTE-19 ventilator
J.M. Alonso-Iñigo, G. Mazzinari, M. Casañ-Pallardó, J.I. Redondo-García, J. Viscasillas-Monteagudo, A. Gutierrez-Bautista, J. Ramirez-Faz, P. Alonso-Pérez, S. Díaz-Lobato, A.S. Neto, O. Diaz-Cambronero, P. Argente-Navarro, M. Gama de Abreu, P. Pelosi, M.J
Revista Española de Anestesiología y Reanimación (English Edition).2022; 69(9): 544. CrossRef
Why COVID-19 modelling of progression and prevention fails to translate to the real-world
Carl J. Heneghan, Tom Jefferson
Advances in Biological Regulation.2022; 86: 100914. CrossRef
The impact of demographic factors on the courseof COVID-19 infection
Karolina Goroszkiewicz, Grażyna Lisowska, Natalia Zięba, Grażyna Stryjewska-Makuch, Kinga Szopińska, Maciej Misiołek
Polski Przegląd Otorynolaryngologiczny.2022; 11(3): 1. CrossRef
COVID-19 cluster size and transmission rates in schools from crowdsourced case reports
Paul Tupper, Shraddha Pai, Caroline Colijn
eLife.2022;[Epub] CrossRef
No magic bullet: Limiting in-school transmission in the face of variable SARS-CoV-2 viral loads
Debra Van Egeren, Madison Stoddard, Abir Malakar, Debayan Ghosh, Antu Acharya, Sk Mainuddin, Biswajit Majumdar, Deborah Luo, Ryan P. Nolan, Diane Joseph-McCarthy, Laura F. White, Natasha S. Hochberg, Saikat Basu, Arijit Chakravarty
Frontiers in Public Health.2022;[Epub] CrossRef
Risk Factors for In-Hospital Mortality among Patients with Coronavirus-19 in Isfahan City, Iran
Roya Riahi, Marziye Ghasemi, Zahra Montazeri Shatouri, Mojgan Gharipour, Mahboobeh Maghami, Hamid Melali, Ramin Sami, Aminreza Tabatabaei, Sayed Mohsen Hosseini
Advanced Biomedical Research.2022; 11(1): 121. CrossRef
Comparison of the Basic Reproduction Numbers for COVID-19 through Four Waves of the Pandemic in Vietnam
Ngan Thi Mai, Giang Thi Huong Tran, Anh Huu Dang, Phuong Thi Bich Cao, Trung Thanh Nguyen, Huong Thi Lan Pham, Tra Thi Thu Vu, Hieu Van Dong, Le Thi My Huynh
International Journal of Translational Medicine.2022; 3(1): 1. CrossRef
Estimating the Basic Reproduction Number for the Second Wave of Covid-19 Pandemic in Nigeria
Ashiribo Senapon Wusu, Olusola Aanu Olabanjo, Manuel Mazzara
International Journal of Pure and Applied Mathematics Research.2022; 2(2): 1. CrossRef
COVID-19 and India: what next?
Ramesh Behl, Manit Mishra
Information Discovery and Delivery.2021; 49(3): 250. CrossRef
What the reproductive number R0 can and cannot tell us about COVID-19 dynamics
Clara L. Shaw, David A. Kennedy
Theoretical Population Biology.2021; 137: 2. CrossRef
Ruling out COVID-19 by chest CT at emergency admission when prevalence is low: the prospective, observational SCOUT study
Ulf Teichgräber, Amer Malouhi, Maja Ingwersen, Rotraud Neumann, Marina Reljic, Stefanie Deinhardt-Emmer, Bettina Löffler, Wilhelm Behringer, Jan-Christoph Lewejohann, Andreas Stallmach, Philipp Reuken
Respiratory Research.2021;[Epub] CrossRef
The challenges of containing SARS-CoV-2 via test-trace-and-isolate
Sebastian Contreras, Jonas Dehning, Matthias Loidolt, Johannes Zierenberg, F. Paul Spitzner, Jorge H. Urrea-Quintero, Sebastian B. Mohr, Michael Wilczek, Michael Wibral, Viola Priesemann
Nature Communications.2021;[Epub] CrossRef
A model for COVID-19 with isolation, quarantine and testing as control measures
M.S. Aronna, R. Guglielmi, L.M. Moschen
Epidemics.2021; 34: 100437. CrossRef
Understanding Viral Infection Mechanisms and Patient Symptoms for the Development of COVID-19 Therapeutics
Hyung Muk Choi, Soo Youn Moon, Hyung In Yang, Kyoung Soo Kim
International Journal of Molecular Sciences.2021; 22(4): 1737. CrossRef
Current understanding of the surface contamination and contact transmission of SARS-CoV-2 in healthcare settings
Hosoon Choi, Piyali Chatterjee, John D. Coppin, Julie A. Martel, Munok Hwang, Chetan Jinadatha, Virender K. Sharma
Environmental Chemistry Letters.2021; 19(3): 1935. CrossRef
Impact of climatic, demographic and disease control factors on the transmission dynamics of COVID-19 in large cities worldwide
Soeren Metelmann, Karan Pattni, Liam Brierley, Lisa Cavalerie, Cyril Caminade, Marcus S.C. Blagrove, Joanne Turner, Kieran J. Sharkey, Matthew Baylis
One Health.2021; 12: 100221. CrossRef
Mathematical modelling to inform New Zealand’s COVID-19 response
Shaun Hendy, Nicholas Steyn, Alex James, Michael J. Plank, Kate Hannah, Rachelle N. Binny, Audrey Lustig
Journal of the Royal Society of New Zealand.2021; 51(sup1): S86. CrossRef
Meta-analysis on Serial Intervals and Reproductive Rates for SARS-CoV-2
Mohammad Hussein, Eman Toraih, Rami Elshazli, Manal Fawzy, August Houghton, Danielle Tatum, Mary Killackey, Emad Kandil, Juan Duchesne
Annals of Surgery.2021; 273(3): 416. CrossRef
Genomic epidemiology of a densely sampled COVID-19 outbreak in China
Lily Geidelberg, Olivia Boyd, David Jorgensen, Igor Siveroni, Fabrícia F Nascimento, Robert Johnson, Manon Ragonnet-Cronin, Han Fu, Haowei Wang, Xiaoyue Xi, Wei Chen, Dehui Liu, Yingying Chen, Mengmeng Tian, Wei Tan, Junjie Zai, Wanying Sun, Jiandong Li,
Virus Evolution.2021;[Epub] CrossRef
Estimating the basic reproduction number for COVID-19 in Western Europe
Isabella Locatelli, Bastien Trächsel, Valentin Rousson, Yury E. Khudyakov
PLOS ONE.2021; 16(3): e0248731. CrossRef
The S(E)IR(D) Models of the COVID-19 Epidemic in Korea
Hee-Young Shin
SSRN Electronic Journal .2021;[Epub] CrossRef
Simulation of COVID-19 Propagation Scenarios in the Madrid Metropolitan Area
David E. Singh, Maria-Cristina Marinescu, Miguel Guzmán-Merino, Christian Durán, Concepción Delgado-Sanz, Diana Gomez-Barroso, Jesus Carretero
Frontiers in Public Health.2021;[Epub] CrossRef
The SEIR(D) Model of the COVID-19 Epidemic in Korea
Hee-Young Shin
SSRN Electronic Journal .2021;[Epub] CrossRef
Countries with delayed COVID-19 introduction – characteristics, drivers, gaps, and opportunities
Zheng Li, Cynthia Jones, Girum S. Ejigu, Nisha George, Amanda L. Geller, Gregory C. Chang, Alys Adamski, Ledor S. Igboh, Rebecca D. Merrill, Philip Ricks, Sara A. Mirza, Michael Lynch
Globalization and Health.2021;[Epub] CrossRef
Containment efficiency and control strategies for the corona pandemic costs
Claudius Gros, Roser Valenti, Lukas Schneider, Kilian Valenti, Daniel Gros
Scientific Reports.2021;[Epub] CrossRef
A comparison of COVID-19 secondary attack rate in household and close contacts compared to current risk stratification guidelines of the Kerala government
Balram Rathish, Arun Wilson, Sonya Joy
Tropical Doctor.2021; 51(3): 461. CrossRef
Evaluating the effectiveness of measures to control the novel coronavirus disease 2019 in Jilin Province, China
Qinglong Zhao, Yao Wang, Meng Yang, Meina Li, Zeyu Zhao, Xinrong Lu, Bo Shen, Bo Luan, Yifei Zhao, Bonan Cao, Laishun Yao, Benhua Zhao, Yanhua Su, Tianmu Chen
BMC Infectious Diseases.2021;[Epub] CrossRef
Impact of Meteorological Conditions on the Dynamics of the COVID-19 Pandemic in Poland
Bogdan Bochenek, Mateusz Jankowski, Marta Gruszczynska, Grzegorz Nykiel, Maciej Gruszczynski, Adam Jaczewski, Michal Ziemianski, Robert Pyrc, Mariusz Figurski, Jarosław Pinkas
International Journal of Environmental Research and Public Health.2021; 18(8): 3951. CrossRef
Mathematical modeling of spatio-temporal population dynamics and application to epidemic spreading
Stefanie Winkelmann, Johannes Zonker, Christof Schütte, Nataša Djurdjevac Conrad
Mathematical Biosciences.2021; 336: 108619. CrossRef
Novel coronavirus disease 2019 (COVID-19) pandemic: From transmission to control with an interdisciplinary vision
Uttpal Anand, Carlo Cabreros, Joyabrata Mal, Florencio Ballesteros, Mika Sillanpää, Vijay Tripathi, Elza Bontempi
Environmental Research.2021; 197: 111126. CrossRef
Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis
Stephen Wai Hang Kwok, Sai Kumar Vadde, Guanjin Wang
Journal of Medical Internet Research.2021; 23(5): e26953. CrossRef
Modelling the impact of household size distribution on the transmission dynamics of COVID-19
Pengyu Liu, Lisa McQuarrie, Yexuan Song, Caroline Colijn
Journal of The Royal Society Interface.2021;[Epub] CrossRef
Previsione della propagazione di SARS-CoV-2 nello Stato di Amapá, Amazzonia, Brasile, mediante modellazione matematica
Neylan Leal Dias, Edcarlos Vasconcelos da Silva, Marcelo Amanajas Pires, Daniel Chaves, Katsumi Letra Sanada, Amanda Alves Fecury, Cláudio Alberto Gellis de Mattos Dias, Euzébio de Oliveira, Carla Viana Dendasck, Simone Delphim Leal
Revista Científica Multidisciplinar Núcleo do Conhecimento.2021; : 73. CrossRef
Estimation of Transmission of COVID-19 in Simulated Nursing Homes With Frequent Testing and Immunity-Based Staffing
Inga Holmdahl, Rebecca Kahn, James A. Hay, Caroline O. Buckee, Michael J. Mina
JAMA Network Open.2021; 4(5): e2110071. CrossRef
Estimation of novel coronavirus (COVID‐19) reproduction number and case fatality rate: A systematic review and meta‐analysis
Tanvir Ahammed, Aniqua Anjum, Mohammad Meshbahur Rahman, Najmul Haider, Richard Kock, Md Jamal Uddin
Health Science Reports.2021;[Epub] CrossRef
Modelling the Impact of Robotics on Infectious Spread Among Healthcare Workers
Raul Vicente, Youssef Mohamed, Victor M. Eguíluz, Emal Zemmar, Patrick Bayer, Joseph S. Neimat, Juha Hernesniemi, Bradley J. Nelson, Ajmal Zemmar
Frontiers in Robotics and AI.2021;[Epub] CrossRef
Who complies with coronavirus disease 2019 precautions and who does not?
Róbert Urbán, Orsolya Király, Zsolt Demetrovics
Current Opinion in Psychiatry.2021; 34(4): 363. CrossRef
Gamma irradiation-mediated inactivation of enveloped viruses with conservation of genome integrity: Potential application for SARS-CoV-2 inactivated vaccine development
Fouad A. Abolaban, Fathi M. Djouider
Open Life Sciences.2021; 16(1): 558. CrossRef
COVID-19 herd immunity in the absence of a vaccine: an irresponsible approach
Jade Khalife, Derrick VanGennep
Epidemiology and Health.2021; 43: e2021012. CrossRef
Machine Learning for Analyzing Non-Countermeasure Factors Affecting Early Spread of COVID-19
Vito Janko, Gašper Slapničar, Erik Dovgan, Nina Reščič, Tine Kolenik, Martin Gjoreski, Maj Smerkol, Matjaž Gams, Mitja Luštrek
International Journal of Environmental Research and Public Health.2021; 18(13): 6750. CrossRef
Impact of reduction of susceptibility to SARS-CoV-2 on epidemic dynamics in four early-seeded metropolitan regions
Thomas J. Barrett, Karen C. Patterson, Timothy M. James, Peter Krüger
Scientific Reports.2021;[Epub] CrossRef
Asian-Origin Approved COVID-19 Vaccines and Current Status of COVID-19 Vaccination Program in Asia: A Critical Analysis
Chiranjib Chakraborty, Ashish Ranjan Sharma, Manojit Bhattacharya, Govindasamy Agoramoorthy, Sang-Soo Lee
Vaccines.2021; 9(6): 600. CrossRef
Phylodynamics reveals the role of human travel and contact tracing in controlling the first wave of COVID-19 in four island nations
Jordan Douglas, Fábio K Mendes, Remco Bouckaert, Dong Xie, Cinthy L Jiménez-Silva, Christiaan Swanepoel, Joep de Ligt, Xiaoyun Ren, Matt Storey, James Hadfield, Colin R Simpson, Jemma L Geoghegan, Alexei J Drummond, David Welch
Virus Evolution.2021;[Epub] CrossRef
The current reproduction number of COVID-19 in Saudi Arabia: is the disease controlled?
Theeb Ayedh Alkahtani, Abdullah Alakeel, Reem Abdullah Alakeel, Faten Abdulrahman Khorshid, Hisham Hamoud Alshammari, Abdullah M. Alguwaihes, Mohammad Almohideb, Eman Merghani Ali, May Bin-Jumah, Mohamed M. Abdel-Daim, Anwar Ali Jammah
Environmental Science and Pollution Research.2021; 28(33): 44812. CrossRef
Beyond the new normal: Assessing the feasibility of vaccine-based suppression of SARS-CoV-2
Madison Stoddard, Sharanya Sarkar, Lin Yuan, Ryan P. Nolan, Douglas E. White, Laura F. White, Natasha S. Hochberg, Arijit Chakravarty, Muhammad Adrish
PLOS ONE.2021; 16(7): e0254734. CrossRef
A multi-stage SEIR(D) model of the COVID-19 epidemic in Korea
Hee-Young Shin
Annals of Medicine.2021; 53(1): 1160. CrossRef
A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics
Alexandru Topîrceanu, Radu-Emil Precup
Scientific Reports.2021;[Epub] CrossRef
THE EFFECT OF COVID 19 FEAR ON QUALITY OF LIFE IN HEMODIALYSIS PATIENTS: A CORRELATION STUDY IN TURKEY
Ayşe Gül PARLAK, Zümrüt AKGÜN ŞAHİN
Samsun Sağlık Bilimleri Dergisi.2021; 6(2): 367. CrossRef
Is compulsory home quarantine less effective than centralized quarantine in controlling the COVID-19 outbreak? Evidence from Hong Kong
Pengyu Zhu, Xinying Tan
Sustainable Cities and Society.2021; 74: 103222. CrossRef
Rates of SARS-CoV-2 transmission and vaccination impact the fate of vaccine-resistant strains
Simon A. Rella, Yuliya A. Kulikova, Emmanouil T. Dermitzakis, Fyodor A. Kondrashov
Scientific Reports.2021;[Epub] CrossRef
Non-adherence to preventive behaviours during the COVID-19 epidemic: findings from a community study
Róbert Urbán, Borbála Paksi, Ádám Miklósi, John B. Saunders, Zsolt Demetrovics
BMC Public Health.2021;[Epub] CrossRef
Prognostic value of neutrophil‐to‐lymphocyte ratio in COVID‐19 patients: A systematic review and meta‐analysis
Juan R. Ulloque‐Badaracco, W. Ivan Salas‐Tello, Ali Al‐kassab‐Córdova, Esteban A. Alarcón‐Braga, Vicente A. Benites‐Zapata, Jorge L. Maguiña, Adrian V. Hernandez
International Journal of Clinical Practice.2021;[Epub] CrossRef
Determinants of COVID-19 vaccine acceptance and hesitancy: a cross-sectional study in Saudi Arabia
Amar Ibrahim Omer Yahia, Abdullah Mohammed Alshahrani, Wael Gabir H. Alsulmi, Mohammed Mesfer M. Alqarni, Tamim Khalid Abdullah Abdulrahim, Waleed Faya H Heba, Turki Ayidh A. Alqarni, Khalid Ali Z Alharthi, Abdullah Ali A. Buhran
Human Vaccines & Immunotherapeutics.2021; 17(11): 4015. CrossRef
Modeling coupling dynamics between the transmission, intervention of COVID-19 and economic development
Zhaowang Zhang, Lingming Kong, Hualiang Lin, Guanghu Zhu
Results in Physics.2021; 28: 104632. CrossRef
Vaccines and variants: Modelling insights into emerging issues in COVID-19 epidemiology
Jamie M. Caldwell, Xuan Le, Lorin McIntosh, Michael T. Meehan, Samson Ogunlade, Romain Ragonnet, Genevieve K. O'Neill, James M. Trauer, Emma S. McBryde
Paediatric Respiratory Reviews.2021; 39: 32. CrossRef
Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 to Close Contacts, China, January–February 2020
Yu Li, Jianhua Liu, Zhongcheng Yang, Jianxing Yu, Chengzhong Xu, Aiqin Zhu, Hao Zhang, Xiaokun Yang, Xin Zhao, Minrui Ren, Zhili Li, Jinzhao Cui, Hongting Zhao, Xiang Ren, Chengxi Sun, Ying Cheng, Qiulan Chen, Zhaorui Chang, Junling Sun, Lance E. Rodewald
Emerging Infectious Diseases.2021; 27(9): 2288. CrossRef
Living with COVID-19: The road ahead
Wycliffe Enli Wei, Wei Keat Tan, Alex Richard Cook, Li Yang Hsu, Yik Ying Teo, Vernon Jian Ming Lee
Annals of the Academy of Medicine, Singapore.2021; 50(8): 619. CrossRef
“Mass gathering events and COVID-19 transmission in Borriana (Spain): A retrospective cohort study”
Salvador Domènech-Montoliu, Maria Rosario Pac-Sa, Paula Vidal-Utrillas, Marta Latorre-Poveda, Alba Del Rio-González, Sara Ferrando-Rubert, Gema Ferrer-Abad, Manuel Sánchez-Urbano, Laura Aparisi-Esteve, Gema Badenes-Marques, Belén Cervera-Ferrer, Ursula Cl
PLOS ONE.2021; 16(8): e0256747. CrossRef
Effective vaccine allocation strategies, balancing economy with infection control against COVID-19 in Japan
Satoshi Sunohara, Toshiaki Asakura, Takashi Kimura, Shun Ozawa, Satoshi Oshima, Daigo Yamauchi, Akiko Tamakoshi, Martial L. Ndeffo Mbah
PLOS ONE.2021; 16(9): e0257107. CrossRef
THE “FLU SEASONS” AND THE MISSING DATA: A MATCHED-PAIR ANALYSIS FOR THE PANDEMIC SEASON 2019_2020
Vincent Kay Lo Ip
International Journal of Research -GRANTHAALAYAH.2021; 9(8): 268. CrossRef
A simple model for control of COVID-19 infections on an urban campus
Robert A. Brown
Proceedings of the National Academy of Sciences.2021;[Epub] CrossRef
Clinical Characteristics and CT Imaging Features of COVID-19 on Admission: A Retrospective Study
Changchun Liu, Jianping Cai, Mengmeng Zhang, Huizhen Li, Chunyan Liu, Jian Dong, Jinghui Dong
Current Medical Imaging Formerly Current Medical Imaging Reviews.2021; 17(11): 1324. CrossRef
Network models to evaluate vaccine strategies towards herd immunity in COVID-19
Josephine N.A. Tetteh, Van Kinh Nguyen, Esteban A. Hernandez-Vargas
Journal of Theoretical Biology.2021; 531: 110894. CrossRef
Examining SARS-CoV-2 Interventions in Residential Colleges Using an Empirical Network
Hali L. Hambridge, Rebecca Kahn, Jukka-Pekka Onnela
International Journal of Infectious Diseases.2021; 113: 325. CrossRef
Immunization using a heterogeneous geo-spatial population model: A qualitative perspective on COVID-19 vaccination strategies
Alexandru Topîrceanu
Procedia Computer Science.2021; 192: 2095. CrossRef
Epidemiological characterization of COVID-19 – Pune, 2020-2021
SumitD Bhardwaj, ManoharLal Choudhary, YogeshK Gurav, Priya Abraham, VarshaA Potdar
Indian Journal of Medical Research.2021; 153(5): 542. CrossRef
Synergistic interventions to control COVID-19: Mass testing and isolation mitigates reliance on distancing
Emily Howerton, Matthew J. Ferrari, Ottar N. Bjørnstad, Tiffany L. Bogich, Rebecca K. Borchering, Chris P. Jewell, James D. Nichols, William J. M. Probert, Michael C. Runge, Michael J. Tildesley, Cécile Viboud, Katriona Shea, Jennifer A. Flegg
PLOS Computational Biology.2021; 17(10): e1009518. CrossRef
Low case numbers enable long-term stable pandemic control without lockdowns
Sebastian Contreras, Jonas Dehning, Sebastian B. Mohr, Simon Bauer, F. Paul Spitzner, Viola Priesemann
Science Advances.2021;[Epub] CrossRef
Rapid relaxation of pandemic restrictions after vaccine rollout favors growth of SARS-CoV-2 variants: A model-based analysis
Debra Van Egeren, Madison Stoddard, Alexander Novokhodko, Michael S. Rogers, Diane Joseph-McCarthy, Bruce Zetter, Arijit Chakravarty, Martial L Ndeffo Mbah
PLOS ONE.2021; 16(11): e0258997. CrossRef
Stability, Bifurcation, and a Pair of Conserved Quantities in a Simple Epidemic System with Reinfection for the Spread of Diseases Caused by Coronaviruses
Jorge Fernando Camacho, Cruz Vargas-De-León, Hassan A. El Morshedy
Discrete Dynamics in Nature and Society.2021; 2021: 1. CrossRef
Knowledge, Awareness, and Practices (KAP) towards COVID-19 among the marine fishers of Maharashtra State of India: An online cross-sectional Analysis
Suhas Wasave, Sangita Wasave, Ketankumar Chaudhari, Prakash Shingare, Bharat Yadav, Sandesh Patil, Bhalchandra Naik, Amitava Mukherjee
PLOS ONE.2021; 16(12): e0261055. CrossRef
Estimating the impact of influenza on the epidemiological dynamics of SARS-CoV-2
Matthieu Domenech de Cellès, Jean-Sebastien Casalegno, Bruno Lina, Lulla Opatowski
PeerJ.2021; 9: e12566. CrossRef
Ruling Out COVID-19 by Chest CT at Emergency Admission to Prevent In-Hospital Spread When Prevalence is Low – The Prospective, Observational SCOUT Study
Ulf Karl-Martin Teichgräber, Amer Malouhi, Maja Ingwersen, Rotraud Neumann, Marina Reljic, Stefanie Deinhardt-Emmer, Bettina Löffler, Wilhelm Behringer, Jan-Christoph Lewejohann, Andreas Stallmach, Philipp A. Reuken
SSRN Electronic Journal .2021;[Epub] CrossRef
Analysis and forecast of COVID-19 in India, USA and Italy - an application of ARIMA Model
Elbin Siby, Maria Joseph, Aneena Thankachan, K. K. Jose
Biometrics & Biostatistics International Journal.2021; 10(2): 75. CrossRef
Olfactory and Taste Dysfunction and Its Correlation with Viral Load on Reverse Transcription-Polymerase Chain Reaction among COVID-19 Patients
Izhar Khan, Vikas Gupta, Abhishek Gaur, Sanjay Kumar Shukla, Shewtank Goel
Archives of Medicine and Health Sciences.2021; 9(2): 196. CrossRef
Spatiotemporal analysis, hotspot mapping, and clustering of confirmed cases of COVID-19 in the initial phase of the pandemic in Qom province, Iran
Abolfazl Mohammadbeigi, Shahram Arsang-Jang, Ehsan Sharifipour, Alireza Koohpaei, Mostafa Vahedian, Narges Mohammadsalehi, Masoud Jafaresmaeili, Moharam Karami, Siamak Mohebi
Journal of Acute Disease.2021; 10(4): 150. CrossRef
Epidemiological characteristics of coronavirus disease 2019 (COVID-19) patients in IRAN: A single center study
Mohamad Nikpouraghdam, Alireza Jalali Farahani, GholamHossein Alishiri, Soleyman Heydari, Mehdi Ebrahimnia, Hossein Samadinia, Mojtaba Sepandi, Nematollah Jonaidi Jafari, Morteza Izadi, Ali Qazvini, Ruhollah Dorostkar, Mahdi Tat, Alireza Shahriary, Gholam
Journal of Clinical Virology.2020; 127: 104378. CrossRef
Preventing major outbreaks of COVID-19 in jails
Justin T Okano, Sally Blower
The Lancet.2020; 395(10236): 1542. CrossRef
Predição da propagação do SARS-CoV-2 no Estado do Amapá, Amazônia, Brasil, por modelagem matemática
Neylan Leal Dias, Edcarlos Vasconcelos da Silva, Marcelo Amanajas Pires, Daniel Chaves, Katsumi Letra Sanada, Amanda Alves Fecury, Cláudio Alberto Gellis de Mattos Dias, Euzébio de Oliveira, Carla Viana Dendasck, Simone Delphim Leal
Revista Científica Multidisciplinar Núcleo do Conhecimento.2020; : 73. CrossRef
Prediction of the propagation of SARS-CoV-2 in Amapá State, Amazon Region, Brazil, by mathematical modeling
Neylan Leal Dias, Edcarlos Vasconcelos da Silva, Marcelo Amanajas Pires, Daniel Chaves, Katsumi Letra Sanada, Amanda Alves Fecury, Cláudio Alberto Gellis de Mattos Dias, Euzébio de Oliveira, Carla Viana Dendasck, Simone Delphim Leal
Revista Científica Multidisciplinar Núcleo do Conhecimento.2020; : 73. CrossRef
Price of Delay in Covid-19 Lockdowns: Delays Spike Total Cases, Natural Experiments Reveal
Gerard J. Tellis, Ashish Sood, Nitish Sood
SSRN Electronic Journal .2020;[Epub] CrossRef
Managing the R0 of COVID‐19: mathematics fights back
J. J. Pandit
Anaesthesia.2020; 75(12): 1643. CrossRef
Estimating COVID-19 outbreak risk through air travel
Yair Daon, Robin N Thompson, Uri Obolski
Journal of Travel Medicine.2020;[Epub] CrossRef
Decrease in Ambient Fine Particulate Matter during COVID-19 Crisis and Corresponding Health Benefits in Seoul, Korea
Changwoo Han, Yun-Chul Hong
International Journal of Environmental Research and Public Health.2020; 17(15): 5279. CrossRef
“Tomorrow Never Dies”: Recent Advances in Diagnosis, Treatment, and Prevention Modalities against Coronavirus (COVID-19) amid Controversies
Partha Laskar, Murali M. Yallapu, Subhash C. Chauhan
Diseases.2020; 8(3): 30. CrossRef
Years of Life Lost Attributable to COVID-19 in High-incidence Countries
In-Hwan Oh, Minsu Ock, Su Yeon Jang, Dun-Sol Go, Young-Eun Kim, Yoon-Sun Jung, Ki Beom Kim, Hyesook Park, Min-Woo Jo, Seok-Jun Yoon
Journal of Korean Medical Science.2020;[Epub] CrossRef
Corona and the climate: a comparison of two emergencies
Kira Vinke, Sabine Gabrysch, Emanuela Paoletti, Johan Rockström, Hans Joachim Schellnhuber
Global Sustainability.2020;[Epub] CrossRef
Imputation method to reduce undetected severe acute respiratory infection cases during the coronavirus disease outbreak in Brazil
Silvano Barbosa de Oliveira, Fabiana Ganem, Wildo Navegantes de Araújo, Jordi Casabona, Mauro Niskier Sanchez, Julio Croda
Revista da Sociedade Brasileira de Medicina Tropical.2020;[Epub] CrossRef
Transmission Dynamics of the COVID-19 Epidemic at the District Level in India: Prospective Observational Study
Suman Saurabh, Mahendra Kumar Verma, Vaishali Gautam, Nitesh Kumar, Akhil Dhanesh Goel, Manoj Kumar Gupta, Pankaj Bhardwaj, Sanjeev Misra
JMIR Public Health and Surveillance.2020; 6(4): e22678. CrossRef
Clinical Characteristics of Critically Ill Patients Infected with COVID-19 in Rasoul Akram Hospital in Iran: A Single Center Study
Poupak Rahimzadeh, Saied Amniati, Reza Farahmandrad, Seyed Hamid Reza Faiz, Setareh Hedayati Emami, Azadeh Habibi
Anesthesiology and Pain Medicine.2020;[Epub] CrossRef
Repeated Testing in SARS-CoV-2 Infection
Giuseppe Lippi, Fabian Sanchis-Gomar, Brandon M. Henry
Mayo Clinic Proceedings.2020; 95(10): 2283. CrossRef
COVID-19 Transmission: Bangladesh Perspective
Masud M A, Md Hamidul Islam, Khondaker A. Mamun, Byul Nim Kim, Sangil Kim
Mathematics.2020; 8(10): 1793. CrossRef
Early management of critically ill patients with COVID‐19
Damián Gutiérrez‐Zarate, Karina Rosas‐Sánchez, Juan Carlos Flores‐Carrillo, Salvador Medrano‐Ahumada, Michel Martínez‐Franco
Journal of the American College of Emergency Physicians Open.2020; 1(6): 1418. CrossRef
Transmissibility of coronavirus disease 2019 in Chinese cities with different dynamics of imported cases
Ka Chun Chong, Wei Cheng, Shi Zhao, Feng Ling, Kirran N. Mohammad, Maggie Wang, Benny CY Zee, Lai Wei, Xi Xiong, Hengyan Liu, Jingxuan Wang, Enfu Chen
PeerJ.2020; 8: e10350. CrossRef
Modelling Excess Mortality in Covid-19-Like Epidemics
Zdzislaw Burda
Entropy.2020; 22(11): 1236. CrossRef
Reproductive number of coronavirus: A systematic review and meta-analysis based on global level evidence
Md. Arif Billah, Md. Mamun Miah, Md. Nuruzzaman Khan, Maria Elena Flacco
PLOS ONE.2020; 15(11): e0242128. CrossRef
Compositional cyber-physical epidemiology of COVID-19
Jin Woo Ro, Nathan Allen, Weiwei Ai, Debi Prasad, Partha S. Roop
Scientific Reports.2020;[Epub] CrossRef
Responsible Communication of Romanian Companies for Ensuring Public Health in a COVID-19 Pandemic Context
Camelia-Daniela Hategan, Ruxandra-Ioana Curea-Pitorac, Vasile-Petru Hategan
International Journal of Environmental Research and Public Health.2020; 17(22): 8526. CrossRef
COVID-19 lockdown induces disease-mitigating structural changes in mobility networks
Frank Schlosser, Benjamin F. Maier, Olivia Jack, David Hinrichs, Adrian Zachariae, Dirk Brockmann
Proceedings of the National Academy of Sciences.2020; 117(52): 32883. CrossRef
Attitudes Toward a Potential SARS-CoV-2 Vaccine
Kimberly A. Fisher, Sarah J. Bloomstone, Jeremy Walder, Sybil Crawford, Hassan Fouayzi, Kathleen M. Mazor
Annals of Internal Medicine.2020; 173(12): 964. CrossRef
Analysis and Forecast of COVID-19 in India, the US and Italy - An Application of Arima Model
Elbin Siby, Maria Joseph, Noel George, Richu Rajesh, Aneena Thankachan
SSRN Electronic Journal .2020;[Epub] CrossRef
Knowledge, Perceived Beliefs, and Preventive Behaviors Related to COVID-19 Among Chinese Older Adults: Cross-Sectional Web-Based Survey
Ying Chen, Rui Zhou, Boyan Chen, Hao Chen, Ying Li, Zhi Chen, Haihong Zhu, Hongmei Wang
Journal of Medical Internet Research.2020; 22(12): e23729. CrossRef
Vorhersage der Ausbreitung von SARS-CoV-2 im brasilianischen Bundesstaat Amapá, Amazonas, durch mathematische Modellierung
Neylan Leal Dias, Edcarlos Vasconcelos da Silva, Marcelo Amanajas Pires, Daniel Chaves, Katsumi Letra Sanada, Amanda Alves Fecury, Cláudio Alberto Gellis de Mattos Dias, Euzébio de Oliveira, Carla Viana Dendasck, Simone Delphim Leal
Revista Científica Multidisciplinar Núcleo do Conhecimento.2020; : 73. CrossRef
Predicción de la propagación del SARS-CoV-2 en el estado de Amapá, Amazonas, Brasil, por modelado matemático
Neylan Leal Dias, Edcarlos Vasconcelos da Silva, Marcelo Amanajas Pires, Daniel Chaves, Katsumi Letra Sanada, Amanda Alves Fecury, Cláudio Alberto Gellis de Mattos Dias, Euzébio de Oliveira, Carla Viana Dendasck, Simone Delphim Leal
Revista Científica Multidisciplinar Núcleo do Conhecimento.2020; : 73. CrossRef
Prédiction de la propagation du SRAS-CoV-2 dans l’État d’Amapá, Amazônia, Brésil, par modélisation mathématique
Neylan Leal Dias, Edcarlos Vasconcelos da Silva, Marcelo Amanajas Pires, Daniel Chaves, Katsumi Letra Sanada, Amanda Alves Fecury, Cláudio Alberto Gellis de Mattos Dias, Euzébio de Oliveira, Carla Viana Dendasck, Simone Delphim Leal
Revista Científica Multidisciplinar Núcleo do Conhecimento.2020; : 73. CrossRef
Прогнозирование распространения SARS-CoV-2 в штате Amapá, Амазонка, Бразилия, с помощью математического моделирования
Neylan Leal Dias, Edcarlos Vasconcelos da Silva, Marcelo Amanajas Pires, Daniel Chaves, Katsumi Letra Sanada, Amanda Alves Fecury, Cláudio Alberto Gellis de Mattos Dias, Euzébio de Oliveira, Carla Viana Dendasck, Simone Delphim Leal
Revista Científica Multidisciplinar Núcleo do Conhecimento.2020; : 73. CrossRef

Brief Report

Community-acquired Legionnaires’ Disease in a Newly Constructed Apartment Building: Sukhyun Ryu, Kyungho Yang, Byung Chul Chun; J Prev Med Public Health. 2017;50(4):274-277. Published online June 28, 2017; DOI: https://doi.org/10.3961/jpmph.17.066

6,057 View
179 Download
5 Crossref

Abstract PDF

Objectives
Legionnaires’ disease (LD) is a severe type of pneumonia caused by inhalation of aerosols contaminated with Legionella. On September 22, 2016, a single case of LD was reported from a newly built apartment building in Gyeonggi province. This article describes an epidemiologic investigation of LD and identification of the possible source of infection. Methods: To identify the source of LD, we interviewed the patient’s husband using a questionnaire based on the Legionella management guidelines from the Korea Centers for Disease Control and Prevention. Water samples from the site were collected and analyzed. An epidemiological investigation of the residents and visitors in the apartment building was conducted for 14 days before the index patient’s symptoms first appeared to 14 days after the implementation of environmental control measures. Results: Legionella pneumophila serogroup 1 was isolated from the heated-water samples from the patient’s residence and the basement of the apartment complex. Thirty-two suspected cases were reported from the apartment building during the surveillance period, yet all were confirmed negative based on urinary antigen tests. Conclusions: The likely source of infection was the building’s potable water, particularly heated water. Further study of effective monitoring systems in heated potable water should be considered.

Summary

Citations

Citations to this article as recorded by

The Presence of Opportunistic Premise Plumbing Pathogens in Residential Buildings: A Literature Review
Claire Hayward, Kirstin E. Ross, Melissa H. Brown, Richard Bentham, Harriet Whiley
Water.2022; 14(7): 1129. CrossRef
Surveillance of Legionella pneumophila: Detection in Public Swimming Pool Environment
Darija Vukić Lušić, Vanda Piškur, Arijana Cenov, Dijana Tomić Linšak, Dalibor Broznić, Marin Glad, Željko Linšak
Microorganisms.2022; 10(12): 2429. CrossRef
Turnover Intention among Field Epidemiologists in South Korea
Sukhyun Ryu
International Journal of Environmental Research and Public Health.2020; 17(3): 949. CrossRef
Comparison of Legionella K-set® and BinaxNOW® Legionella for diagnosing Legionnaires’ disease on concentrated urine samples
Aubin Souche, Ghislaine Descours, Anne-Gaëlle Ranc, Gérard Lina, Sophie Jarraud, Laetitia Beraud
European Journal of Clinical Microbiology & Infectious Diseases.2020; 39(9): 1641. CrossRef
Presence of Legionella spp. in Hot Water Networks of Different Italian Residential Buildings: A Three-Year Survey
Michele Totaro, Paola Valentini, Anna Costa, Lorenzo Frendo, Alessia Cappello, Beatrice Casini, Mario Miccoli, Gaetano Privitera, Angelo Baggiani
International Journal of Environmental Research and Public Health.2017; 14(11): 1296. CrossRef

Special Article

Structural Factors of the Middle East Respiratory Syndrome Coronavirus Outbreak as a Public Health Crisis in Korea and Future Response Strategies: Dong-Hyun Kim; J Prev Med Public Health. 2015;48(6):265-270. Published online November 30, 2015; DOI: https://doi.org/10.3961/jpmph.15.066

38,199 View
212 Download
21 Crossref

Abstract PDF

The recent Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak has originated from a failure in the national quarantine system in the Republic of Korea as most basic role of protecting the safety and lives of its citizens. Furthermore, a number of the Korean healthcare system’s weaknesses seem to have been completely exposed. The MERS-CoV outbreak can be considered a typical public health crisis in that the public was not only greatly terrorized by the actual fear of the disease, but also experienced a great impact to their daily lives, all in a short period of time. Preparedness for and an appropriate response to a public health crisis require comprehensive systematic public healthcare measures to address risks comprehensively with an all-hazards approach. Consequently, discussion regarding establishment of post-MERS-CoV improvement measures must focus on the total reform of the national quarantine system and strengthening of the public health infrastructure. In addition, the Korea Centers for Disease Control and Prevention must implement specific strategies of action including taking on the role of “control tower” in a public health emergency, training of Field Epidemic Intelligence Service officers, establishment of collaborative governance between central and local governments for infection prevention and control, strengthening the roles and capabilities of community-based public hospitals, and development of nationwide crisis communication methods.

Summary

Citations

Citations to this article as recorded by

Factors associated with clinicians’ response ability for public health emergencies: a cross-sectional study
Jia Yu Zhang, Yan Wang, Bao Jun Wan, Lai Hua Qi, Tao Shu, Zhan Chun Feng
Journal of Public Health.2024;[Epub] CrossRef
Competency in responding to infectious disease outbreaks among nurses in primary healthcare institutions: a quantitative, cross-sectional multicentre study
Wei Zhu, Jizhen Zhang, Liyao Yang, Jiping Li, Hongxia Guo
Frontiers in Public Health.2024;[Epub] CrossRef
Changes in Anxiety, Depression, and Stress in 1 Week and 1 Month Later After the Wuhan Shutdown Against the COVID-19 Epidemic
Qi Chen, Mengying Li, Yueqing Wang, Ling Zhang, Xiaodong Tan
Disaster Medicine and Public Health Preparedness.2022; 16(4): 1423. CrossRef
Uncertain future of privacy protection under the Korean public health emergency preparedness governance amid the COVID-19 pandemic
Younsik Kim
Cogent Social Sciences.2022;[Epub] CrossRef
Prevalence and influencing factors of psychological distress among nurses in sichuan, china during the COVID-19 outbreak: A cross-sectional study
Caixia Xie, Jia Zhang, Jia Ping, Xinyu Li, Yu Lv, Limei Liao
Frontiers in Psychiatry.2022;[Epub] CrossRef
The impact of the Middle East Respiratory Syndrome coronavirus on inbound tourism in South Korea toward sustainable tourism
Yunseon Choe, Junhui Wang, HakJun Song
Journal of Sustainable Tourism.2021; 29(7): 1117. CrossRef
Nurses’ core emergency competencies for COVID‐19 in China: A cross‐sectional study
Hongdan Li, Shuju Dong, Li He, Rui Wang, Shiyan Long, Fengming He, Huairong Tang, Ling Feng
International Nursing Review.2021; 68(4): 524. CrossRef
Middle East Respiratory Syndrome (MERS) Virus—Pathophysiological Axis and the Current Treatment Strategies
Abdullah M Alnuqaydan, Abdulmajeed G Almutary, Arulmalar Sukamaran, Brian Tay Wei Yang, Xiao Ting Lee, Wei Xuan Lim, Yee Min Ng, Rania Ibrahim, Thiviya Darmarajan, Satheeshkumar Nanjappan, Jestin Chellian, Mayuren Candasamy, Thiagarajan Madheswaran, Ankur
AAPS PharmSciTech.2021;[Epub] CrossRef
Nursing Care for People with Chronic Diseases and Pulmonary Infection by Coronavirus: An Integrative Review
Jina Mariont Velasco Arias, Maria de Fátima Mantovani, Robson Giovani Paes, Vanessa Bertoglio Comassetto Antunes de Oliveira, Vanêssa Piccinin Paz, Adelmo Fernandes do Espírito Santo-Neto
Aquichan.2021; 21(2): 1. CrossRef
Analysis of the Healthcare MERS-CoV Outbreak in King Abdulaziz Medical Center, Riyadh, Saudi Arabia, June–August 2015 Using a SEIR Ward Transmission Model
Tamer Oraby, Michael G. Tyshenko, Hanan H. Balkhy, Yasar Tasnif, Adriana Quiroz-Gaspar, Zeinab Mohamed, Ayesha Araya, Susie Elsaadany, Eman Al-Mazroa, Mohammed A. Alhelail, Yaseen M. Arabi, Mustafa Al-Zoughool
International Journal of Environmental Research and Public Health.2020; 17(8): 2936. CrossRef
Learning From the Past: Distributed Cognition and Crisis Management Capabilities for Tackling COVID-19
Seulki Lee, Jungwon Yeo, Chongmin Na
The American Review of Public Administration.2020; 50(6-7): 729. CrossRef
Study on Integrated Workflow Development and Presentation of Fangcang Shelter Hospitals in COVID-19 Pandemic
Na Li, Jie Pan
Journal of Emergency Management and Disaster Communications.2020; 01(01): 11. CrossRef
Assessing global preparedness for the next pandemic: development and application of an Epidemic Preparedness Index
Ben Oppenheim, Mark Gallivan, Nita K Madhav, Naor Brown, Volodymyr Serhiyenko, Nathan D Wolfe, Patrick Ayscue
BMJ Global Health.2019; 4(1): e001157. CrossRef
Trends in Infectious Disease Mortality, South Korea, 1983–2015
Young June Choe, Seung-Ah Choe, Sung-Il Cho
Emerging Infectious Diseases.2018; 24(2): 320. CrossRef
Effects of operational decisions on the diffusion of epidemic disease: A system dynamics modeling of the MERS-CoV outbreak in South Korea
Nina Shin, Taewoo Kwag, Sangwook Park, Yon Hui Kim
Journal of Theoretical Biology.2017; 421: 39. CrossRef
Strategic risk communication for infectious disease outbreaks: the evolving landscape of publics and media
Hye-Jin Paek
Journal of the Korean Medical Association.2017; 60(4): 306. CrossRef
Identified Transmission Dynamics of Middle East Respiratory Syndrome Coronavirus Infection During an Outbreak: Implications of an Overcrowded Emergency Department
Thamer H. Alenazi, Hussain Al Arbash, Aiman El-Saed, Majid M. Alshamrani, Henry Baffoe-Bonnie, Yaseen M. Arabi, Sameera M. Al Johani, Ra’ed Hijazi, Adel Alothman, Hanan H. Balkhy
Clinical Infectious Diseases.2017; 65(4): 675. CrossRef
Time-optimal control strategies in SIR epidemic models
Luca Bolzoni, Elena Bonacini, Cinzia Soresina, Maria Groppi
Mathematical Biosciences.2017; 292: 86. CrossRef
Ethical Perspectives on the Middle East Respiratory Syndrome Coronavirus Epidemic in Korea
Ock-Joo Kim
Journal of Preventive Medicine and Public Health.2016; 49(1): 18. CrossRef
Current status of personnel and infrastructure resources for infection prevention and control programs in the Republic of Korea: A national survey
Young Kyung Yoon, Sung Eun Lee, Beom Sam Seo, Hyeon Jeong Kim, Jong Hun Kim, Kyung Sook Yang, Min Ja Kim, Jang Wook Sohn
American Journal of Infection Control.2016; 44(11): e189. CrossRef
Costly Lessons From the 2015 Middle East Respiratory Syndrome Coronavirus Outbreak in Korea
Sang-il Lee
Journal of Preventive Medicine and Public Health.2015; 48(6): 274. CrossRef

Perspective

Costly Lessons From the 2015 Middle East Respiratory Syndrome Coronavirus Outbreak in Korea: Sang-il Lee; J Prev Med Public Health. 2015;48(6):274-276. Published online November 25, 2015; DOI: https://doi.org/10.3961/jpmph.15.064

16,103 View
172 Download
22 Crossref

Abstract PDF

Since the Middle East respiratory syndrome (MERS) outbreak in the Republic of Korea (hereafter Korea) began on May 11, 2015, a total of 186 persons have been infected by the MERS coronavirus, 38 of whom have died. With this number, Korea becomes second only to the Kingdom of Saudi Arabia in the ranking of cumulative MERS cases. In this paper Korea’s unique experience of an outbreak of MERS will be summarized and discussed briefly.

Summary

Citations

Citations to this article as recorded by

Government Initiatives for Research Ethics During COVID-19 Pandemic in Korea
Young Su Park, Ock-Joo Kim
Journal of Korean Medical Science.2024;[Epub] CrossRef
National trend of the treatment for chronic venous diseases in Korea between 2010 and 2020
SooBum Shon, Hyangkyoung Kim, Hyeong Cheol Kim, Sungsin Cho, Seung Hwan Lee, Jin Hyun Joh
Annals of Surgical Treatment and Research.2023; 104(1): 27. CrossRef
Uncertain future of privacy protection under the Korean public health emergency preparedness governance amid the COVID-19 pandemic
Younsik Kim
Cogent Social Sciences.2022;[Epub] CrossRef
The repeated setbacks of HIV vaccine development laid the groundwork for SARS-CoV-2 vaccines
Jeffrey E. Harris
Health Policy and Technology.2022; 11(2): 100619. CrossRef
A research and development (R&D) roadmap for broadly protective coronavirus vaccines: Setting a path to address coronavirus threats
Kristine A. Moore, Michael T. Osterholm, Eve M. Lackritz, Gregory A. Poland
Vaccine.2022; 40(42): 6001. CrossRef
How College Students Assess the Threat of Infectious Diseases: Implications for University Leaders and Health Communicators
Yan Jin, Yen-I Lee, Brooke Fisher Liu, Lucinda Austin, Seoyeon Kim
Journal of International Crisis and Risk Communication Research.2021; 4: 129. CrossRef
Research Progress of Wild Bird Coronavirus
晓云米
Asian Case Reports in Veterinary Medicine.2021; 10(02): 9. CrossRef
A comparative study of COVID-19 responses in South Korea and Japan: political nexus triad and policy responses
M. Jae Moon, Kohei Suzuki, Tae In Park, Kentaro Sakuwa
International Review of Administrative Sciences.2021; 87(3): 651. CrossRef
Current Status of Global Research on Novel Coronavirus Disease (COVID-19): A Bibliometric Analysis and Knowledge Mapping
Md Mahbub Hossain
SSRN Electronic Journal .2020;[Epub] CrossRef
Influence of trust on two different risk perceptions as an affective and cognitive dimension during Middle East respiratory syndrome coronavirus (MERS-CoV) outbreak in South Korea: serial cross-sectional surveys
Won Mo Jang, Un-Na Kim, Deok Hyun Jang, Hyemin Jung, Sanghyun Cho, Sang Jun Eun, Jin Yong Lee
BMJ Open.2020; 10(3): e033026. CrossRef
Current status of global research on novel coronavirus disease (COVID-19): a bibliometric analysis and knowledge mapping
Md Mahbub Hossain
F1000Research.2020; 9: 374. CrossRef
Enhancing hospital event-based surveillance system – Findings from a pilot study, Vietnam, 2017-2018
Satoko Otsu, Hien Do, Tuan Anh Ha, Tu H. Ngo, Quang D. Tran, Orla Condell, Tuan V. Le, Nghia D. Ngu, Thanh V. Hoang, Tan Q. Dang, Phu D. Tran, Phuong T. N. Tran, Anh T. Lai, Masaya Kato, Cindy Chiu
Global Security: Health, Science and Policy.2020; 5(1): 28. CrossRef
Antiviral drugs and plasma therapy used for Covid-19 treatment: a nationwide Turkish algorithm
Hayrunnisa Nadaroglu
Drug Metabolism Reviews.2020; 52(4): 531. CrossRef
Scenarios to Manage the Demand for N95 Respirators for Healthcare Workers During the COVID-19 Pandemic

Yinxiaohe Sun, Hirono Otomaru, Sharon Esi Duoduwa Quaye, Jyoti Somani, Natasha Bagdasarian, Darius LL Beh, Dale A Fisher, Alex R Cook, Borame L Dickens
Risk Management and Healthcare Policy.2020; Volume 13: 2489. CrossRef
Adaptive evolution influences the infectious dose of MERS-CoV necessary to achieve severe respiratory disease
Madeline G. Douglas, Jacob F. Kocher, Trevor Scobey, Ralph S. Baric, Adam S. Cockrell
Virology.2018; 517: 98. CrossRef
Detection and characterisation of coronaviruses in migratory and non-migratory Australian wild birds
Anthony Chamings, Tiffanie M. Nelson, Jessy Vibin, Michelle Wille, Marcel Klaassen, Soren Alexandersen
Scientific Reports.2018;[Epub] CrossRef
Modeling pathogenesis of emergent and pre-emergent human coronaviruses in mice
Adam S. Cockrell, Sarah R. Leist, Madeline G. Douglas, Ralph S. Baric
Mammalian Genome.2018; 29(7-8): 367. CrossRef
MRPrimerV: a database of PCR primers for RNA virus detection
Hyerin Kim, NaNa Kang, KyuHyeon An, Doyun Kim, JaeHyung Koo, Min-Soo Kim
Nucleic Acids Research.2017; 45(D1): D475. CrossRef
Vaccines for emerging infectious diseases: Lessons from MERS coronavirus and Zika virus
Joel N. Maslow
Human Vaccines & Immunotherapeutics.2017; 13(12): 2918. CrossRef
A multiplex liquid-chip assay based on Luminex xMAP technology for simultaneous detection of six common respiratory viruses
Yong Yan, Jian-Yong Luo, Yin Chen, Heng-Hui Wang, Guo-Ying Zhu, Pei-Yan He, Jin-Lei Guo, Yong-Liang Lei, Zhong-Wen Chen
Oncotarget.2017; 8(57): 96913. CrossRef
Ethical Perspectives on the Middle East Respiratory Syndrome Coronavirus Epidemic in Korea
Ock-Joo Kim
Journal of Preventive Medicine and Public Health.2016; 49(1): 18. CrossRef
Persistence of Antibodies against Middle East Respiratory Syndrome Coronavirus
Daniel C. Payne, Ibrahim Iblan, Brian Rha, Sultan Alqasrawi, Aktham Haddadin, Mohannad Al Nsour, Tarek Alsanouri, Sami Sheikh Ali, Jennifer Harcourt, Congrong Miao, Azaibi Tamin, Susan I. Gerber, Lia M. Haynes, Mohammad Mousa Al Abdallat
Emerging Infectious Diseases.2016; 22(10): 1824. CrossRef

Original Articles

Respiratory Syncytial Virus Outbreak in the Basic Military Training Camp of the Republic of Korea Air Force: Won-Ju Park, Seok-Ju Yoo, Suk-Ho Lee, Jae-Woo Chung, Keun-Ho Jang, Jai-Dong Moon; J Prev Med Public Health. 2015;48(1):10-17. Published online January 14, 2015; DOI: https://doi.org/10.3961/jpmph.14.037

10,078 View
99 Download
2 Crossref

Abstract PDF

Objectives
An outbreak of acute febrile illness occurred in the Republic of Korea Air Force boot camp from May to July 2011. An epidemiological investigation of the causative agent, which was of a highly infective nature, was conducted.
Methods
Throat swabs were carried out and a multiplex reverse transcriptase-polymerase chain reaction (RT-PCR) assay was performed to identify possible causative factors.
Results
The mean age of patients who had febrile illness during the study period was 20.24 years. The multiplex RT-PCR assay identified respiratory syncytial virus (RSV) as the causative agent. The main symptoms were sore throat (76.0%), sputum (72.8%), cough (72.1%), tonsillar hypertrophy (67.9%), and rhinorrhea (55.9%). The mean temperature was 38.75°C and the attack rate among the recruits was 15.7% (588 out of 3750 recruits), while the mean duration of fever was 2.3 days. The prognosis was generally favorable with supportive care but recurrent fever occurred in 10.1% of the patients within a month.
Conclusions
This is the first epidemiological study of an RSV outbreak that developed in a healthy young adult group. In the event of an outbreak of an acute febrile illness of a highly infective nature in facilities used by a young adult group, RSV should be considered among the possible causative agents.

Summary

Citations

Citations to this article as recorded by

Respiratory syncytial virus infection and the need for immunization in Korea
Hye Young Kim, Ki Wook Yun, Hee Jin Cheong, Eun Hwa Choi, Hoan Jong Lee
Expert Review of Vaccines.2023;[Epub] CrossRef
COVID-19 outbreak in a military unit in Korea
Chanhee Kim, Young-Man Kim, Namwoo Heo, Eunjung Park, Sojin Choi, Sehyuk Jang, Nayoung Kim, Donghyok Kwon, Young-Joon Park, Byeongseop Choi, Beomman Ha, Kyounghwa Jung, Changbo Park, Sejin Park, Heeyoung Lee
Epidemiology and Health.2021; 43: e2021065. CrossRef

Epidemiological Investigation of an Outbreak of Hepatitis A at a Residential Facility for the Disabled, 2011: Hyun-Sul Lim, Kumbal Choi, Saerom Lee; J Prev Med Public Health. 2013;46(2):62-73. Published online March 28, 2013; DOI: https://doi.org/10.3961/jpmph.2013.46.2.62

10,449 View
83 Download
4 Crossref

Abstract PDF

Objectives

An outbreak of hepatitis A occurred at a residential facility for the disabled in July 10, 2011. This investigation was carried out to develop a response plan, and to find the infection source of the disease.

Methods

A field epidemiologist investigated the symptoms, vaccination histories, living environments, and probable infection sources with 51 residents and 31 teachers and staff members. In July 25, 81 subjects were tested for the hepatitis A virus antibody, and specimens of the initial 3 cases and the last case were genetically tested.

Results

Three cases occurred July 10 to 14, twelve cases August 3 to 9, and the last case on August 29. Among the teachers and staff, no one was IgM positive (on July 25). The base sequences of the initial 3 and of the last case were identical. The vehicle of the outbreak was believed to be a single person. The initial 3 patients were exposed at the same time and they might have disseminated the infection among the patients who developed symptoms in early August, and the last patient might have, in turn, been infected by the early August cases.

Conclusions

The initial source of infection is not clear, but volunteers could freely come into contact with residents, and an infected volunteer might have been the common infection source of the initial patients. Volunteers' washing their hands only after their activity might be the cause of this outbreak. Although there may be other possible causes, it would be reasonable to ask volunteers to wash their hands both before and after their activities.

Summary

Citations

Citations to this article as recorded by

Prevention of Hepatitis A Virus Infection in the United States: Recommendations of the Advisory Committee on Immunization Practices, 2020
Noele P. Nelson, Mark K. Weng, Megan G. Hofmeister, Kelly L. Moore, Mona Doshani, Saleem Kamili, Alaya Koneru, Penina Haber, Liesl Hagan, José R. Romero, Sarah Schillie, Aaron M. Harris
MMWR. Recommendations and Reports.2020; 69(5): 1. CrossRef
Outbreak of Hepatitis A Virus Infection Among Adult Patients of a Mental Hospital — Los Angeles County, 2017
Curtis Croker, Susan Hathaway, Amy Marutani, Margilane Hernandez, Crystal Cadavid, Shobita Rajagopalan, Bessie Hwang, Moon Kim
Infection Control & Hospital Epidemiology.2018; 39(07): 881. CrossRef
Estimating human-to-human transmissibility of hepatitis A virus in an outbreak at an elementary school in China, 2011
Xu-Sheng Zhang, Giovanni Lo Iacono, Eric HY Lau
PLOS ONE.2018; 13(9): e0204201. CrossRef
Source identification through social networks in an epidemiological investigation of a hepatitis A outbreak at an elementary school in Anhui province, China
J. B. WU, X. L. LI, J. ZHANG, D. XU, J. J. ZHU, B. S. ZHOU
Epidemiology and Infection.2014; 142(7): 1450. CrossRef

Special Article

The Singapore Field Epidemiology Service: Insights Into Outbreak Management: Peng-Lim Ooi, Theresa Seetoh, Jeffery Cutter; J Prev Med Public Health. 2012;45(5):277-282. Published online September 28, 2012; DOI: https://doi.org/10.3961/jpmph.2012.45.5.277

15,664 View
101 Download
2 Crossref

Abstract PDF

Field epidemiology involves the implementation of quick and targeted public health interventions with the aid of epidemiological methods. In this article, we share our practical experiences in outbreak management and in safeguarding the population against novel diseases. Given that cities represent the financial nexuses of the global economy, global health security necessitates the safeguard of cities against epidemic diseases. Singapore's public health landscape has undergone a systemic and irreversible shift with global connectivity, rapid urbanization, ecological change, increased affluence, as well as shifting demographic patterns over the past two decades. Concomitantly, the threat of epidemics, ranging from severe acute respiratory syndrome and influenza A (H1N1) to the resurgence of vector-borne diseases as well as the rise of modern lifestyle-related outbreaks, have worsened difficulties in safeguarding public health amidst much elusiveness and unpredictability. One critical factor that has helped the country overcome these innate and man-made public health vulnerabilities is the development of a resilient field epidemiology service, which includes our enhancement of surveillance and response capacities for outbreak management, and investment in public health leadership. We offer herein the Singapore story as a case study in meeting the challenges of disease control in our modern built environment.

Summary

Citations

Citations to this article as recorded by

The role of financial and epidemic crises on tourism loyalty
Mohammad Al-Shboul, Sajid Anwar, Iman Akour
Journal of Policy Research in Tourism, Leisure and Events.2023; 15(1): 18. CrossRef
“I wouldn’t really believe statistics” – Challenges with influenza vaccine acceptance among healthcare workers in Singapore
Neisha Sundaram, Kathryn Duckett, Chee Fu Yung, Koh Cheng Thoon, Sucitro Sidharta, Indumathi Venkatachalam, Angela Chow, Joanne Yoong
Vaccine.2018; 36(15): 1996. CrossRef

Brief Report

Fifteen Years After the Gozan-Dong Glass Fiber Outbreak, Incheon in 1995: Soo-Hun Cho, Joohon Sung, Jonghoon Kim, Young-Su Ju, Minji Han, Kyu-Won Jung; J Prev Med Public Health. 2011;44(4):185-189. Published online July 29, 2010; DOI: https://doi.org/10.3961/jpmph.2011.44.4.185

7,205 View
55 Download

Abstract PDF: Objectives
In 1995, an outbreak survey in Gozan-dong concluded that an association between fiberglass exposure in drinking water and cancer outbreak cannot be established. This study follows the subjects from a study in 1995 using a data linkage method to examine whether an association existed. The authors will address the potential benefits and methodological issues following outbreak surveys using data linkage, particularly when informed consent is absent.
Methods
This is a follow-up study of 697 (30 exposed) individuals out of the original 888 (31 exposed) participants (78.5%) from 1995 to 2007 assessing the cancer outcomes and deaths of these individuals. The National Cancer Registry (KNCR) and death certificate data were linked using the ID numbers of the participants. The standardized incidence ratio (SIR) and standardized mortality ratio (SMR) from cancers were calculated by the KNCR.
Results
The SIR values for all cancer or gastrointestinal cancer (GI) occurrences were the lowest in the exposed group (SIR, 0.73; 95% CI, 0.10 to 5.21; 0.00 for GI), while the two control groups (control 1: external, control 2: internal) showed slight increases in their SIR values (SIR, 1.18 and 1.27 for all cancers; 1.62 and 1.46 for GI). All lacked statistical significance. All-cause mortality levels for the three groups showed the same pattern (SMR 0.37, 1.29, and 1.11).
Conclusions
This study did not refute a finding of non-association with a 13-year follow-up. Considering that many outbreak surveys are associated with a small sample size and a cross-sectional design, follow-up studies that utilize data linkage should become standard procedure.; Summary

Original Article

Epidemiologic Investigation into the Outbreak of Acute Hemorrhagic Conjunctivitis in Gyeongju-City, South Korea, in 2002.: Hong Hwan Kim, Hyun Sul Lim, Young Sun Min; J Prev Med Public Health. 2004;37(4):312-320. Published online November 30, 2004

2,436 View
43 Download

Abstract PDF: OBJECTIVES
An outbreak of acute hemorrhagic conjunctivitis (AHC) caused by coxsackie A24 (CA24) virus occurred in South Korea in 2002. CA24 was isolated for the first time from patients with AHC. Therefore, this study was conducted to understand the transmission routes and prevent another AHC outbreaks. METHODS: The authors conducted a questionnaire survey among 1, 730 students from 2 middle schools and 1 technical high school in Gyeongju city. For statistical analysis the chi-square test was used, and chi-square for trend method showing a level of significance less than p< 0.05 was proven to be significant. Variables which were proven to be significant in univariate analysis were analysed by multiple logistic regression. RESULTS: The attack rate was 57.1%. The student groups with rubbing one's own eyes, computer usage, and sharing cellular phone had a significantly higher AHC attack rate (p< 0.05). According to the multiple logistic regression, the odds ratios for male, high school, computer use, sharing cellular phone, and rubbing one's own eyes were significant (p< 0.05). CONCLUSION: The most significant feature of this outbreak was that many students rubbed their own eyes following contact with AHC patients in a deliberate attempt to avoid going to school. Other transmission methods were computer usage and sharing cellular phone. In the future, health and school authorities must plan new strategies for the prevention of AHC.; Summary

English Abstract

Epidemiological Investigation for Outbreak of Food Poisoning Caused by Bacillus cereus Among the Workers at a Local Company in 2010.: Kum Bal Choi, Hyun Sul Lim, Kwan Lee, Gyoung Yim Ha, Kwang Hyun Jung, Chang Kyu Sohn; J Prev Med Public Health. 2011;44(2):65-73.; DOI: https://doi.org/10.3961/jpmph.2011.44.2.65

5,749 View
166 Download
7 Crossref

Abstract PDF

OBJECTIVES
In July 2 2010, a diarrhea outbreak occurred among the workers in a company in Gyeungju city, Korea. An epidemiological investigation was performed to clarify the cause and transmission route of the outbreak. METHODS: We conducted a questionnaire survey among 193 persons, and we examined 21 rectal swabs and 6 environmental specimens. We also delegated the Daegu Bukgu public health center to examine 3 food service employees and 5 environmental specimens from the P buffet which served a buffet on June 30. The patient case was defined as a worker of L Corporation and who participated in the company meal service and who had diarrhea more than one time. We also collected the underground water filter of the company on July 23. RESULTS: The attack rate of diarrhea among the employees was 20.3%. The epidemic curve showed that a single exposure peaked on July 1. The relative risk of attendance and non-attendance by date was highest for the lunch of June 30 (35.62; 95% CI, 2.25 to 574.79). There was no specific food that was statistically regarded as the source of the outbreak. Bacillus cereus was cultured from two of the rectal swabs, two of the preserved foods and the underground water filter. We thought the exposure date was lunch of June 30 according the latency period of B. cereus. CONCLUSIONS: We concluded the route of transmission was infection of dishes, spoons and chopsticks in the lunch buffet of June 30 by the underground water. At the lunch buffet, 50 dishes, 40 spoons, and chopsticks were served as cleaned and wiped with a dishcloth. We thought the underground water contaminated the dishes, spoons, chopsticks and the dishcloth. Those contaminated materials became the cause of this outbreak.

Summary

Citations

Citations to this article as recorded by

Bacillus cereus: A review of “fried rice syndrome” causative agents
Sui Sien Leong, Figen Korel, Jie Hung King
Microbial Pathogenesis.2023; 185: 106418. CrossRef
Outbreaks, Germination, and Inactivation of Bacillus cereus in Food Products: A Review
Won Choi, Sang-Soon Kim
Journal of Food Protection.2020; 83(9): 1480. CrossRef
The Bacillus cereus Food Infection as Multifactorial Process
Nadja Jessberger, Richard Dietrich, Per Einar Granum, Erwin Märtlbauer
Toxins.2020; 12(11): 701. CrossRef
Surveillance of Bacillus cereus Isolates in Korea from 2012 to 2014
Su-Mi Jung, Nan-Ok Kim, Injun Cha, Hae-young Na, Gyung Tae Chung, Hyo Sun Kawk, Sahyun Hong
Osong Public Health and Research Perspectives.2017; 8(1): 71. CrossRef
Analysis of Waterborne Pathogenic Bacteria among Total Coliform Positive Samples in the Groundwater of Chungcheongnam-do Province, Korea
Jungho Yu, Changkeun Wang, Inchul Shin, Donguk Kim, Kwisung Park
Korean Journal of Environmental Health Sciences.2016; 42(3): 189. CrossRef
Cellular responses and proteomic analysis of hemolytic Bacillus cereus MH-2 exposed to epigallocatechin gallate (EGCG)
Dong-Min Kim, Sang-Kook Park, Kye-Heon Oh
The Korean Journal of Microbiology.2016; 52(3): 260. CrossRef
Molecular Typing in Public Health Laboratories: From an Academic Indulgence to an Infection Control Imperative
Franz Allerberger
Journal of Preventive Medicine and Public Health.2012; 45(1): 1. CrossRef

Brief Communication

An Outbreak of Novel Influenza A (H1N1) in the English Language Institute.: Joon Hyung Kim, Han Sung Lee, Hye Kyung Park, Jin Seok Kim, Sang Won Lee, Seong Sun Kim, Jong Koo Lee; J Prev Med Public Health. 2010;43(3):274-278.; DOI: https://doi.org/10.3961/jpmph.2010.43.3.274

4,658 View
38 Download
1 Crossref

Abstract PDF

OBJECTIVES
This report describes the results of an investigation on an outbreak of novel influenza A (H1N1) in an English language Institute in Seoul, Korea in May 2009. METHODS: In this outbreak, novel influenza A (H1N1) was confirmed in 22 of 91 trainees, trainers and staff members. The trainees and 2 staff members were isolated in an assigned facility and the rest were isolated in their homes after we discovered the first patient with novel influenza A (H1N1). After the isolation, the people in the assigned facility were educated to use N95 respirators and they received oseltamivir for prophylaxis. RESULTS: The initial findings in this study suggest that the symptoms were mild and similar to those of seasonal influenza. The classmates and roommates of the infected patients were more likely to get infected with novel influenza A (H1N1) than the trainees who were not classmates or roommates of the patients (OR: 3.19, 95% CI=0.91 - 11.11 for classmates and OR: 40.0, 95% CI=7.4-215.7 for roommates). CONCLUSIONS: The public health response seems successful in terms of preventing the spread of this virus into the local community.

Summary

Citations

Citations to this article as recorded by

In-Flight Transmission of Novel Influenza A (H1N1)
Joon Hyung Kim, Dong-Han Lee, Sang-Sook Shin, Chun Kang, Jin Seok Kim, Byung Yool Jun, Jong-Koo Lee
Epidemiology and Health.2010; 32: e2010006. CrossRef

English Abstracts

Mumps Transmission Control Status and Inapparent Infection Rate among Middle and High School Students during the 2007-2008 Mumps Outbreak in Daegu.: Kyo Hyun Kim, Chang Hwi Kim, Bo Youl Choi, Un Yeong Go, Dong Han Lee, Moran Ki; J Prev Med Public Health. 2009;42(6):408-415.; DOI: https://doi.org/10.3961/jpmph.2009.42.6.408

5,373 View
48 Download
5 Crossref

Abstract PDF

OBJECTIVES
This study was performed to investigate the mumps transmission control status and inapparent infection rate among middle and high school students in Daegu City during a mumps outbreak. METHODS: Nine schools (two middle schools and seven high schools), which reported a number of mumps cases between 2007 and 2008 were selected for investigation. During March-May 2008, a standard questionnaire was distributed to gather information about case identification, instructed isolation measure, isolation status of mumps cases and related factors, and outdoor activities of non-isolated mumps case. Inapparent infection rate was estimated by serum mumps IgM and IgG antibodies status and self-reported mumps symptoms in three of the nine schools. RESULTS: Among 2,560 respondents, more than half of students answered that they did not receive instructions in mumps transmission control measures during the outbreak. Among the 327 mumps cases identified by the questionnaire, 131 cases (40.1%) were considered as isolated and the isolation rates were significantly different among schools, grades, and gender. Of the non-isolated cases, 88.3% continued attending school. Inapparent mumps infection rates were between 56.3% and 70.2%. CONCLUSIONS: Mumps transmission control was inadequate to control the mumps outbreak. Although high inapparent infection rate would mitigate the transmission control effect of case isolation, this measure is fundamental for infection control. The reasons of this inadequate status need to be explored to develop an effective intervention strategy.

Summary

Citations

Citations to this article as recorded by

A Case of Idiopathic Orbital Inflammation With Elevated Anti-Mumps Immunoglobulin M Antibody
Jiyeon Han, Kyung In Woo
Ophthalmic Plastic & Reconstructive Surgery.2024; 40(3): e86. CrossRef
Trend of measles, mumps, and rubella incidence following the measles‐rubella catch up vaccination in the Republic of Korea, 2001
Young June Choe, Hye‐Eun Eom, Sung‐Il Cho
Journal of Medical Virology.2017; 89(9): 1528. CrossRef
Resurgence of Mumps in Korea
Sun Hee Park
Infection & Chemotherapy.2015; 47(1): 1. CrossRef
An Outbreak of Mumps in a High School, Seoul, 2013
Ha Ra Kang, Sung Yoon Kim, Hyo Hyun Cha, Young Min An, In Ah Park, Hae Ji Kang, Byung Wook Eun
Pediatric Infection & Vaccine.2015; 22(1): 1. CrossRef
Reappraisal of MMR vaccines currently used in Korea
Hyunju Lee, Han Wool Kim, Hye Kyung Cho, Eun Ae Park, Kyong Min Choi, Kyung‐Hyo Kim
Pediatrics International.2011; 53(3): 374. CrossRef

Epidemiological Investigation of a Measles Outbreak in a Preschool in Incheon, Korea, 2006.: Jae Sung So, Un Yeong Go, Dong Han Lee, Koang Suk Park, Jong Koo Lee; J Prev Med Public Health. 2008;41(3):153-158.; DOI: https://doi.org/10.3961/jpmph.2008.41.3.153

5,315 View
65 Download
11 Crossref

Abstract PDF

OBJECTIVES
This study describes a plan that was designed to prevent a measles outbreak that showed a changed outbreak pattern. This study is based on the epidemiological investigation of a measles outbreak in a preschool in Incheon, Korea, 2006. METHODS: The subjects were 152 students at a preschool where a measles outbreak occurred. A questionnaire survey was conducted and serological testing for measlesspecific IgM was preformed. RESULTS: Of the fifteen confirmed, identified cases, eleven patients had been vaccinated with one dose, one patient had received two doses and three patients were unvaccinated. The three unvaccinated cases consisted of one 5-year-old child, one 3-year-old child and one 16-month-old infant. For the cases with one dose of the vaccination, there were 11 cases, which consisted of six 5-year-old children, two 4-year-old children, two 3-year-old children and one 2-year-old child. The case with two doses of the vaccination was one 4-year-old child. The attack rate of measles was 100% in the 0-dose group, 11.2% in the 1-dose group and 2.0% in the 2-dose group. The vaccine's efficacy was 88.8% in the 1-dose group and 98.0% in the 2-dose group. The vaccine effectiveness for the 2-dose group was higher than that of the 1-dose group. CONCLUSIONS: High coverage with a 2-dose vaccination should be maintained, and the vaccination should be given at the suitable time to prevent a measles outbreak with a changed outbreak pattern.

Summary

Citations

Citations to this article as recorded by

Vaccines for measles, mumps, rubella, and varicella in children
Carlo Di Pietrantonj, Alessandro Rivetti, Pasquale Marchione, Maria Grazia Debalini, Vittorio Demicheli
Cochrane Database of Systematic Reviews.2021;[Epub] CrossRef
Vaccines for measles, mumps, rubella, and varicella in children
Carlo Di Pietrantonj, Alessandro Rivetti, Pasquale Marchione, Maria Grazia Debalini, Vittorio Demicheli
Cochrane Database of Systematic Reviews.2020;[Epub] CrossRef
Measles Elimination Activities in the Western Pacific Region: Experience from the Republic of Korea
Young June Choe, Youngmee Jee, Myoung-don Oh, Jong-Koo Lee
Journal of Korean Medical Science.2015; 30(Suppl 2): S115. CrossRef
Epidemiological Investigation of a Measles Outbreak in Seoul, 2013~2014
Heejin Ham, Jungim Jang, Changho Han
Journal of Bacteriology and Virology.2015; 45(4): 372. CrossRef
Vaccines for measles, mumps and rubella in children
Vittorio Demicheli, Alessandro Rivetti, Maria Grazia Debalini, Carlo Di Pietrantonj
Evidence-Based Child Health: A Cochrane Review Journal.2013; 8(6): 2076. CrossRef
Reemergence of Measles in South Korea: Implications for Immunization and Surveillance Programs
Young-Joon Park, Hye Suk Eom, Eun Seong Kim, Young June Choe, Geun-Ryang Bae, Duk-Hyoung Lee
Japanese Journal of Infectious Diseases.2013; 66(1): 6. CrossRef
Assessment of Serologic Immunity to Diphtheria-Tetanus-Pertussis After Treatment of Korean Pediatric Hematology and Oncology Patients
Hyo Jin Kwon, Jae-Wook Lee, Nak-Gyun Chung, Bin Cho, Hack-Ki Kim, Jin Han Kang
Journal of Korean Medical Science.2012; 27(1): 78. CrossRef
Current status of measles in the Republic of Korea: an overview of case-based and seroepidemiological surveillance scheme
Young June Choe, Geun-Ryang Bae
Korean Journal of Pediatrics.2012; 55(12): 455. CrossRef
Seroprevalence of measles among children affected by national measles elimination program in Korea, 2010
Eun Seong Kim, Young June Choe, Heeyeon Cho, You-Jin Kim, Hee Sook Yoon, Jeong-Sun Yang, Kisoon Kim, Geun-Ryang Bae, Duk-hyoung Lee
Vaccine.2012; 30(23): 3355. CrossRef
Vaccines for measles, mumps and rubella in children
Vittorio Demicheli, Alessandro Rivetti, Maria Grazia Debalini, Carlo Di Pietrantonj
Cochrane Database of Systematic Reviews.2012;[Epub] CrossRef
Evaluation of an Expanded Case Definition for Vaccine-Modified Measles in a School Outbreak in South Korea in 2010
Young June Choe, Jae Kyung Hu, Kyung Min Song, Heeyeon Cho, Hee Sook Yoon, Seung Tae Kim, Han Jung Lee, Kisoon Kim, Geun-Ryang Bae, Jong-Koo Lee
Japanese Journal of Infectious Diseases.2012; 65(5): 371. CrossRef

Original Article

Epidemiologic Investigation on an Outbreak of Cholera in Gyeongsangbuk-do, Korea, 2001.: Jun Ho Lee, Hyun Sul Lim, Kwan Lee, Jun Chul Kim, Sang Won Lee, Un Yeong Go, Byung Kuk Yang, Jong Koo Lee, Moon Sik Kim; Korean J Prev Med. 2002;35(4):295-304.

2,458 View
42 Download

Abstract PDF: OBJECTIVES
This study was carried out to investigate the cause, magnitude and transmission route of the cholera outbreak in 2001. METHODS: The study population were those persons who ingested foods at the restaurant, were confirmed as cholera patients, had symptoms of diarrhea and served as workers at the restaurant. A questionnaire survey and microbiological examinations on the microbes isolated from rectal swabs were conducted. Of the cases, 316 food histories were surveyed by an analysis of the restaurant menu. RESUJLTS: There were 139 confirmed cases of cholera reported in Korea in 2001. Of these, 104 were related to the restaurant. By region, Gyeongsangbuk-do had the highest incidence with 91 cases. Of these 91 cases, 74 had ingested foods at the restaurant, 2 were employees and 3 were secondary infection cases within the families. The results of the odds ratio analysis of the 316 persons having ingested foods at the restaurant were as follows: sandwiches 5.07 (95% CI, 1.85-14.59), soybean curd 2.45 (95% CI, 1.09-5.56), noodles 2.34 (95% CI, 1.24-4.42), steamed squid 2.01 (95% CI, 1.17-3.47) and vinegared rice 1.82 (95% CI, 1.08-3.09). It was certain the restaurant in question was the cause of the 2001 outbreak. CONCLUSIONS: We suspected that more than one restaurant employee contaminated foods served at the restaurant. In addition, eating raw fishes purchased at the Pohang Fisheries infected the employees of the restaurant. There is a possibility that these raw fishes were themselves contaminated by cholera bacilli in the sea.; Summary

First
Prev
Page of 2
Next
Last

Search