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Epidemiologic Investigation
Detecting mpox infection in the early epidemic: an epidemiologic investigation of the third and fourth cases in Korea
Taeyoung Kim, Eonjoo Park, Jun Suk Eun, Eun-young Lee, Ji Won Mun, Yunsang Choi, Shinyoung Lee, Hansol Yeom, Eunkyoung Kim, Jongmu Kim, Jihyun Choi, Jinho Ha, Sookkyung Park
Epidemiol Health. 2023;45:e2023040.   Published online March 23, 2023
DOI: https://doi.org/10.4178/epih.e2023040
  • 3,882 View
  • 178 Download
  • 2 Web of Science
  • 3 Crossref
AbstractAbstract AbstractSummary PDF
Abstract
OBJECTIVES
As few mpox cases have been reported in Korea, we aimed to identify the characteristics of mpox infection by describing our epidemiologic investigation of a woman patient (index patient, the third case in Korea) and a physician who was infected by a needlestick injury (the fourth case).
METHODS
We conducted contact tracing and exposure risk evaluation through interviews with these 2 patients and their physicians and contacts, as well as field investigations at each facility visited by the patients during their symptomatic periods. We then classified contacts into 3 levels according to their exposure risk and managed them to minimize further transmission by recommending quarantine and vaccination for post-exposure prophylaxis and monitoring their symptoms.
RESULTS
The index patient had sexual contact with a man foreigner during a trip to Dubai, which was considered the probable route of transmission. In total, 27 healthcare-associated contacts across 7 healthcare facilities and 9 community contacts were identified. These contacts were classified into high (7 contacts), medium (9 contacts), and low (20 contacts) exposure risk groups. One high-risk contact was identified as a secondary patient: a physician who was injured while collecting specimens from the index patient.
CONCLUSIONS
The index patient visited several medical facilities due to progressive symptoms prior to isolation. Although the 2022 mpox epidemic mainly affected young men, especially men who have sex with men, physicians should also consider mpox transmission in the general population for the timely detection of mpox-infected patients.
Summary
Korean summary
국내 엠폭스 3번환자는 전파 가능 시기에 7곳의 의료기관을 방문했으며, 접촉자로 분류된 27명의 의료기관 접촉자와 9명의 지역사회 접촉자 중 주사침 자상을 입은 의료인 1명이 추가 확진되었다. 적시에 엠폭스 환자를 발견하기 위하여 의료인들은 전파위험이 낮은 일반 인구의 감염 가능성에 대한 고려가 필요하다.
Key Message
As a result of contact tracing of a mpox patient in the early phase of epidemic, she visited 7 healthcare facilities to be diagnosed which infers diagnosing those who are statistically not at high risk is challenging. Yet the risk of contracting mpox seems relatively low as only one of 36 contacts was infected; a healthcare personnel who sustained a needlestick injury.

Citations

Citations to this article as recorded by  
  • Clinical Features of Mpox Patients in Korea: A Multicenter Retrospective Study
    So Yun Lim, Hyeon Jae Jo, Su-Yeon Lee, Miyoung Ahn, Yeonjae Kim, Jaehyun Jeon, Eu Suk Kim, BumSik Chin, Jae-Phil Choi, Nam Joong Kim
    Journal of Korean Medical Science.2024;[Epub]     CrossRef
  • Transmission potential of mpox in mainland China, June-July 2023: estimating reproduction number during the initial phase of the epidemic
    Andrei R. Akhmetzhanov, Pei-Hsuan Wu
    PeerJ.2024; 12: e16908.     CrossRef
  • Mpox exposure and transmission in healthcare settings during the 2022 global outbreak
    Kimon C Zachary, Lisa L Philpotts, Erica S Shenoy
    Current Opinion in Infectious Diseases.2023; 36(4): 257.     CrossRef
Original Article
Predicting needlestick and sharps injuries and determining preventive strategies using a Bayesian network approach in Tehran, Iran
Hamed Akbari, Fakhradin Ghasemi, Hesam Akbari, Amir Adibzadeh
Epidemiol Health. 2018;40:e2018042.   Published online August 20, 2018
DOI: https://doi.org/10.4178/epih.e2018042
  • 15,845 View
  • 279 Download
  • 21 Web of Science
  • 21 Crossref
AbstractAbstract PDFSupplementary Material
Abstract
OBJECTIVES
Recent studies have shown that the rate of needlestick and sharps injuries (NSIs) is unacceptably high in Iranian hospitals. The aim of the present study was to use a systematic approach to predict and reduce these injuries.
METHODS
This cross-sectional study was conducted in 5 hospitals in Tehran, Iran. Eleven variables thought to affect NSIs were categorized based on the Human Factors Analysis and Classification System (HFACS) framework and modeled using a Bayesian network. A self-administered validated questionnaire was used to collect the required data. In total, 343 cases were used to train the model and 50 cases were used to test the model. Model performance was assessed using various indices. Finally, using predictive reasoning, several intervention strategies for reducing NSIs were recommended.
RESULTS
The Bayesian network HFACS model was able to predict 86% of new cases correctly. The analyses showed that safety motivation and fatigue were the most important contributors to NSIs. Supervisors’ attitude toward safety and working hours per week were the most important factors in the unsafe supervision category. Management commitment and staffing were the most important organizational-level factors affecting NSIs. Finally, promising intervention strategies for reducing NSIs were identified and discussed.
CONCLUSIONS
To reduce NSIs, both management commitment and sufficient staffing are necessary. Supervisors should encourage nurses to engage in safe behavior. Excessive working hours result in fatigue and increase the risk of NSIs.
Summary

Citations

Citations to this article as recorded by  
  • Analysis of factors associated with needlestick injuries of clinical nurses by applying a human factor analysis and classification system: A nationwide cross‐sectional survey
    Huimin Gao, Mengyuan Liu, Yanan Su, Yinglan Li, Lingyun Tian
    Journal of Clinical Nursing.2024;[Epub]     CrossRef
  • Shift work organization on nurse injuries: A scoping review
    Christopher C. Imes, Nicole J. Barthel, Eileen R. Chasens, Jacqueline Dunbar-Jacob, Sandra J. Engberg, Christine A. Feeley, Laura A. Fennimore, Cassandra M. Godzik, Mary Lou Klem, Faith S. Luyster, Dianxu Ren, Lynn Baniak
    International Journal of Nursing Studies.2023; 138: 104395.     CrossRef
  • Exposure to needle stick injuries among health care workers in hemodialysis units in the southwest of Iran: a cross-sectional study
    Jamshid Roozbeh, Leila Malekmakan, Mina Mashayekh, Anahita Dehghani, Soroush Ansari, Hossein Akbarialiabad, Mehdi Mahmudpour
    BMC Health Services Research.2023;[Epub]     CrossRef
  • Determination and prioritization of factors affecting the occurrence of needle stick injuries among healthcare workers using techniques of Delphi and fuzzy analytical hierarchy process (FAHP)
    Seyed Mahdi Mousavi, Saeid Yazdanirad, Sara Althubiti, Masoud Askari Majdabadi, Faranak Najarian, Parvin Sepehr
    BMC Public Health.2023;[Epub]     CrossRef
  • Analysis of occupational accidents among nurses working in hospitals based on safety climate and safety performance: a Bayesian network analysis
    Fakhradin Ghasemi, Hamed Aghaei, Taleb Askaripoor, Farhad Ghamari
    International Journal of Occupational Safety and Ergonomics.2022; 28(1): 440.     CrossRef
  • Prediction of human error probability during the hydrocarbon road tanker loading operation using a hybrid technique of fuzzy sets, Bayesian network and CREAM
    Fakhradin Ghasemi, Arash Ghasemi, Omid Kalatpour
    International Journal of Occupational Safety and Ergonomics.2022; 28(3): 1342.     CrossRef
  • Fatigue profile among petrochemical firefighters and its relationship with safety behavior: the moderating and mediating roles of perceived safety climate
    Fakhradin Ghasemi, Hemn Zarei, Mohammad Babamiri, Omid Kalatpour
    International Journal of Occupational Safety and Ergonomics.2022; 28(3): 1822.     CrossRef
  • Work schedule characteristics and occupational fatigue/recovery among rotating‐shift nurses: A cross‐sectional study
    Ari Min, Hye Chong Hong, Young Man Kim
    Journal of Nursing Management.2022; 30(2): 463.     CrossRef
  • Human and organizational failures analysis in process industries using FBN-HFACS model: Learning from a toxic gas leakage accident
    Fakhradin Ghasemi, Kamran Gholamizadeh, Amirhasan Farjadnia, Alireza Sedighizadeh, Omid Kalatpour
    Journal of Loss Prevention in the Process Industries.2022; 78: 104823.     CrossRef
  • Occupational fatigue, workload and nursing teamwork in hospital nurses
    Hyeonmi Cho, Knar Sagherian, Linda D. Scott, Linsey M. Steege
    Journal of Advanced Nursing.2022; 78(8): 2313.     CrossRef
  • Dynamic risk analysis of hydrogen gas leakage using Bow-tie technique and Bayesian network
    H. Borgheipour, G. M. Tehrani, T. Eskandari, O. C. Mohammadieh, I. Mohammadfam
    International Journal of Environmental Science and Technology.2021; 18(11): 3613.     CrossRef
  • Education and training for preventing sharps injuries and splash exposures in healthcare workers
    Shelley Cheetham, Hanh TT Ngo, Juha Liira, Helena Liira
    Cochrane Database of Systematic Reviews.2021;[Epub]     CrossRef
  • Risk Factors of Needlestick and Sharp Injuries among Health Care Workers at Sanglah Tertiary Hospital
    I Komang Widarma Atmaja, I Made Ady Wirawan, I Ketut Suarjana
    Jurnal Berkala Epidemiologi.2021; 9(1): 36.     CrossRef
  • Comparison of Job Satisfaction and Job Stress Among Nurses, Operating Room and Anesthesia Staff
    Ramin Rahmani, Ali Ebrazeh, Farzad Zandi, Roghayeh Rouhi, Shirdel Zandi
    Journal of Ergonomics.2021; 8(4): 103.     CrossRef
  • Multicenter cross-sectional study on the reporting status and influencing factors of needlestick injuries caused by insulin injection devices among nurses in Peking, China
    Yingyue Dong, Fangfang Li, Jing Li, Rui Li, Qun Wang
    American Journal of Infection Control.2020; 48(7): 805.     CrossRef
  • Prevalence of needlestick injuries among health-care workers in iranian hospitals: An updated systematic review and meta-analysis
    Yousef Alimohamadi, Maryam Taghdir, Mojtaba Sepandi, Leila Kalhor, Fahimeh Abedini
    Archives of Trauma Research.2020; 9(2): 47.     CrossRef
  • Predictors of Blood and Body Fluid Exposure and Mediating Effects of Infection Prevention Behavior in Shift-Working Nurses: Application of Analysis Method for Zero-Inflated Count Data
    Jae Geum Ryu, Smi Choi-Kwon
    Journal of Korean Academy of Nursing.2020; 50(5): 658.     CrossRef
  • A new scoring system for the Rapid Entire Body Assessment (REBA) based on fuzzy sets and Bayesian networks
    Fakhradin Ghasemi, Neda Mahdavi
    International Journal of Industrial Ergonomics.2020; 80: 103058.     CrossRef
  • The Relationships Among Occupational Safety Climate, Patient Safety Climate, and Safety Performance Based on Structural Equation Modeling
    Hamed Aghaei, Zahra Sadat Asadi, Mostafa Mirzaei Aliabadi, Hassan Ahmadinia
    Journal of Preventive Medicine and Public Health.2020; 53(6): 447.     CrossRef
  • Analysis of the severity of occupational injuries in the mining industry using a Bayesian network
    Mostafa Mirzaei Aliabadi, Hamed Aghaei, Omid kalatpuor, Ali Reza Soltanian, Asghar Nikravesh
    Epidemiology and Health.2019; 41: e2019017.     CrossRef
  • The links among workload, sleep quality, and fatigue in nurses: a structural equation modeling approach
    Fakhradin Ghasemi, Parnia Samavat, Fatemeh Soleimani
    Fatigue: Biomedicine, Health & Behavior.2019; 7(3): 141.     CrossRef

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