Literature DB >> 32574702

Super-factors associated with transmission of occupational COVID-19 infection among healthcare staff in Wuhan, China.

Y Wang1, W Wu2, Z Cheng3, X Tan4, Z Yang5, X Zeng6, B Mei7, Z Ni8, X Wang9.   

Abstract

BACKGROUND: Globally, there have been many cases of coronavirus disease 2019 (COVID-19) among medical staff; however, the main factors associated with the infection are not well understood. AIM: To identify the super-factors causing COVID-19 infection in medical staff in China.
METHODS: A cross-sectional study was conducted between January 1st and February 30th, 2020, in which front-line members of medical staff who took part in the care and treatment of patients with COVID-19 were enrolled. Epidemiological and demographic data between infected and uninfected groups were collected and compared. Social network analysis (SNA) was used to establish socio-metric social links between influencing factors.
FINDINGS: A total of 92 medical staff were enrolled. In all participant groups, the super-factor identified by the network was wearing a medical protective mask or surgical mask correctly (degree: 572; closeness: 25; betweenness centrality: 3.23). Touching the cheek, nose, and mouth while working was the super-factor in the infected group. This was the biggest node in the network and had the strongest influence (degree: 370; closeness: 29; betweenness centrality: 0.37). Self-protection score was the super-factor in the uninfected group but was the isolated factor in the infected group (degree: 201; closeness: 28; betweenness centrality: 5.64). For family members, the exposure history to Huanan Seafood Wholesale Market and the contact history to wild animals were two isolated nodes.
CONCLUSION: High self-protection score was the main factor that prevented medical staff from contracting COVID-19 infection. The main factor contributing to COVID-19 infections among medical staff was touching the cheek, nose, and mouth while working.
Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Infection; Medical staff; SARS-CoV-2; Social network analysis; Super-factors

Mesh:

Year:  2020        PMID: 32574702     DOI: 10.1016/j.jhin.2020.06.023

Source DB:  PubMed          Journal:  J Hosp Infect        ISSN: 0195-6701            Impact factor:   3.926


  4 in total

Review 1.  Remote nursing training model combined with proceduralization in the intensive care unit dealing with patients with COVID-19.

Authors:  Hui Wang; Kai Kang; Yang Gao; Bo Yang; Jing Li; Lei Wang; Ying Bi; Kai-Jiang Yu; Qing-Qing Dai; Ming-Yan Zhao
Journal:  World J Clin Cases       Date:  2021-02-16       Impact factor: 1.337

2.  Knowledge, attitude and practice concerning healthcare-associated infections among healthcare workers in Wuhan, China: cross-sectional study.

Authors:  Wenwen Wu; Wenru Wang; Yufeng Yuan; Likai Lin; Yibin Tan; Jinru Yang; Li Dai; Ying Wang
Journal:  BMJ Open       Date:  2021-01-05       Impact factor: 2.692

Review 3.  Implications of human activities for (re)emerging infectious diseases, including COVID-19.

Authors:  Nundu Sabiti Sabin; Akintije Simba Calliope; Shirley Victoria Simpson; Hiroaki Arima; Hiromu Ito; Takayuki Nishimura; Taro Yamamoto
Journal:  J Physiol Anthropol       Date:  2020-09-25       Impact factor: 2.867

4.  Revisiting the Effects of High-Speed Railway Transfers in the Early COVID-19 Cross-Province Transmission in Mainland China.

Authors:  Chun-Hsiang Chan; Tzai-Hung Wen
Journal:  Int J Environ Res Public Health       Date:  2021-06-13       Impact factor: 3.390

  4 in total

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