Health Care Workers Causing Large Nosocomial Outbreaks: A Systematic Review

BMC Infect Dis. 2013 Feb 22;13:98. doi: 10.1186/1471-2334-13-98.

Abstract

Backgrounds: Staff in the hospital itself may be the source of a nosocomial outbreak (NO). But the role of undetected carriers as an outbreak source is yet unknown.

Methods: A systematic review was conducted to evaluate outbreaks caused by health care workers (HCW). The Worldwide Outbreak Database and PubMed served as primary sources of data. Articles in English, German or French were included. Other reviews were excluded. There were no restrictions with respect to the date of publication.Data on setting, pathogens, route of transmission, and characteristics of the HCW was retrieved. Data from large outbreaks were compared to smaller outbreaks.

Results: 152 outbreaks were included, mainly from surgery, neonatology, and gynecology departments. Most frequent corresponding infections were surgical site infections, infection by hepatitis B virus, and septicemia. Hepatitis B virus (27 NO), S. aureus (49 NO) and S. pyogenes (19 NO) were the predominant pathogens involved. 59 outbreaks (41.5%) derived from physicians and 56 outbreaks (39.4%) derived from nurses. Transmission mainly occurred via direct contact. Surgical and pediatric departments were significantly associated with smaller outbreaks, and gynecology with larger outbreaks. Awareness of carrier status significantly decreased the risk of causing large outbreaks.

Conclusions: As NO caused by HCW represent a rare event, screening of personnel should not be performed regularly. However, if certain species of microorganisms are involved, the possibility of a carrier should be taken into account.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review
  • Systematic Review

MeSH terms

  • Analysis of Variance
  • Cross Infection / epidemiology*
  • Cross Infection / prevention & control
  • Cross Infection / transmission
  • Disease Outbreaks / prevention & control
  • Disease Outbreaks / statistics & numerical data*
  • Health Personnel / statistics & numerical data*
  • Humans
  • Infection Control / statistics & numerical data
  • Logistic Models
  • Risk Factors