Assessing the Likelihood of Hand-to-Hand Cross-Transmission of Bacteria: An Experimental Study

Infect Control Hosp Epidemiol. 2017 May;38(5):553-558. doi: 10.1017/ice.2017.9. Epub 2017 Feb 22.

Abstract

BACKGROUND Although the hands of healthcare workers (HCWs) are implicated in most episodes of healthcare-associated infections, the correlation between hand contamination and the likelihood of cross-transmission remains unknown. METHODS We conducted a laboratory-based study involving pairs of HCWs. The hands of a HCW (transmitter) were contaminated with Escherichia coli ATCC 10536 before holding hands with another HCW (host) for 1 minute. Meanwhile, the unheld hand of the transmitter was sampled. Afterward, the host's held hand was also sampled. Each experiment consisted of 4 trials with increasing concentrations of E. coli (103-106 colony-forming units [cfu]/mL). The primary outcome was the likelihood of transmission of at least 1 cfu from transmitter to host. We used a mixed logistic regression model with a random effect on the subject to assess the association between transmission and bacterial count on the transmitter's hands. RESULTS In total, 6 HCWs performed 30 experiments and 120 trials. The bacterial counts recovered from host hands were directly associated with the bacterial counts on transmitter hands (P1 and ≤3 log10 cfu compared to ≤1 log10. When transmitter contamination was <1 log10 cfu, no cross-transmission was detected. CONCLUSION There is a direct relationship between the bacterial burden on HCWs hands and the likelihood of cross-transmission. Under the described conditions, at least 1 log10 cfu must be present on HCW hands to be potentially transmitted. Further studies are needed at the low contamination range. Infect Control Hosp Epidemiol 2017;38:553-558.

MeSH terms

  • Colony Count, Microbial
  • Cross Infection / microbiology*
  • Cross Infection / transmission*
  • Escherichia coli / isolation & purification*
  • Escherichia coli Infections / transmission*
  • Hand / microbiology*
  • Health Personnel
  • Hospitals, University
  • Humans
  • Logistic Models
  • Switzerland / epidemiology