Background: Transmission of harmful microorganisms may lead to infections and poses a major threat to patients and healthcare workers in healthcare settings. The most effective countermeasure against the transmission and spread of harmful microorganisms is the adherence to spatiotemporal hand hygiene policies, but adherence rates are relatively low and vary over space and time. The spatiotemporal effects on the transmission and spread of harmful microorganisms for varying levels of hand hygiene compliance are unknown. The objectives of this study are to (1) identify a healthcare worker occupancy group of potential super-spreaders and (2) quantify spatiotemporal effects on the transmission and spread of harmful microorganisms for varying levels of hand hygiene compliance caused by this group.
Methods: Spatiotemporal data were collected in a ward of an academic hospital using radio frequency identification technology for seven days. A potential super-spreader healthcare worker occupation group was identified using the contact data derived from the frequency identification sensors. The effects of five probability distributions of hand hygiene compliance and three rates of harmful microorganism transmission were simulated using a dynamic agent-based simulation model. The effects of initial simulation assumptions on the simulation results were quantified using five risk factors.
Results: Nurses, doctors and patients are together responsible for 78.8% of all contacts. Nurses made up 57% of all contacts, which is more than five times that of doctors (11.1%). This identifies nurses as the potential super-spreader healthcare worker occupation group. For initial simulation conditions of extreme lack of hand hygiene compliance (5%) and high transmission rates (5% per contact moment), a colonized nurse can transfer microbes to three of the 17 healthcare worker or patients encountered during the 87 minutes of visiting 22 rooms while colonized. The harmful microorganism transmission potential for nurses is higher during weeknights (5 pm – 7 am) and weekends as compared to weekdays (7 am – 5 pm).
Conclusion: Spatiotemporal behaviour and social mixing patterns of healthcare can change the expected number of transmissions and spread of harmful microorganism by super-spreaders in a closed healthcare setting. These insights can be used to develop better-informed infection prevention and control strategies.