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OBJECTIVE: To determine if the high-level personal protective equipment used in the treatment of high-consequence infectious diseases is effective at stopping the spread of pathogens to healthcare personnel (HCP) while doffing. BACKGROUND: Personal protective equipment (PPE) is fundamental to the safety of HCPs. HCPs treating patients with high-consequence infectious diseases use several layers of PPE, forming complex protective ensembles. With high-containment PPE, step-by-step procedures are often used for donning and doffing to minimize contamination risk to the HCP, but these procedures are rarely empirically validated and instead rely on following infection prevention best practices. METHODS: A doffing protocol video for a high-containment PPE ensemble was evaluated to determine potential contamination pathways. These potential pathways were tested using fluorescence and genetically marked bacteriophages. RESULTS: The experiments revealed existing protocols permit contamination pathways allowing for transmission of bacteriophages to HCPs. Updates to the doffing protocols were generated based on the discovered contamination pathways. This updated doffing protocol eliminated the movement of viable bacteriophages from the outside of the PPE to the skin of the HCP. CONCLUSIONS: Our results illustrate the need for quantitative, scientific investigations of infection prevention practices, such as doffing PPE.
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BACKGROUND: Relatively little is known about the cognitive processes of healthcare workers that mediate between performance-shaping factors (eg, workload, time pressure) and adherence to infection prevention and control (IPC) practices. We taxonomised the cognitive work involved in IPC practices and assessed its role in how pathogens spread. METHODS: Forty-two registered nurses performed patient care tasks in a standardised high-fidelity simulation. Afterwards, participants watched a video of their simulation and described what they were thinking, which we analysed to obtain frequencies of macrocognitive functions (MCFs) in the context of different IPC practices. Performance in the simulation was the frequency at which participants spread harmless surrogates for pathogens (bacteriophages). Using a tertiary split, participants were categorised into a performance group: high, medium or low. To identify associations between the three variables-performance groups, MCFs and IPC practices-we used multiblock discriminant correspondence analysis (MUDICA). RESULTS: MUDICA extracted two factors discriminating between performance groups. Factor 1 captured differences between high and medium performers. High performers monitored the situation for contamination events and mitigated risks by applying formal and informal rules or managing their uncertainty, particularly for sterile technique and cleaning. Medium performers engaged more in future-oriented cognition, anticipating contamination events and planning their workflow, across many IPC practices. Factor 2 distinguished the low performers from the medium and high performers who mitigated risks with informal rules and sacrificed IPC practices when managing tradeoffs, all in the context of minimising cross-contamination from physical touch. CONCLUSIONS: To reduce pathogen transmission, new approaches to training IPC (eg, cognitive skills training) and system design are needed. Interventions should help nurses apply their knowledge of IPC fluidly during patient care, prioritising and monitoring situations for risks and deciding how to mitigate risks. Planning IPC into one's workflow is beneficial but may not account for the unpredictability of patient care.
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Bioinformatic and experimental data show that bacteriophages are ubiquitous in human enteric microbiomes. However, there are gaps in understanding the contribution of these viruses in shaping the bacterial strain and species composition of the gut microbiome and how these phages are maintained over time. To address these questions, we adapted and analyzed the properties of a mathematical model of the population and evolutionary dynamics of bacteria and phage and performed experiments with Escherichia coli and phages isolated from four fecal microbiota transplantation (FMT) doses as representative samples of non-dysbiotic enteric microbiota. Our models predict and experiments confirm that due to production of the O antigen, E. coli in the enteric microbiome are likely to be resistant to infection with co-occurring phages. However, phages can be maintained in these populations in high densities due to high rates of transition between resistant and sensitive states, which we call leaky resistance. Based on these models and observations, we postulate that the phages found in the human gut are likely to play little role in shaping the composition of E. coli in the enteric microbiome in healthy individuals. How general this is for other species of bacteria in enteric microbiota is not yet clear, although O antigen production is broadly conserved across many taxa.