A bacteriophage-based validation of a personal protective equipment doffing procedure to be used with high-consequence pathogens

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.

Connecting pathogen transmission and healthcare worker cognition: a cognitive task analysis of infection prevention and control practices during simulated patient care

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.

Enteric Populations of Escherichia coli are Likely to be Resistant to Phages Due to O Antigen Production

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.

A methodology for using Lambda phages as a proxy for pathogen transmission in hospitals

BACKGROUND

One major concern in hospitalized patients is acquiring infections from pathogens borne on surfaces, patients, and healthcare workers (HCWs). Fundamental to controlling healthcare-associated infections is identifying the sources of pathogens, monitoring the processes responsible for their transmission, and evaluating the efficacy of the procedures employed for restricting their transmission.

AIM

To present a method using the bacteriophage Lambda (λ) to achieve these ends.

METHODS

Defined densities of multiple genetically marked λ phages were inoculated at known hotspots for contamination on high-fidelity mannequins. HCWs then entered a pre-sanitized simulated hospital room and performed a series of patient care tasks on the mannequins. Sampling occurred on the scrubs and hands of the HCWs, as well as previously defined high-touch surfaces in hospital rooms. Following sampling, the rooms were decontaminated using procedures demonstrated to be effective. Following the conclusion of the simulation, the samples were tested for the presence, identity, and densities of these λ phages.

FINDINGS

The data generated enabled the determination of the sources and magnitude of contamination caused by the breakdown of established infection prevention practices by HCWs. This technique enabled the standardized tracking of multiple contaminants during a single episode of patient care. Unlike other biological surrogates, λ phages are susceptible to common hospital disinfectants, and allow for a more accurate evaluation of pathogen transmission.

CONCLUSION

Whereas our application of these methods focused on healthcare-associated infections and the role of HCW behaviours in their spread, these methods could be employed for identifying the sources and sites of microbial contamination in other settings.

Genes for tRNALys5 from Drosophila melanogaster

The sequences of two cloned genes from Drosophila which hybridize with tRNALys5 are reported. One gene, in plasmid pDt39, has a sequence which corresponds to the sequence of tRNA. The other gene, in pDt59R, differs in three nucleotides pairs. Both plasmids are transcribed in vitro with extracts of Drosophila Kc cells to give full-sized tRNA precursors with four additional nucleotides at the 5'-end as well as truncated molecules containing 35 nucleotides. This premature termination occurs in a block of four T residues within the mature coding region. Sequences flanking the tRNA genes show little in common except for the blocks of five or more T-residues beyond the 3'-end of the gene. pDt39 hybridizes to 84AB on the polytene chromosomes of Drosophila and pDt59R hybridizes to 29A.