Dynamics of the Oral Microbiome During Initial Military Training at Fort Benning, Georgia.

INTRODUCTION: Military trainees are at increased risk for infectious disease outbreaks because of the unique circumstances of the training environment (e.g., close proximity areas and physiologic/psychologic stress). Standard medical countermeasures in military training settings include routine immunization (e.g., influenza and adenovirus) as well as chemoprophylaxis [e.g., benzathine penicillin G (Bicillin) for the prevention of group A streptococcal disease] for pathogens associated with outbreaks in these settings. In a population of U.S. Army Infantry trainees, we evaluated changes in the oral microbiome during a 14-week military training cycle. MATERIALS AND METHODS: Trainees were enrolled in an observational cohort study in 2015-2016. In 2015, Bicillin was administered to trainees to ameliorate the risk of group A Streptococcus outbreaks, whereas in 2016, trainees did not receive a Bicillin inoculation. Oropharyngeal swabs were collected from participants at days 0, 7, 14, 28, 56, and 90 of training. Swabs were collected, flash frozen, and stored. DNA was extracted from swabs, and amplicon sequencing of the 16s rRNA gene was performed. Microbiome dynamics were evaluated using the QIIME 2 workflow along with DADA2, SINA with SILVA, and an additional processing in R. RESULTS: We observed that microbiome samples from the baseline (day 0) visit were distinct from one another, whereas samples collected on day 14 exhibited significant microbiome convergence. Day 14 convergence was coincident with an increase in DNA sequences associated with Streptococcus, though there was not a significant difference between Streptococcus abundance over time between 2015 and 2016 (P = .07), suggesting that Bicillin prophylaxis did not significantly impact overall Streptococcus abundance. CONCLUSIONS: The temporary convergence of microbiomes is coincident with a rise in communicable infections in this population. The dynamic response of microbiomes during initial military training supports similar observations in the literature of transient convergence of the human microbiome under cohabitation in the time frame including in this experiment. This population and the associated longitudinal studies allow for controlled studies of human microbiome under diverse conditions.

Improving physical distancing among healthcare workers in a pediatric intensive care unit.

BACKGROUND: Healthcare workers (HCWs) not adhering to physical distancing recommendations is a risk factor for acquisition of severe acute respiratory coronavirus virus 2 (SARS-CoV-2). The study objective was to assess the impact of interventions to improve HCW physical distancing on actual distance between HCWs in a real-life setting. METHODS: HCWs voluntarily wore proximity beacons to measure the number and intensity of physical distancing interactions between each other in a pediatric intensive care unit. We compared interactions before and after implementing a bundle of interventions including changes to the layout of workstations, cognitive aids, and individual feedback from wearable proximity beacons. RESULTS: Overall, we recorded 10,788 interactions within 6 feet (∼2 m) and lasting >5 seconds. The number of HCWs wearing beacons fluctuated daily and increased over the study period. On average, 13 beacons were worn daily (32% of possible staff; range, 2-32 per day). We recorded 3,218 interactions before the interventions and 7,570 interactions after the interventions began. Using regression analysis accounting for the maximum number of potential interactions if all staff had worn beacons on a given day, there was a 1% decline in the number of interactions per possible interactions in the postintervention period (incident rate ratio, 0.99; 95% confidence interval, 0.98-1.00; P = .02) with fewer interactions occurring at nursing stations, in workrooms and during morning rounds. CONCLUSIONS: Using quantitative data from wearable proximity beacons, we found an overall small decline in interactions within 6 feet between HCWs in a busy intensive care unit after a multifaceted bundle of interventions was implemented to improve physical distancing.

The case for wearable proximity devices to inform physical distancing among healthcare workers.

OBJECTIVE: Despite the importance of physical distancing in reducing SARS-CoV-2 transmission, this practice is challenging in healthcare. We piloted use of wearable proximity beacons among healthcare workers (HCWs) in an inpatient unit to highlight considerations for future use of trackable technologies in healthcare settings. MATERIALS AND METHODS: We performed a feasibility pilot study in a non-COVID adult medical unit from September 28 to October 28, 2020. HCWs wore wearable proximity beacons, and interactions defined as <6 feet for ≥5 s were recorded. Validation was performed using direct observations. RESULTS: A total of 6172 close proximity interactions were recorded, and with the removal of 2033 false-positive interactions, 4139 remained. The highest proportion of interactions occurred between 7:00 Am-9:00 Am. Direct observations of HCWs substantiated these findings. DISCUSSION: This pilot study showed that wearable beacons can be used to monitor and quantify HCW interactions in inpatient settings. CONCLUSION: Technology can be used to track HCW physical distancing.

Examining the effect of wound cleansing on the microbiome of venous stasis ulcers.

Common treatment for venous leg wounds includes topical wound dressings with compression. At each dressing change, wounds are debrided and washed; however, the effect of the washing procedure on the wound microbiome has not been studied. We hypothesized that wound washing may alter the wound microbiome. To characterize microbiome changes with respect to wound washing, swabs from 11 patients with chronic wounds were sampled before and after washing, and patient microbiomes were characterized using 16S rRNA sequencing and culturing. Microbiomes across patient samples prior to washing were typically polymicrobial but varied in the number and type of bacterial genera present. Proteus and Pseudomonas were the dominant genera in the study. We found that washing does not consistently change microbiome diversity but does cause consistent changes in microbiome composition. Specifically, washing caused a decrease in the relative abundance of the most highly represented genera in each patient cluster. The finding that venous leg ulcer wound washing, a standard of care therapy, can induce changes in the wound microbiome is novel and could be potentially informative for future guided therapy strategies.