Infection control response to an outbreak of OXA-23 carbapenemase-producing carbapenem-resistant Acinetobacter baumannii in a skilled nursing facility in Utah.

BACKGROUND: Antibiotic-resistant Acinetobacter species are a growing public health threat, yet are not nationally notifiable, and most states do not mandate reporting. Additionally, there are no standardized methods to detect Acinetobacter species colonization. METHODS: An outbreak of carbapenem-resistant Acinetobacter baumannii (CRAB) was identified at a Utah ventilator unit in a skilled nursing facility. An investigation was conducted to identify transmission modes in order to control spread of CRAB. Culture-based methods were used to identify patient colonization and environmental contamination in the facility. RESULTS: Of the 47 patients screened, OXA-23-producing CRAB were detected in 10 patients (21%), with 7 patients (15%) having been transferred from out-of-state facilities. Of patients who screened positive, 60% did not exhibit any signs or symptoms of active infection by chart review. A total of 38 environmental samples were collected and CRAB was recovered from 37% of those samples. Whole genome sequencing analyses of patient and environmental isolates suggested repeated CRAB introduction into the facility and highlighted the role of shared equipment in transmission. CONCLUSIONS: The investigation demonstrated this ventilated skilled nursing facility was an important reservoir for CRAB in the community and highlights the need for improved surveillance, strengthened infection control and inter-facility communication within and across states.

Operating room air delivery design to protect patient and surgical site results in particles released at surgical table having greater concentration along walls of the room than at the instrument tray.

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, recommendations have included that personnel not involved in procedures releasing airborne contaminants reduce their exposure by moving >2 m away. We tested whether air particle concentrations in operating rooms (ORs) are greater in the periphery, downstream from the supply airflow. METHODS: We analyzed data from 15 mock surgical procedures performed in 3 ORs. Two ORs were modern, one with a single large diffuser system above the surgical table, and the other using a multiple diffuser array design. An air particle counting unit was located on the instrument table, another adjacent to an air return grille. RESULTS: Concentrations of air particles were greater at return grille than instrument table for the single large diffuser at 26 air exchanges per hour, and the multiple diffuser array at both 26 and 20 air exchanges per hour (all P ≤ .0044), including during electrocautery (all P ≤ .0072). The ratios of concentrations, return grille versus instrument table, were greater during electrocautery for 0.5 to 1.0-micron particles and 1.0 to 5.0-micron particles (both P < .0001). CONCLUSIONS: Modern OR airflow systems are so effective at protecting the surgical field and team from airborne particles emitted during surgery that concentrations of particles released at the OR table are greater at the OR walls than near the center of the room.

Research ethics in a pandemic: considerations for the use of research infrastructure and resources for public health activities.

The number and size of existing research studies with massive databases and biosample repositories that could be leveraged for public health response against SARS-CoV-2 (or other infectious disease pathogens) are unparalleled in history. What risks are posed by coopting research infrastructure-not just data and samples but also participant recruitment and contact networks, communications, and coordination functions-for public health activities? The case of the Seattle Flu Study highlights the general challenges associated with utilizing research infrastructure for public health response, including the legal and ethical considerations for research data use, the return of the results of public health activities relying upon research resources to unwitting research participants, and the possible impacts of public health reporting mandates on future research participation. While research, including public health research, is essential during a pandemic, careful consideration should be given to distinguishing and balancing the ethical mandates of public health activities against the existing ethical responsibilities of biomedical researchers.

Health, housing, and 'direct threats' during a pandemic.

The COVID-19 pandemic brought into stark relief the intimate nexus between health and housing. This extraordinary infectious disease outbreak combined with the astounding lack of a clear, coordinated, prompt, and effective public health response in the U.S. created conditions and introduced practical challenges that left many disoriented-not only health care providers but also housing providers. Innumerable issues are worth examination, such as implications of moratoria on evictions and foreclosures, force majeure contract clauses, insurability of pandemic-related damages and disruptions, holdover tenancies and delayed occupancies, and possible abatement of rent or homeowner/condominium association dues in light of closed common facilities (such as fitness areas) or reduced benefits to be enjoyed with residential property; however, this article focuses on fair housing law and the ``direct threat'' exemption; finds it unlikely that COVID-19 is a disability, likely that the ``direct threat'' defense is available, and both determinations to be case-specific inquiries dependent upon rapidly-changing scientific understanding of this disease. By highlighting adequate housing as a human right for which the government has primary responsibility for ensuring its achievement, this article underscores the importance of finding a holistic solution to public health and housing problems before the next public health emergency arises.

PEEP/ FIO2 ARDSNet Scale Grouping of a Single Ventilator for Two Patients: Modeling Tidal Volume Response.

BACKGROUND: The COVID-19 pandemic is creating ventilator shortages in many countries that is sparking a conversation about placing multiple patients on a single ventilator. However, on March 26, 2020, six leading medical organizations released a joint statement warning clinicians that attempting this technique could lead to poor outcomes and high mortality. Nevertheless, hospitals around the United States and abroad are considering this technique out of desperation (eg, New York), but there is little data to guide their approach. The overall objective of this study is to utilize a computational model of mechanically ventilated lungs to assess how patient-specific lung mechanics and ventilator settings impact lung tidal volume (VT). METHODS: We developed a lumped-parameter computational model of multiple patients connected to a shared ventilator and validated it against a similar experimental study. We used this model to evaluate how patient-specific lung compliance and resistance would impact VT under 4 ventilator settings of pressure control level, PEEP, breathing frequency, and inspiratory:expiratory ratio. RESULTS: Our computational model predicts VT within 10% of experimental measurements. Using this model to perform a parametric study, we provide proof-of-concept for an algorithm to better match patients in different hypothetical scenarios of a single ventilator shared by > 1 patient. CONCLUSIONS: Assigning patients to preset ventilators based on their required level of support on the lower PEEP/higher [Formula: see text] scale of the National Institute of Health's National Heart, Lung, and Blood Institute ARDS Clinical Network (ARDSNet), secondary to lung mechanics, could be used to overcome some of the legitimate concerns of placing multiple patients on a single ventilator. We emphasize that our results are currently based on a computational model that has not been validated against any preclinical or clinical data. Therefore, clinicians considering this approach should not look to our study as an exact estimate of predicted patient VT values.