Background: The phenomena of emerging infectious diseases accelerating once they reach healthcare facilities have been well documented. Outbreaks of MERS-CoV, SARS-CoV, and COVID-19 have led to in-hospital transmission where the initial patient infects healthcare workers, patients, visitors, etc., with infection control policies unable to curtail the spread early on. We refer to this phenomenon as nosocomial amplification. Nosocomial amplification causes an undue burden on a hospital that’s already strained from the pandemic. We aimed to understand which hospital-level parameters impact the community most and vice versa. Methods: We adapted an SEIR compartmental model to have two interconnected units, a community unit and a hospital special care unit, to determine the number of COVID-19 acquisitions in each of them over a hypothetical year. The model was stochastically simulated using Gillespie’s Direct Method for 1000 iterations. A parameter sensitivity analysis assessed the effects each parameter had on the model. The original values of all parameters were allowed to vary +/- 50%. The number of simulation acquisitions was normalized as a percent change from the original model’s mean acquisition. Results: Our analysis found that parameters impacting the community had a disproportionate impact on COVID-19 acquisitions in the hospital as compared to the special care unit, as did the parameters governing the level of asymptomatic transmission. Transmission between healthcare workers facilitated within-hospital transmission even when strict patient-based cohorting and testing were in place. Extensive community-level transmission was also found to readily overwhelm hospital-level infection control at realistic levels of effectiveness and compliance. Conclusion: These findings illustrate that hospitals and the community are tightly linked systems. Hospitals may reintroduce infection into the community that might have contained or mitigated ongoing outbreaks or introduce the disease into a disease-free population; community transmission puts tremendous pressure on infection control. In the future, we can model policies to curb an existing COVID-19 outbreak or subsequent outbreaks to avoid or minimize nosocomial amplification, thus improving the disproportionate burdens on the healthcare system.

Understanding the impact of mpox-related hospitalizations for medical versus infection control indications in New York City Background: New York City (NYC) accounted for 15-20% of new mpox infections at the peak of the 2022-2023 United States outbreak. Globally, 8% of mpox patients required hospitalization. We investigated the proportion of mpox hospitalizations for medical versus infection control indications at two large healthcare systems in the New York metropolitan area. Methods: We included all patients admitted to NYU Langone Health or NYC Health + Hospitals for laboratory-confirmed mpox between May 1, 2022, and April 28, 2023. We analyzed demographic information, reasons for hospitalization, length of stay, number and type of co-infections, healthcare encounters, complications, and treatments received. Results: Sixty-five patients were hospitalized for mpox, with 8 (12%) admitted primarily for infection control isolation (Table 1). Median age was 35 years (IQR=31-40), 69% were cisgender men, and 38% were Black. Those hospitalized primarily for isolation were more likely to reside in a homeless shelter (50% vs. 9%, p < 0 .01) and less likely to have a private residence (25% vs. 81%, p < 0 .01) than those hospitalized for medical indications. Those hospitalized for medical indications were more likely to have HIV (63% vs. 25%, p=0.04), secondary bacterial infections (67% vs. 25%, p=0.02), and to receive antibiotics (82% vs. 25%, p < 0 .01) (Tables 2 and 3). There was no significant difference in median cumulative length of stay per patient (p=0.69) between those hospitalized for medical versus isolation purposes. Most admissions for medical indications were for soft tissue superinfection (40%), severe pharyngitis and/or proctitis (28%) and pain management (20%). There was no significant difference in the proportion of tecovirimat receipt (65% vs. 38%, p=0.14) between those hospitalized for medical versus isolation purposes. Conclusion: Infection control isolation accounted for a significant proportion (12%) of mpox hospitalizations and was associated with a similar median length of stay per patient as hospitalization for medical indications. Our small cohort limits statistical power for comparison between groups. However, our findings argue for increased community-based isolation capacity. This may reduce unnecessary hospitalizations during future outbreaks, particularly amongst unsheltered individuals or those living in congregate settings.

Disclosure: Madeline DiLorenzo: Stocks - Abbvie, Amgen Inc., Becton Dickinson, Biogen Inc., Bristol Myers and Squibb, CVS Health, Davita Inc., Elevance Health, Gilead, Henry Schein, Hologic Inc., Humana Inc., Jazz Pharmaceuticals, Laboratory Corp, Merck and Co., Quest Diagnostics, ResMed Inc., Teladoc Health, Vertex Pharmaceuticals, West Pharmaceuticals

Background: In September 2022, UNC Hospitals was awarded a Regional Emerging Special Pathogens Treatment Center (RESPTC) grant by the U.S. Department of Health and Human Services Administration for Strategic Preparedness and Response (ASPR) to care for up to two patients with viral hemorrhagic fever, or similar pathogen, and up to ten patients with novel respiratory pathogens. Intensive infection prevention efforts and timely multidisciplinary commitment was required to develop the Space, Strategy, Staff, and Stuff needed to care for patients with a special pathogen. Methods: Multiple space needs assessments were undertaken to acquire spaces for the care of patients, simulation training, and a dedicated laboratory. Strategies for developing the response plan required collaboration with hospital executives, nursing leadership, public health leaders, and regional partners. Staff were recruited across various disciplines to join the response team and were provided hands-on skills training which was assessed by post-training surveys. Specialized ‘stuff’ (i.e., PPE, training equipment, and waste management devices) were researched and procured for use by the team. Results: Patient care and dedicated laboratory space was identified within existing infrastructure, and renovation plans were developed to adapt the space for these specialized activities. A waste management plan that benefits the hospital for routine waste and allows for Category A waste management was approved. Fifty-three staff members were recruited from 3 main disciplines (RNs, MDs, Paramedics), and across numerous settings (Medicine Acute Care & ICU, Pediatric ICU & Stepdown, Air Care/Transport, Burn ICU, Surgery Stepdown, Emergency Medicine, Infection Prevention, Infectious Disease) were trained during five 4-hour training sessions, culminating in an exercise involving transporting a rule–out Ebola patient to the hospital’s special pathogens unit. Post-training evaluations demonstrated a very high level of confidence (‘strongly agree’) in staffs’ knowledge about the RESPTC site (92.3%), special pathogens (80.8%), collaboration needed for managing patient care (80.8%), and in their comfort with special PPE donning and doffing (73.1%). Conclusions: Using a systematic approach to develop Space, Strategy, Staff, and Stuff, a large academic hospital readied itself to become a new RESPTC site. Key lessons learned include the importance of a multidisciplinary response team; local, state, and regional coordination for care planning and delivery; and early community partnership development. Logistical infrastructure and waste management challenges continue to require partnership with hospital leadership to optimize workflows and patient care. Holistic decision-making around infrastructure has led to changes that benefit all hospital patients and offer efficiencies to

Disclosure: William Fischer: Consultant - Roche, Merck, Inhalon Biopharma; Speaker for ACGME - IMG. David J Weber: Consultant on vaccines: Pfizer; DSMB chair: GSK; Consultant on disinfection: BD, GAMA, PDI, Germitec

Background: Thorough cleaning and disinfection of high-touch surface areas in hospital inpatient rooms remain vital parts of effective strategies in reducing hospital-acquired infections (HAIs). Currently, Methodist Specialty & Transplant Hospital (MHST) inconsistently utilizes fluorescent marking for terminal cleaning validation. Without quantitative results, it’s difficult to measure the effectiveness of cleaning. To ensure MHST is maintaining a safe and clean environment for patients & staff, MHST implemented a comprehensive cleaning verification program to include adenosine triphosphate (ATP) technology. We aimed to establish the program with baseline readings, and an overall weekly passing score of 95% for all tested inpatient rooms. Methods: To achieve sustained improvement, we needed to monitor, educate, and have periodic performance feedback to individuals and stakeholders. Key stakeholders (IP, EVS, Operations Leadership, Nursing Leadership representative) were identified, and a weekly meeting was established to discuss the planning and implementation of the ATP program. Some key actions included: standardization of brand of luminometer- device to measure ATP for microbial contamination; establishment of 16 high surface touch points to be tested; partnership with IT to create a database & dashboard for ATP results & data analysis; training of ATP device to all personnel who will be utilizing ATP device; establishment of a threshold for a “pass” clean (relative light unit [RLU] less than or equal to 45). Summary of Results: After baseline testing, the average weekly pass score met goal at 95 percent for all tested rooms. The bedside table located on the 2W floor was the location that failed the most (3 instances). Conclusions: Our program implementation project aimed to improve terminal cleaning validation utilizing ATP technology in inpatient rooms, was successfully implemented. Equipped with quantitative results, the MHST team, was able to verify cleaning quickly and efficiently without any confusion, as it may have been with the previous verification method of fluorescent marking. The partnership between Infection Prevention (IP) & Environmental Services (EVS) was crucial in the implementation of this process improvement- from participating in training together to understanding and sharing ATP pass/fail score data.

Background: Candida auris (CA) is an urgent threat per Centers for Disease Control and Prevention with rapidly increasing cases across the US. Patient rooms recontaminate with CA within hours after daily cleaning due to skin shedding, persistence on environmental surfaces and resistance to commonly used disinfectants. Continuous dry hydrogen peroxide (cDHP) is a novel environmental technology augmenting daily room disinfection. cDHP reduces CA organism counts based on environmental cultures. Adenosine triphosphatase (ATPase) testing offers rapid results to monitor surface cleanliness. ATPase Testing Protocol: Upon identification of CA, cDHP was activated in the patient’s room. ATPase surface testing was performed in rooms of CA infected inpatients and nearby control rooms of inpatients without CA and thus no cDHP. Group A surfaces near the patient were nurse call handheld devices and/or bed rail. Group B surfaces were horizontal counter and/or computer keyboard, located >3 feet away from the patient. ATPase testing was to occur within one hour of daily room disinfection for CA patient Day0 (day of cDHP activation), Day1, Day7 and Day14 and controls. Daily room disinfection using quaternary disinfectants was replaced with EPA Class P chemicals upon CA identification. Nursing spot disinfects with Class P ready to use disinfectant wipes in all rooms. Results: Testing occurred among 13 CA and 22 control patients in 5 hospitals. In Table 1, pass rates are displayed by cumulative (Day0+1+7+14) test days for surfaces and patient room groups. Analysis applied Pearson’s Chi-squared test with Yates’ continuity correction. Conclusions: Surfaces further from the patient in rooms of CA patients exposed to cDHP had higher ATPase pass rates than controls. Surfaces close to the patient have a high ATPase failure rate, regardless of CA or cDHP. Strategies are needed to ensure disinfection occurs on high touch surfaces near patients. cDHP may have value in supplementing room disinfection. Contributing failure factors include surfaces missed for disinfection, delays in timely testing and known limitations with ATPase methods.

Background: Surgical site infections (SSIs) are associated with increased morbidity, monetary loss and mortality. The physical aspects of the operation room (OR) including airflow, humidity, pressure, and particulate counts are essential part of SSI prevention. Humidity control is vital to avoid static electricity buildup.Temperature control helps prevent hypothermia. Limiting OR traffic and door opening are essential to prevent airflow disturbance and minimze particles in OR environment. We have recently studied electronic monitoring of OR traffic and the traffic was higher than what was expected. Our aim was to evaluate our real-life measurement of these OR parameters as part of SSI prevention bundle. Methods: This is a prospective study focused on the OR physical environmental factors as part of operative SSI prevention bundle. The study was conducted for 4 weeks at an academic medical center. The study was conducted in two different generations of OR for neurosurgical and ophthalmologic procedures. We performed direct observation of OR traffic as well as environmental parameters (temperature, humidity, pressure, and particulate count) for the entire length of the procedure. We used both directly measured data as well as automated data generated by facilities. Results: The study showed that temperature, humidity, and pressure wer tightly controlled in the OR. This observation was consistent between manual data and automatically generated data. The OR traffic was not easily monitored by the current automatic data and was measured by direct observation. The correlations between particulate count and OR traffic was strongest for 0.3μm (0.7370, and weakest for 1.0μm ( 0.087). The 5.0μm particulate size had a moderate positive correlation of 0.344, Additionally, shorter procedures had less particulate matter in the OR environment. Automated data were only available in the new ORs but could not predict traffic without automated door monitors. But the automated data could easily portray the temperature, humidity and pressure minute by minute. Conclusion: OR traffic increases the particle count particularly the small size. Other physical aspects of the OR environment were tightly controlled. The ability to automatically monitor OR parameters could be extremely helpful for assuring patient safety as well as reviewing OR factors in SSI cases.

Background: Healthcare-acquired infections (HAIs) continue to be a major challenge. In fact, an increased risk of HAIs has been linked to high-touch surfaces contaminated with multidrug-resistant organisms (MDROs), and enhanced environmental disinfection is linked to reduced HAI rates. Recently, more focus has been placed on emerging disinfection technologies, such as UV light-producing portable device that emits light at a wavelength of 222 nm, which has previously demonstrated germicidal capabilities at short contact times. In this study, we aim i) to evaluate the efficacy of a filtered far-UV-C handheld device (FFUHH) to reduce bacterial loads on high-touch surfaces in clinical workrooms in a cancer center, and ii) to isolate, identify and establish a genetic relationship between these environmental clinically significant pathogens and the ones recovered from patients. Methods: Samples were collected weekly on a rotating schedule over a 24-week period from five high-touch items (dictation device, mouse, armchair, desk, and keyboard) in multiple clinical work rooms on hematologic malignancy and stem cell transplant units. Contact plates for colony count and swabs were collected pre- and post-intervention with the FFUHH on standardized adjacent areas respectively for each surface. The swabs were enriched and cultured on selective media to isolate clinically significant pathogens. Whole genome sequencing (WGS) was then performed on environmental pathogens validated by MALDI-TOF as well as clinical samples collected from patients in the same unit around the time of environmental sample collection. Results: A total of 440 plates, 220 pre- and 220 post-interventions, were collected and analyzed. The highest mean colony count pre-treatment was detected from the armchairs and the lowest for the keyboards. The mean reduction of colony forming units (CFUs) ranged between 53% for the keyboard and 83% for the mouse. The reduction was statistically significant across all surfaces with P values < 0.05, except for the keyboard (Figure 1). We isolated many pathogens of the human microbiota identified by MALDI-TOF such as Micrococcus luteus, S. capitis as well as methicillin-resistant S. epidermidis, S. haemolyticus and S. hominis. We also identified several Candida parapsilosis, Pseudomonas stutzeri, one Listeria grayi and one Acinetobacter baumanni. Finally, WSG allowed us to further characterize an environmental multi-drug resistant S. epidermidis ST5 strain associated with patient bacteremia, and ST16 strains detected on surfaces both pre- and post-FFUHH treatment. Conclusion: The FFUHH effectively reduced the microbial burden on high-touch surfaces in clinical workrooms on hematologic malignancy and stem cell units.

Background: Environmental sampling and detection methods for fungi in healthcare settings are not well-established. We previously refined methods for fungal sampling and detection in a controlled laboratory environment and aimed to validate them in a real-world healthcare setting. Methods: We performed a microbiological analysis of air and surfaces in three inpatient units at a tertiary care center. Surface samples were obtained with foam sponges from 3 locations in patient rooms (Patient bedrails, bathroom floor, HVAC export) and 5 locations in units (HVAC exports 3x, clean linen storage, soiled linen storage). Air samples were taken with an active air sampler directly below HVAC exports. Sponges were processed using the stomacher technique. Samples underwent DNA extraction followed by qPCR with FungiQuant primers targeting the 18S rRNA gene. Amplicons from positive samples were sequenced (NextSeq 1000, 300bp PE) and SmartGene databases were used to interpret sequence data. For comparison to culture methods, samples were also plated onto Sabouraud and HardyCHROM Candida + auris medias. Fungal growth underwent DNA extraction, 18S PCR and Sanger sequencing for genus and species identification. Results: A total of 85 samples were obtained, from 15 patient rooms and three units resulting in 61 surface and 24 air samples. Patients in study rooms had a median age of 53, 9 (60%) were male, and no patients had an invasive fungal infection during their hospital encounter. 44 (53%) and 39 (46%) samples were positive for fungi via qPCR and culture, respectively. Of the 44 positive qPCR samples, microbiome analyses identified at least one fungi to the species, genus and family levels in 43 (98%), 28 (64%), 18 (41%) samples, respectively (Table 1). 114 total isolates were identified of which the most common were Mallassezia restricta (30 [26%]), Malassezia globose (29 [25%]), and Pennicillium paradoxum (4 [4%]). 39 genera were identified of which the most common were Mucor (19 [49%]) and Candida (8 [21%]). Of the 39 culture positive samples, 90 total isolates were recovered. The most common species were Paradendryphiella arenariae (19 [21%]), Aspergillus niger (12 [13%]) and Penicillium commune (12 [13%]). Conclusion: These results demonstrate the presence of diverse fungal species in both air and surface samples across inpatient units. Higher sensitivity was noted utilizing qPCR, however, identified genera and species were markedly different between qPCR and culture methods. Larger studies are needed to assess the efficacy of qPCR for fungal detection in the healthcare environment.

Background: The World Health Organization launched ‘Your 5 moments for hand hygiene’ to identify when healthcare workers should perform hand hygiene to reduce healthcare-associated infections (HAIs). Performing hand hygiene correctly is necessary to decrease pathogen transfer, though little research has assessed the effectiveness of all 5 moments. Methods: Registered nurses (n=42) participated in a standardized, one-hour high-fidelity patient care simulation that were recorded via a head-mounted camera. The simulation involved two patients, each requiring four clinical care tasks (e.g., indwelling Foley catheter insertion, stool sample collection). Transmission data was obtained from the simulations using four genetic variants of bacteriophage λ. Before each simulation, variants were applied to unique locations on two manikins: patient A’s wound, patient A’s stool, patient B’s groin, and patient B’s stool. After each simulation, we sampled the patients, nurse, and high-touch environmental surfaces to determined bacteriophage identity of positive samples. For each moment, hand hygiene performance was the total time the nurse practiced hand hygiene across opportunities over the total recommended time (15 seconds per opportunity). Positive samples were categorized as 1) nurse contamination, 2) patient critical site(s) contamination, 3) high touch surface contamination from the same patient, or 4) high touch surface contamination from the other patient. To compare nurse’s performance of each of the 5 moments, we used a Friedman test and then a Wilcoxon test for pairwise comparisons. To assess the relationship between the four types of transmission outcomes and hand hygiene performance of the 5 moments, we performed linear regressions and calculated 95% confidence intervals by bootstrapping the original cases. Results: Performance of moments 1 (Before patient contact: 9.49%), 4 (After patient contact: 13.11%), and 5 (After contact with patient’s surroundings: 13.66%) were significantly higher than moments 2 (Before clean or aseptic task: 2.72%) and 3 (After bodily fluid exposure: 4.22%; p < 0 .05). Moment 2 perfomance, furthermore, was significantly lower than moment 3 (Figure 1). Only moment 2’s performance was significantly related to transmission; specifically, performance was negatively related to critical site contamination (B= -0.03, CI 95%: -0.06 – -0.01); Table 1. Conclusions: Moment 2performance was the lowest of all 5 moments and was the only moment that demonstrated evidence of relationship with pathogen transmission, specifically critical site contamination. Of all the 5 moments, this moment is most directly related to HAIs. Further research should investigate why moment 2 performance is so low.

Background: Proper hand hygiene is the most important practice to reduce the transmission of infections in healthcare settings. Despite this, healthcare institutions continue to struggle to achieve and maintain high rates of hand hygiene compliance among healthcare workers with some studies estimating national healthcare worker hand hygiene compliance to be approximately 50%. Methods: We conducted an anonymous one-time survey of our Lifespan Hospital System employees to evaluate barriers and facilitators to performing hand hygiene as well as interventions to improve hand hygiene compliance. The survey was designed with guidance from the Consolidated Framework for Implementation Research and input from Lifespan infection prevention staff. Result: Over four weeks 985 (6%) Lifespan employees completed the survey. Figure 1 shows the aggregate results of the first 4 survey questions which focused on hand hygiene infrastructure at Lifespan, including availability of sanitizer, staff to manage hand hygiene supplies, and educational materials/reminders. One significant finding was >70% of respondents reported that they either did not know if their unit/department has a person assigned to replace/monitor hand hygiene supplies, or if so, who that person is. We also asked employees to rate how effective different interventions would be at improving hand hygiene compliance. Figure 2 shows of five proposed interventions, three were rated as either “moderately effective” or “very effective” by >50% of respondents. These included displaying hand hygiene instructions, making hand hygiene data available to employees, and displaying materials/reminders promoting hand hygiene. There were also 977 free-text responses regarding “barriers or facilitators to proper hand hygiene”. Major barriers identified were a lack of staff to monitor and refill supplies, slow replacement of hand hygiene products, lack of sanitizer dispensers and sinks, inconsistency of sink location and dispenser placement, lack of hand hygiene reminders/educational materials, time constraints, skin irritation from sanitizer, and an inability to have dispensers in behavioral health units. Survey responses led us to enhance the following: educational materials and reminders in work areas; staff education; leadership involvement in hand hygiene initiatives; routine auditing and feedback; conveniently placed sanitizer dispensers and sinks at the point of care; and making hand hygiene compliance data readily available to staff. Conclusion: This survey identifies important barriers and facilitators to achieving high rates of hand hygiene compliance among healthcare workers and provides the basis for interventions aimed at improving hand hygiene compliance in a large multicenter academic hospital system.