Background: Healthcare facilities have experienced many challenges during the COVID-19 pandemic, including limited personal protective equipment (PPE) supplies. Healthcare personnel (HCP) rely on PPE, vaccines, and other infection control measures to prevent SARS-CoV-2 infections. We describe PPE concerns reported by HCP who had close contact with COVID-19 patients in the workplace and tested positive for SARS-CoV-2. Method: The CDC collaborated with Emerging Infections Program (EIP) sites in 10 states to conduct surveillance for SARS-CoV-2 infections in HCP. EIP staff interviewed HCP with positive SARS-CoV-2 viral tests (ie, cases) to collect data on demographics, healthcare roles, exposures, PPE use, and concerns about their PPE use during COVID-19 patient care in the 14 days before the HCP’s SARS-CoV-2 positive test. PPE concerns were qualitatively coded as being related to supply (eg, low quality, shortages); use (eg, extended use, reuse, lack of fit test); or facility policy (eg, lack of guidance). We calculated and compared the percentages of cases reporting each concern type during the initial phase of the pandemic (April–May 2020), during the first US peak of daily COVID-19 cases (June–August 2020), and during the second US peak (September 2020–January 2021). We compared percentages using mid-P or Fisher exact tests (α = 0.05). Results: Among 1,998 HCP cases occurring during April 2020–January 2021 who had close contact with COVID-19 patients, 613 (30.7%) reported ≥1 PPE concern (Table 1). The percentage of cases reporting supply or use concerns was higher during the first peak period than the second peak period (supply concerns: 12.5% vs 7.5%; use concerns: 25.5% vs 18.2%; p Conclusions: Although lower percentages of HCP cases overall reported PPE concerns after the first US peak, our results highlight the importance of developing capacity to produce and distribute PPE during times of increased demand. The difference we observed among selected groups of cases may indicate that PPE access and use were more challenging for some, such as nonphysicians and nursing home HCP. These findings underscore the need to ensure that PPE is accessible and used correctly by HCP for whom use is recommended.

Funding: None

Disclosures: None

Healthcare personnel with severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection were interviewed to describe activities and practices in and outside the workplace. Among 2,625 healthcare personnel, workplace-related factors that may increase infection risk were more common among nursing-home personnel than hospital personnel, whereas selected factors outside the workplace were more common among hospital personnel.

Background: In February 2019, the Colorado Department of Public Health and Environment (CDPHE) identified a cluster of 3 invasive group A Streptococcus (GAS) infections in residents receiving wound care in a long-term care facility (LTCF). An investigation revealed a larger outbreak that extended to nonresidents receiving outpatient wound care at the LTCF. Methods: A case was defined as a positive culture for GAS emm type 82 from an individual with exposure to the LTCF between January and June 2019. Cases were categorized as clinical (symptoms of GAS disease or GAS isolated from a wound or sterile site) or carriage (no symptoms). Carriers were identified via samples collected from throat and skin lesions. Screening occurred in 2 rounds and included residents of affected units followed by screening of all wound-care staff and residents facility-wide. Available isolates were sent for emm type testing and whole-genome sequencing (WGS) at the CDC. CDPHE staff performed infection control observations. Results: We identified 14 cases: 8 clinical and 6 carriage (from 5 residents and 1 staff member). Two patients with invasive GAS died. Of 8 patients with clinical GAS, 6 resided in the facility on or 1 day prior to symptom onset; 2 were not residents but received outpatient therapy at the LTCF. All 8 patients with clinical GAS (100%) and 3 carriers had received wound care. The staff member with emm 82 carriage had provided wound care and occupational therapy to the affected residents and the 2 outpatients. Two additional cases were detected with onset dates following staff member decolonization. Moreover, 13 of the 14 emm 82 isolates were found to be identical by WGS. Infection control observations identified lapses in staff wound care and hand hygiene practices in the residential and outpatient settings of the facility. Conclusions: This investigation details a large GAS outbreak in an LTCF associated with asymptomatic carriage in residents and staff that included patients who had only received care in the outpatient portion of the facility. The outbreak was halted following decolonization of a staff member and improvements in infection control, including in the outpatient setting. Outpatient services, particularly wound care, provided by LTCFs should be considered when investigating LTCF-related GAS cases and outbreaks.

Funding: None

Disclosures: None

Background: With the emergence of antibiotic resistant threats and the need for appropriate antibiotic use, laboratory microbiology information is important to guide clinical decision making in nursing homes, where access to such data can be limited. Susceptibility data are necessary to inform antibiotic selection and to monitor changes in resistance patterns over time. To contribute to existing data that describe antibiotic resistance among nursing home residents, we summarized antibiotic susceptibility data from organisms commonly isolated from urine cultures collected as part of the CDC multistate, Emerging Infections Program (EIP) nursing home prevalence survey. Methods: In 2017, urine culture and antibiotic susceptibility data for selected organisms were retrospectively collected from nursing home residents’ medical records by trained EIP staff. Urine culture results reported as negative (no growth) or contaminated were excluded. Susceptibility results were recorded as susceptible, non-susceptible (resistant or intermediate), or not tested. The pooled mean percentage tested and percentage non-susceptible were calculated for selected antibiotic agents and classes using available data. Susceptibility data were analyzed for organisms with ≥20 isolates. The definition for multidrug-resistance (MDR) was based on the CDC and European Centre for Disease Prevention and Control’s interim standard definitions. Data were analyzed using SAS v 9.4 software. Results: Among 161 participating nursing homes and 15,276 residents, 300 residents (2.0%) had documentation of a urine culture at the time of the survey, and 229 (76.3%) were positive. Escherichia coli, Proteus mirabilis, Klebsiella spp, and Enterococcus spp represented 73.0% of all urine isolates (N = 278). There were 215 (77.3%) isolates with reported susceptibility data (Fig. 1). Of these, data were analyzed for 187 (87.0%) (Fig. 2). All isolates tested for carbapenems were susceptible. Fluoroquinolone non-susceptibility was most prevalent among E. coli (42.9%) and P. mirabilis (55.9%). Among Klebsiella spp, the highest percentages of non-susceptibility were observed for extended-spectrum cephalosporins and folate pathway inhibitors (25.0% each). Glycopeptide non-susceptibility was 10.0% for Enterococcus spp. The percentage of isolates classified as MDR ranged from 10.1% for E. coli to 14.7% for P. mirabilis. Conclusions: Substantial levels of non-susceptibility were observed for nursing home residents’ urine isolates, with 10% to 56% reported as non-susceptible to the antibiotics assessed. Non-susceptibility was highest for fluoroquinolones, an antibiotic class commonly used in nursing homes, and ≥ 10% of selected isolates were MDR. Our findings reinforce the importance of nursing homes using susceptibility data from laboratory service providers to guide antibiotic prescribing and to monitor levels of resistance.

Disclosures: None

Funding: None

Background: With an aging population, increasingly complex care, and frequent re-admissions, prevention of healthcare-associated infections (HAIs) in nursing homes (NHs) is a federal priority. However, few contemporary sources of HAI data exist to inform surveillance, prevention, and policy. Prevalence surveys (PSs) are an efficient approach to generating data to measure the burden and describe the types of HAI. In 2017, the Centers for Disease Control and Prevention (CDC) performed its first large-scale HAI PS through the Emerging Infections Program (EIP) to measure the prevalence and describe the epidemiology of HAI in NH residents. Methods: NHs from several states (CA, CO, CT, GA, MD, MN, NM, NY, OR, & TN) were randomly selected and asked to participate in a 1-day HAI PS between April and October 2017; participation was voluntary. EIP staff reviewed available medical records for NH residents present on the survey date to collect demographic and basic clinical information and infection signs and symptoms. HAIs with onset on or after NH day 3 were identified using revised McGeer infection definitions applied to data collected by EIP staff and were reported to the CDC through a web-based system. Data were reviewed by CDC staff for potential errors and to validate HAI classifications prior to analysis. HAI prevalence, number of residents with >1 HAI per number of surveyed residents ×100, and 95% CIs were calculated overall (pooled mean) and for selected resident characteristics. Data were analyzed using SAS v9.4 software. Results: Among 15,296 residents in 161 NHs, 358 residents with 375 HAIs were identified. The most common HAI sites were skin (32%), respiratory tract (29%), and urinary tract (20%). Cellulitis, soft-tissue or wound infection, symptomatic UTI, and cold or pharyngitis were the most common individual HAIs (Fig. 1). Overall HAI prevalence was 2.3 per 100 residents (95% CI, 2.1–2.6); at the NH level, the median HAI prevalence was 1.8 and ranged from 0 to 14.3 (interquartile range, 0–3.1). At the resident level (Fig. 2), HAI prevalence was significantly higher in persons admitted for postacute care with diabetes, with a pressure ulcer, receiving wound care, or with a device. Conclusions: In this large-scale survey, 1 in 43 NH residents had an HAI on a given day. Three HAI types comprised >80% of infections. In addition to identifying characteristics that place residents at higher risk for HAIs, these findings provide important data on HAI epidemiology in NHs that can be used to expand HAI surveillance and inform prevention policies and practices.

Funding: None

Disclosures: None

Background: Healthcare-associated group A Streptococcus (GAS) infections can cause severe morbidity and death. Invasive GAS is a reportable condition in the 5-county metropolitan area of Denver, Colorado. Prior to August 2018, methodology to identify long-term care facility (LTCF) residency among reported GAS cases was accomplished by reviewing addresses reported electronically, and identification of postsurgical cases and outbreaks relied on reporting by healthcare facilities. We evaluated whether the use of a health information exchange (HIE) to identify healthcare exposures improved our ability to detect and rapidly respond to these events. Methods: In August 2018, we implemented a review of health records available in the HIE accessible by the Colorado Department of Public Health and Environment for all incoming reports of GAS for selected healthcare exposures: LTCF residency, surgery, delivery, wound care, and other relevant exposures. We defined an LTCF-related case as GAS in a current or recent resident (ie, in the 14 days prior to the positive culture) of an LTCF. Postpartum and postsurgical cases were defined as GAS isolated from a sterile site or wound during the inpatient stay or within 7 days of discharge following a delivery or surgical procedure. Outbreaks in each of these settings were defined as 2 or more cases within a 3-month period. We compared the number of cases and outbreaks identified in each category during a 1-year period before and after implementation of the use of the HIE in the case ascertainment process. Results: During August 2017 through July 2018, prior to implementation of the HIE process, we detected 45 LTCF cases and conducted outbreak investigations in 9 facilities. Moreover, 1 postsurgical case and 1 postpartum outbreak were reported by healthcare facilities; none were detected via surveillance. During August 2018 through July 2019, after the implementation of HIE process, we identified 70 LTCF cases and conducted outbreak investigations in 13 LTCFs. We detected 5 postsurgical cases and 3 postpartum cases, which resulted in 2 outbreak investigations. Conclusions: Enhanced GAS surveillance through use of a HIE resulted in detection of more healthcare-associated GAS infections and outbreaks. Timely identification of healthcare-associated GAS infections can allow for prompt response to outbreaks and promotion of proper infection control practices to prevent further cases. Jurisdictions in which GAS is a reportable condition should consider the use of HIEs as part of routine surveillance to identify GAS outbreaks in high-risk settings. HIEs should be made available to public health agencies for case ascertainment and outbreak identification.

Funding: None

Disclosures: None

Background: Antibiotics are among the most commonly prescribed drugs in nursing homes; urinary tract infections (UTIs) are a frequent indication. Although there is no gold standard for the diagnosis of UTIs, various criteria have been developed to inform and standardize nursing home prescribing decisions, with the goal of reducing unnecessary antibiotic prescribing. Using different published criteria designed to guide decisions on initiating treatment of UTIs (ie, symptomatic, catheter-associated, and uncomplicated cystitis), our objective was to assess the appropriateness of antibiotic prescribing among NH residents. Methods: In 2017, the CDC Emerging Infections Program (EIP) performed a prevalence survey of healthcare-associated infections and antibiotic use in 161 nursing homes from 10 states: California, Colorado, Connecticut, Georgia, Maryland, Minnesota, New Mexico, New York, Oregon, and Tennessee. EIP staff reviewed resident medical records to collect demographic and clinical information, infection signs, symptoms, and diagnostic testing documented on the day an antibiotic was initiated and 6 days prior. We applied 4 criteria to determine whether initiation of treatment for UTI was supported: (1) the Loeb minimum clinical criteria (Loeb); (2) the Suspected UTI Situation, Background, Assessment, and Recommendation tool (UTI SBAR tool); (3) adaptation of Infectious Diseases Society of America UTI treatment guidelines for nursing home residents (Crnich & Drinka); and (4) diagnostic criteria for uncomplicated cystitis (cystitis consensus) (Fig. 1). We calculated the percentage of residents for whom initiating UTI treatment was appropriate by these criteria. Results: Of 248 residents for whom UTI treatment was initiated in the nursing home, the median age was 79 years [IQR, 19], 63% were female, and 35% were admitted for postacute care. There was substantial variability in the percentage of residents with antibiotic initiation classified as appropriate by each of the criteria, ranging from 8% for the cystitis consensus, to 27% for Loeb, to 33% for the UTI SBAR tool, to 51% for Crnich and Drinka (Fig. 2). Conclusions: Appropriate initiation of UTI treatment among nursing home residents remained low regardless of criteria used. At best only half of antibiotic treatment met published prescribing criteria. Although insufficient documentation of infection signs, symptoms and testing may have contributed to the low percentages observed, adequate documentation in the medical record to support prescribing should be standard practice, as outlined in the CDC Core Elements of Antibiotic Stewardship for nursing homes. Standardized UTI prescribing criteria should be incorporated into nursing home stewardship activities to improve the assessment and documentation of symptomatic UTI and to reduce inappropriate antibiotic use.

Funding: None

Disclosures: None

Background: Candidemia is associated with high morbidity and mortality. Although risk factors for candidemia and other bloodstream infections (BSIs) overlap, little is known about patient characteristics and the outcomes of polymicrobial infections. We used data from the CDC Emerging Infections Program (EIP) candidemia surveillance to describe polymicrobial candidemia infections and to assess clinical differences compared with Candida-only BSIs. Methods: During January 2017–December 2017 active, population-based candidemia surveillance was conducted in 45 counties in 9 states covering ~6% of the US population through the CDC EIP. A case was defined as a blood culture with Candida spp in a surveillance-area resident; a blood culture >30 days from the initial culture was considered a second case. Demographic and clinical characteristics were abstracted from medical records by trained EIP staff. We examined characteristics of polymicrobial cases, in which Candida and ≥1 non-Candida organism were isolated from a blood specimen on the same day, and compared these to Candida-only cases using logistic regression or t tests using SAS v 9.4 software. Results: Of the 1,221 candidemia cases identified during 2017, 215 (10.2%) were polymicrobial. Among polymicrobial cases, 50 (23%) involved ≥3 organisms. The most common non-Candida organisms were Staphylococcus epidermidis (n = 30, 14%), Enterococcus faecalis (n = 26, 12%), Enterococcus faecium (n = 17, 8%), and Staphylococcus aureus, Klebsiella pneumoniae, and Stenotrophomonas maltophilia (n = 15 each, 7%). Patients with polymicrobial cases were significantly younger than those with Candida-only cases (54.3 vs 60.7 years; P < .0004). Healthcare exposures commonly associated with candidemia like total parenteral nutrition (relative risk [RR], 0.82; 95% CI, 0.60–1.13) and surgery (RR, 0.99; 95% CI, 0.77–1.29) were similar between the 2 groups. Polymicrobial cases had shorter median time from admission to positive culture (1 vs 4 days, P < .001), were more commonly associated with injection drug use (RR, 1.95; 95% CI, 1.46–2.61), and were more likely to be community onset-healthcare associated (RR, 1.91; 95% CI, 1.50–2.44). Polymicrobial cases were associated with shorter hospitalization (14 vs 17 days; P = .031), less ICU care (RR, 0.7; 95% CI, 0.51–0.83), and lower mortality (RR, 0.7; 95% CI, 0.50–0.92). Conclusions: One in 10 candidemia cases were polymicrobial, with nearly one-quarter of those involving ≥3 organisms. Lower mortality among polymicrobial cases is surprising but may reflect the younger age and lower severity of infection of this population. Greater injection drug use, central venous catheter use, and long-term care exposures among polymicrobial cases suggest that injection or catheter practices play a role in these infections and may guide prevention opportunities.

Funding: None

Disclosures: None

Background: Carbapenem-resistant Acinetobacter baumannii (CRAB) is a serious threat to patient safety due to limited treatment options and propensity to spread in healthcare settings. Using Emerging Infections Program (EIP) data, we describe changes in CRAB incidence and epidemiology. Methods: During January 2012 to December 2018, 9 sites (Colorado, Connecticut, Georgia, Maryland, Minnesota, New Mexico, New York, Oregon, and Tennessee) participated in active laboratory- and population-based surveillance. An incident case was defined as the first isolation of A. baumannii complex, in a 30-day period, resistant to ≥1 carbapenem (excluding ertapenem) from a normally sterile site or urine of a surveillance area resident. Cases were considered hospital-onset (HO) if the culture was collected >3 days after hospital admission; all others were community-onset (CO). Cases were classified as device-associated (DA) if the patient had 1 or more medical devices (ie, urinary catheter, central venous catheter (CVC), endotracheal/nasotracheal tube, tracheostomy, or another indwelling device) present in the 2 days prior to culture collection. Temporal trends were estimated using generalized linear models adjusted for age, race, sex, and EIP site. Results: Overall, 984 incident CRAB cases were identified, representing 849 patients. Among these patients, 291 (34%) were women, 510 (61%) were nonwhite, and the median age was 62 years (mean, 59; range, 0–102). Among the cases, 226 (23%) were HO; 758 (77%) were CO; and 793 (81%) were DA. Overall incidence rates in 2012 and 2018 were 1.58 (95% CI, 1.29–1.90) and 0.60 (95% CI, 0.40–0.67) per 100,000 population, respectively. There was a 15% annual decrease in incidence (adjusted rate ratio [aRR] 0.85; 95% CI: 0.82-0.88, P < .0001). Decreases were observed among sterile site (aRR 0.88; 95% CI, 0.84–0.93) and urine cases (aRR 0.83; 95% CI, 0.80–0.87). Annual decreases occurred for HO cases (aRR, 0.78; 95% CI, 0.73–0.85) and CO cases (aRR, 0.86; 95% CI, 0.83–0.9). The DA cases decreased 16% annually overall (aRR, 0.84; 95% CI, 0.81–0.88). Decreases among cases in patients with CVC (aRR, 0.85; 95% CI, 0.80–0.90) and urinary catheters (aRR, 0.84; 95% CI, 0.80–0.88) were smaller than what was seen in patients with other indwelling devices (aRR, 0.81; 95% CI, 0.77–0.86). Discussion: Overall, from 2012 to 2018, the incidence of CRAB decreased >60%. Decreases were observed in all case groups, regardless of source, infection onset location, or types of devices. Smaller annual decreases in rates of CO-CRAB than HO-CRAB suggest that there may be opportunities to accelerate prevention outside the hospital to further reduce the incidence of these difficult-to-treat infections.

Funding: None

Disclosures: None

Health data have enormous potential to transform healthcare, health service design, research, and individual health management. However, health data collected by institutions tend to remain siloed within those institutions limiting access by other services, individuals or researchers. Further, health data generated outside health services (e.g., from wearable devices) may not be easily accessible or useable by individuals or connected to other parts of the health system. There are ongoing tensions between data protection and the use of data for the public good (e.g., research). Concurrently, there are a number of data platforms that provide ways to disrupt these traditional health data siloes, giving greater control to individuals and communities. Through four case studies, this paper explores platforms providing new ways for health data to be used for personal data sharing, self-health management, research, and clinical care. The case-studies include data platforms: PatientsLikeMe, Open Humans, Health Record Banks, and unforgettable.me. These are explored with regard to what they mean for data access, data control, and data governance. The case studies provide insight into a shift from institutional to individual data stewardship. Looking at emerging data governance models, such as data trusts and data commons, points to collective control over health data as an emerging approach to issues of data control. These shifts pose challenges as to how “traditional” health services make use of data collected on these platforms. Further, it raises broader policy questions regarding how to decide what public good data should be put towards.

Acute change in mental status (ACMS), defined by the Confusion Assessment Method, is used to identify infections in nursing home residents. A medical record review revealed that none of 15,276 residents had an ACMS documented. Using the revised McGeer criteria with a possible ACMS definition, we identified 296 residents and 21 additional infections. The use of a possible ACMS definition should be considered for retrospective nursing home infection surveillance.

Optical positions from the SuperCOSMOS Sky Survey have been compared in detail with accurate radio positions that define the second realisation of the International Celestial Reference Frame (ICRF2). The comparison was limited to the IIIaJ plates from the UK/AAO and Oschin (Palomar) Schmidt telescopes. A total of 1 373 ICRF2 sources was used, with the sample restricted to stellar objects brighter than BJ = 20 and Galactic latitudes |b| > 10°. Position differences showed an rms scatter of $0.16\text{ arcsec}$ in right ascension and declination. While overall systematic offsets were < $0.1\text{ arcsec}$ in each hemisphere, both the systematics and scatter were greater in the north.