Background: Remdesivir was granted EUA followed by full FDA approval for treatment of hospitalized COVID-19 patients on October 22, 2020, based on the results from the ACTT1 trial. Remdesivir use was initially restricted to infectious disease (ID) physicians in our hospital with prescription needing formal ID consultation until complete approval. Due to increasing case counts in our hospital, a decision was made to allow intensivists and hospitalists the authorization to prescribe remdesivir in a phased manner. In this retrospective study, we assessed the impact of phased-in prescribing on remdesivir utilization and days of therapy of antimicrobials. Methods: Remdesivir prescribing was streamlined by real-time institutional guidelines developed by a COVID-19 treatment committee constituting ID and other clinicians. Eligibility for remdesivir included positive SARS-CoV-2 PCR test, severe disease defined as persistent hypoxia (<94% oxygen saturation on room air), requiring supplemental oxygen and/or on mechanical ventilation (MV) for <72 hours, and symptom onset of <10 days. We retrospectively reviewed cohorts of 3 periods during which remdesivir was prescribed. In the first cohort A, between October 23, 2020, and November 12, 2020, remdesivir was restricted to ID physicians with formal ID consultation. Cohort B comprised inpatients between November 13, 2020, and December 6, 2020, when hospitalists and intensivists were allowed to prescribe remdesivir through an EMR order set after prior authorization by an ID physician via curbside or telephonic consultation. Cohort C, from December 7, 2020, to December 26, 2020, comprised inpatients with unrestricted prescribing of remdesivir by hospitalists and intensivists. We also evaluated antibiotic use. Results: In cohort A, SARS CoV-2 positivity was 20.3%; 64 inpatients tested positive and 35 patients (54.7%) who met the criteria were prescribed remdesivir after a formal consultation with an ID physician. In cohort B, requiring prior authorization by an ID physician, SARS-CoV-2 positivity rapidly increased to 34%; 193 patients tested positive and 97 patients (50.3%) received remdesivir. In cohort C, during unrestricted access, positivity further increased to 38%; 235 inpatients tested positive and 123 (52.5%) received remdesivir. Remdesivir use remained steady during the 3 phases of gradual de-escalation of restricted prescribing and safe handoff in the context of clear guidelines, as well as ongoing curbside education provided by ID physicians during the second phase. Cohort B demonstrated the best prescribing rates. Antimicrobial prescribing data were also collected during the 3 cohort phases (Figures 1–3). Conclusions: Remdesivir is an expensive antiviral with limited utility and maximum benefit in COVID-19 inpatients who are hypoxic but do not require mechanical ventilation. Stewardship of remdesivir with safe, gradual handoff to inpatient can be achieved without overuse.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Figure 3.

Background: Diversion of resources from infection prevention activities, personal protective equipment supply shortages, conservation (extended use and reuse) or overuse with multiple gown and glove layers, and antimicrobial prescribing changes during the COVID-19 pandemic might increase healthcare-associated infection (HAI) incidence and antimicrobial resistance. We compared the incidences of Clostridioides difficile infection (CDI), methicillin-resistant Staphyloccocus aureus bloodstream infection (MRSA BSI), and vancomycin-resistant enterococci bloodstream infection (VRE BSI) reported by California hospitals during the COVID-19 pandemic with incidence data collected prior to the pandemic. Methods: Using data reported by hospitals to the California Department of Health via the NHSN, we compared incidences in the second and third quarters of 2020 (pandemic) to the second and third quarters of 2019 (before the pandemic). For CDI and MRSA BSI, we compared the standardized infection ratios (SIRs, based on the 2015 national baseline), and we calculated the P values. No adjustment model is available for VRE BSI; thus, we measured incidence via crude incidence rates (infections per 100,000 patient days). We calculated incidence rate ratio (IRR) with 95% CI for VRE BSI. To examine the possible effect of missing data during the pandemic, we performed a sensitivity analysis by excluding all facilities that had incomplete data reporting at any time during either analysis period. Results: Incidence measures and numbers of facilities contributing data in prepandemic and pandemic periods are shown in Table 1. There were no statistically significant changes in SIRs at P = .05 for either MRSA BSI or CDI between the prepandemic and pandemic periods (MRSA BSI P = .17; CDI P = .08). Crude VRE BSI incidence increased during the pandemic compared to the prepandemic period (IRR, 1.40; 95% CI, 1.16–1.70). Excluding facilities with incomplete data had minimal effect. Conclusions: We found insufficient evidence that MRSA BSI or CDI incidence changed in California hospitals during the pandemic relative to the prepandemic period; however, there was a significant increase in the crude incidence of VRE BSI. Next, we will include interrupted time series analyses to assess departure from long-term trends, including a risk-adjusted model for VRE BSI. Additionally, we will evaluate for changes in central-line–associated bloodstream infection incidence and antimicrobial resistance among HAI pathogens.

Funding: No

Disclosures: None

Table 1.

Group Name: The Emory COVID-19 Quality and Clinical Research Collaborative

Background: Patients hospitalized with COVID-19 are at risk of secondary infections—10%–33% develop bacterial pneumonia and 2%–6% develop bloodstream infection (BSI). We conducted a retrospective cohort study to identify the prevalence, microbiology, and outcomes of secondary pneumonias and BSIs in patients hospitalized with COVID-19. Methods: Patients aged ≥18 years with a positive SARS-CoV-2 real-time polymerase chain reaction assay admitted to 4 academic hospitals in Atlanta, Georgia, between February 15 and May 16, 2020, were included. We extracted electronic medical record data through June 16, 2020. Microbiology tests were performed according to standard protocols. Possible ventilator-associated pneumonia (PVAP) was defined according to Centers for Disease Control and Prevention (CDC) criteria. We assessed in-hospital mortality, comparing patients with and without infections using the χ2 test. SAS University Edition software was used for data analyses. Results: In total, 774 patients were included (median age, 62 years; 49.7% female; 66.6% black). In total, 335 patients (43.3%) required intensive care unit (ICU) admission, 238 (30.7%) required mechanical ventilation, and 120 (15.5%) died. Among 238 intubated patients, 65 (27.3%) had a positive respiratory culture, including 15 with multiple potential pathogens, for a total of 84 potential pathogens. The most common organisms were Staphylococcus aureus (29 of 84; 34.5%), Pseudomonas aeruginosa (16 of 84; 19.0%), and Klebsiella spp (14 of 84; 16.7%). Mortality did not differ between intubated patients with and without a positive respiratory culture (41.5% vs 35.3%; P = .37). Also, 5 patients (2.1%) had a CDC-defined PVAP (1.7 PVAPs per 1,000 ventilator days); none of them died. Among 536 (69.3%) nonintubated patients, 2 (0.4%) had a positive Legionella urine antigen and 1 had a positive respiratory culture (for S. aureus). Of 774 patients, 36 (4.7%) had BSI, including 5 with polymicrobial BSI (42 isolates total). Most BSIs (24 of 36; 66.7%) had ICU onset. The most common organisms were S. aureus (7 of 42; 16.7%), Candida spp (7 of 42; 16.7%), and coagulase-negative staphylococci (5 of 42; 11.9%); 12 (28.6%) were gram-negative. The most common source was central-line–associated BSI (17 of 36; 47.2%), followed by skin (6 of 36; 16.7%), lungs (5 of 36; 13.9%), and urine (4 of 36; 11.1%). Mortality was 50% in patients with BSI versus 13.8% without (p < 0.0001). Conclusions: In a large cohort of patients hospitalized with COVID-19, secondary infections were rare: 2% bacterial pneumonia and 5% BSI. The risk factors for these infections (intubation and central lines, respectively) and causative pathogens reflect healthcare delivery and not a COVID-19–specific effect. Clinicians should adhere to standard best practices for preventing and empirically treating secondary infections in patients hospitalized with COVID-19.

Funding: No

Disclosures: None

Background: In their interim infection prevention and control recommendations for the coronavirus disease 2019 (COVID-19) pandemic, the Centers for Disease Control and Prevention (CDC) recommend that healthcare facilities have a plan to identify, investigate, and trace potential COVID-19 exposures. In an academic hospital, the scale of such tracing is substantial, given that medically complex patients can have dozens of staff contacts across multiple locations during an encounter. Furthermore, the family-centered care model employed by pediatric institutions precludes visitor exclusion, further complicating tracing efforts. Despite this complexity, tracing accuracy and timeliness is of paramount importance for exposure management. To address these challenges, our institution developed a contact-tracing system that balanced expert participation with automated tracing tools. Methods: Our institution’s contact-tracing initiative includes positive patients, parents and/or visitors, and staff for the enterprise’s inpatient, procedural, and ambulatory locations at the main campus and 4 satellites. The team consists of 11 staff and is overseen by an infection preventionist. For positive patients and parents and/or visitors, potentially exposed staff are automatically identified via a report that extracts staff details for all encounters occurring during the patient’s infectious period. For positive staff, trained contact tracers call the staff member to determine whether mask and distancing practices could result in others meeting CDC exposure criteria. Any potentially exposed healthcare workers (HCWs) receive an e-mail that details exposure criteria and provides follow-up instructions. These HCWs are also entered into a secure, centralized tracking database that (1) allows infection prevention and occupational health staff to query and identify all epidemiologic links between traced patients, parents and/or visitors, and staff, and (2) initiates staff enrollment in a twice-daily symptom tracking system administered via REDCap. Potentially exposed patients and parents and/or visitors are contacted directly by a hospital representative. The contact tracing team, infection prevention staff, and occupational health staff meet daily to review positive staff cases in the last 24 hours. Results: To date, the team has traced ~1,300 patients, 15 parents and/or visitors, and 700 staff. Since the start of the pandemic, tracing and contact notification for all positive cases has been conducted within 24 hours. Through these proactive tracing efforts and other institutional infection prevention initiatives, the institution only experienced 1 staff cluster (N < 15) and <5 hospital-onset patient cases. Conclusions: Equipping a trained group of contact tracers with automated tracking tools can afford infection prevention and occupational health departments the ability to achieve and sustain timely and accurate contact tracing initiatives throughout a large-scale pandemic response.

Funding: No

Disclosures: None

Background: Prison populations have been disproportionally affected by COVID-19, partly due to challenges related to social distancing. Data on viral transmission dynamics in inpatient prison units remain limited. The Ohio State University Wexner Medical Center (OSUWMC) has a 24-bed inpatient prison unit in collaboration with the Ohio Department of Rehabilitations and Corrections (ODRC). The unit has 5 shared rooms holding 4 patients each and 4 single-patient rooms. Several cases of inpatient transmission of COVID-19 were identified on the inpatient prison unit. Methods: An IRB-approved retrospective chart review was conducted to evaluate inpatient transmission dynamics of hospital-acquired (HCA) COVID-19. All ODRC patients admitted from March 1 to April 24, 2020, were included. Patients assigned to the prison unit during their hospital stay were evaluated for potential HCA COVID-19, defined as a positive SARS-CoV-2 test ≥4 days after admission. Patient characteristics, testing data, symptoms, aerosol-generating procedures (AGPs), and room assignments were reviewed. Healthcare workers (HCWs) and correction officers (COs) working on the unit who tested positive during this period were identified. Results: In total, 142 ODRC patients were admitted during the study period and 89% had a positive SARS-CoV-2 testing prior to or during admission. Also, 61 patients (43%) were assigned to the prison unit. Moreover, 8 patients on the unit met potential HCA COVID-19 definition with 7 linked to 3 distinct clusters. Also, 7 COs had COVID-19 (outside hospital exposure) and 5 HCWs acquired COVID-19 from patient exposure on the unit. In cluster 1, 4 patients admitted to the same room developed HCA COVID-19. A symptomatic index patient not tested on admission given an atypical presentation required CPAP and frequent nebulizer treatments. In cluster 2, 1 patient from cluster 1 was transferred to another room. The new roommate subsequently developed HCA COVID-19. In cluster 3, a symptomatic correctional officer was assigned to 2 patients in a shared room; the patients later developed HCA COVID-19. Conclusions: Three patient clusters of HCA COVID-19 on a prison unit were identified. Aerosol transmission potentially played a role in cluster 1. Inpatient transmission within the unit prompted updated guidance for ODRC admissions, including universal SARS-CoV-2 admission testing, excluding patients requiring AGPs from shared rooms, and preemptive isolation for patients from an ODRC facility experiencing a COVID-19 surge. Universal testing was quickly expanded to all inpatient admissions. HCWs and COs were also linked to inpatient transmission, highlighting the importance of strict infection control practices for patient populations who cannot socially distance.

Funding: No

Disclosures: None

Background: The use of personal protective equipment (PPE) is a critical intervention in preventing the spread of transmission-based infections in healthcare settings. However, contamination of the skin and clothing of healthcare personnel (HCP) frequently occurs during the doffing of PPE. In fact, nearly 40% of HCP make errors while doffing their PPE, causing them to contaminate themselves. PPE monitors are staff that help to promote their colleagues’ safety by guiding them through the PPE donning and doffing processes. With the advent of the COVID-19 pandemic in early 2020, the UNC Medical Center chose to incorporate PPE monitors as part of its comprehensive COVID-19 prevention strategy, using them in inpatient areas (including COVID-19 containment units and all other units with known or suspected SARS-CoV-2–positive patients), procedural areas, and outpatient clinics. Methods: Infection prevention and nursing developed a PPE monitoring team using redeployed staff from outpatient clinics and inpatient areas temporarily closed because of the pandemic. Employee training took place online and included fundamentals of disease transmission, hand hygiene basics, COVID-19 policies and signage, and videos on proper donning and doffing, including coaching tips. The monitors’ first shifts were supervised by experienced monitors to continue in-place training. Employees had competency sheets signed off by a supervisor. Results: The Medical Center’s nursing house supervisors took over management and deployment of the PPE monitoring team, and infection prevention staff continued to train new members. Eventually, as closed clinics and areas reopened and these PPE monitors returned to their regular positions, areas used their own staff to perform the role of PPE monitor. In the fall of 2020, a facility-wide survey was sent to all inpatient staff to assess their perceptions of the Medical Center’s efforts to protect them from acquiring COVID-19. It included a question asking how much staff agreed or disagreed that PPE monitors “play an important role in keeping our staff who care for COVID-19 patients safe.” Of the 626 staff who answered this question, 67.6% agreed or strongly agreed that PPE monitors played an important role in keeping staff safe. Thus far, there has been no direct transmission or clusters of COVID-19 involving HCP in COVID-19 containment units with PPE monitors. Conclusions: PPE monitors are an important part of a comprehensive COVID-19 prevention strategy. In early 2021, the UNC Medical Center posted and hired paid PPE monitor positions to continue this critical work in a sustainable way.

Funding: No

Disclosures: None

Background: The US–Mexico border represents a unique region of the country where antibiotics are more accessible and nonprescription treatment with antibiotics is deeply enculturated. Currently, both the United States and Mexico are experiencing widespread community transmission of SARS-CoV-2, which may have implications for antibiotic seeking and use. The objective of this study was to examine antibiotic seeking behavior as it relates to COVID-19 in the border region relative to the greater US and Mexico populations. Methods: An interdisciplinary team at The University of Arizona developed a survey to assess knowledge, attitudes, and beliefs about antibiotics along the US–Mexico border region (defined as 100 km from the border) and to compare findings from the border region to the broader US and Mexico populations. The team recruited survey participants through Amazon’s MTurk survey platform and through the distribution of recruitment flyers to community partners in Arizona and Mexico border regions from October 2020 to January 2021. Targeted recruitment was 750 through March 2021. We report here on findings from the first round of recruitment (n = 116). These participants were asked whether they had sought out antibiotics specifically as a treatment for COVID-19, as well as their general beliefs and behaviors on self-seeking antibiotics for illness. Results: As of January 24, 2021, we surveyed 116 participants: 82 (70.7%) from the United States and 34 (29.3%) from Mexico. Most participants (71.2%) were aged 25–44 years; 56.9% were male; and 50% reported Hispanic ethnicity. Of these, 13.8% lived within 100 km of the US–Mexico border. Overall, 21.6% of participants reported taking antibiotics to fight COVID-19–like illness. Of these participants, 28% obtained the antibiotics directly from a pharmacy, without a physician prescription, and 16% obtained them from an online vendor. Additionally, 33% of US respondents reported that they would be willing to travel to Mexico to obtain antibiotics if they were too difficult to obtain in the United States. Of these respondents, 55% said they would be willing to travel for >1 hour to obtain antibiotics. Conclusions: Preliminary data suggest that the COVID-19 pandemic will have widespread ramifications on antibiotic seeking behavior and could propagate antibiotic resistance. Targeted intervention strategies in the border region are necessary to mitigate the unique factors that contribute to antibiotic use in this area.

Funding: No

Disclosures: None

Background: As the COVID-19 pandemic continues, special attention is focused on high-risk patients. In this study, we assessed the risk factors for COVID-19 mortality in nursing home patients. Methods: In this retrospective cohort study, we reviewed the electronic medical records of SARS-COV-2 PCR–positive nursing-home patients between March 8 and June 14, 2020. The primary outcome was in-hospital mortality. Risk factors were compared between those who were discharged or died using the Student t test, the Mann-Whitney U test, χ2 analysis, and logistic regression. Results: Among 169 hospitalized nursing-home patients, the case fatality rate was 43.2%. The mean age was 72.3 ± 13.8 years; 92 patients (54.4%) were male; and 112 patients (66.3%) were black. Within the first day of hospitalization, 83 (49%) patients developed fever. On admission, 24 (14.2%) patients were hypotensive. Leukopenia, lymphopenia, and thrombocytopenia were present in 20 (12%), 91 (53%), and 40 (23.7%) patients, respectively. Among the inflammatory markers, elevations in CRP and ferritin levels occurred in 79% and 24%, respectively. Intensive care admission was needed for 40 patients (23.7%). Septic shock occurred in 25 patients (14.8%). Patients over the age of 70 were more likely to die than younger patients (OR, 2.2; 95% CI, 1.2– 4.1; P = .20). Patients with a fever on admission were more likely to die than those who were afebrile (OR, 2.03; 95% CI, 1.08–3.8; P = .03). Also, 66.7% hypotensive patients died compared to 39.3% normotensive patients (OR, 3.1; 95% CI, 1.2–7.7 P = .01). Intubated patients died more often than those not intubated, 78.4% versus 33.3%, respectively (OR=7.3, p < 0.001, CI 3.1, 17.2) Factors significantly associated with death included higher mean qSofa (p < 0.001), higher median Charlson scores (0.02), thrombocytopenia (p = 0.04) and lymphocytopenia (0.04). From multivariable logistic regression, independent factors associated with death were Charlson score (OR=1.2, p=0.05), qSofa (OR=2.0, p=0.004), thrombocytopenia (OR = 3.0, p = 0.01) and BMI less than 25 (OR = 3.5, p=0.002). Conclusions: Our multivariable analysis revealed that patients with a greater burden of comorbidities, lower BMI, higher qSOFA sepsis score, and thrombocytopenia had a higher risk of death, perhaps because of severe infection despite a robust immune response.

Funding: No

Disclosures: None

Background: Significant outbreaks of SARS-CoV-2 infections have occurred in healthcare personnel (HCP). We used an electronic tracking system (ETS) as a tool to link staff cases of COVID-19 in place and time during a COVID-19 outbreak in a community hospital. Methods: We identified SARS-CoV-2 infection cases through surveillance, case investigation and contact tracing, and voluntary testing. For those wearing ETS badges (Centrak), data were reviewed for places occupied by the personnel during their incubation and infectious windows. Contacts beyond 15 minutes in the same location were considered close contacts. Results: Over 6 weeks (August 10–September 14, 2020), 35 HCPs tested positive for SARS-CoV-2 by NAAT testing. In total, 18 nurses and aides were clustered on 1 hospital unit, 7 cases occurred among respiratory therapists that visited that unit, and 10 occurred in other departments. Overall, 17 individuals wore ETS badges as part of hand hygiene monitoring. ETS data established potential transmission opportunities in 17 instances, all but 2 before symptom onset or positive test result. Contacts were most often (10 of 17) in common work areas (nursing stations), with a median time of 45 minutes (IQR, 21–137). Contacts occurred within and between departments. A few COVID-19 patients were cared for in this location at the time of the outbreak. However, we did not detect HCP-to-patient nor patient-to-HCP transmission. Conclusions: Significant HCP-to-HCP transmission occurred during this outbreak based on ETS location. These events often occurred in shared work areas such as the nursing station in addition to break areas noted in other reports. ETS systems, installed for other purposes, can serve to reinforce standard epidemiology.

Funding: No

Disclosures: None

Background: Reports of hospitals overwhelmed by COVID-19 patients created severe shortages of personal protective equipment (PPE). In this large academic medical system, we used a systematic team approach to proactively maintain an adequate PPE supply. The team consisted of staff from multiple departments including infection prevention, environmental health and safety, operational efficiency, and supply chain. The healthcare system solicited donations of PPE, and our team was tasked with developing a sustainable method to provide healthcare workers with safe and effective N-95 respirators. Respirators are normally fitted to our 6,000+ healthcare workers through a fit-testing process using 4 models of N-95s. We received >60 models, many in small quantities, posing a new level of complexity that prevented use of our typical fit-testing method. Methods: Donated respirators were manually verified on the CDC/NIOSH website to validate approval or approved alternative. A categorization system was developed, and respirators were sorted based on quality, style, and condition. User seal checks replaced qualitative fit testing due to the uncertain and quickly changing respirator supply. Staff were educated about the importance of performing a seal check to evaluate respirator fit and were provided instructions for what to do if they failed a seal check. We performed limited quantitative fit testing on a small group previously fit tested to 1 of the 4 models of N-95s normally stocked to identify the most effective alternative respirators to serve as substitute N-95s. Results: We were able to provide staff with new N-95s and delay the release of reprocessed N-95s. Overall, 18 models of respirators were tested on staff for filtration effectiveness and fit. We deemed 61% masks to be of last resort, and these were not released. We determined that 39% were acceptable as an alternative for at least 1 of our usual respirator models. However, only 3 models (17%) available in small quantities fit wearers whose size was in shortest supply. This scarcity led to the evaluation and purchase of a new respirator prototype for small N-95 wearers, which was an important success of our team’s work and for staff safety. Conclusions: Collaboration between teams from a variety of backgrounds, using both qualitative and quantitative data, resulted in a sustainable method for receiving, sorting, and evaluating donated N-95 respirators, ensuring the delivery of a steady supply of effective N-95 respirators to our staff. This quality-driven approach was an efficient and effective strategy to maintain our N-95 respirator supply during a pandemic driven global shortage.

Funding: No

Disclosures: None

Background: Determining the incidence of SARS-CoV-2 in healthcare workers (HCW) is important in assessing the safety of the work environment. Though of limited use in acute illness, serologic testing can detect some infections that occur undetected. We compared the prevalence of antibodies to SARS-CoV-2 to a place of work, exposure by role and department, and use of various prevention methods. Methods: Healthcare workers (HCWs) working in Geisinger Health System were offered voluntary serology through Employee Health. Before they had blood taken, they completed a brief questionnaire. Testing was conducted from June 15 to September 4, 2020. Blood was analyzed for SARS-CoV-2 immunoglobulin G (IgG) (Roche and Diasorin platforms). Results: In total, 2,295 employees and contract workers providing care at Geisinger facilities were tested. Most of this group, 2,037 (88.8%), were involved in direct patient care. In total, 101 tests returned positive, a rate of 4.4% (95% CI, 3.6%–5.3%). Of 54 HCWs with a positive NAAT for SARS-CoV-2, positive serology results were found in 48, a sensitivity of 89% (95% CI, 78%–95%). Those involved in patient care were slightly more likely to become infected, 91 of 2,037 (4.6%) compared to 10 of 258 who were not involved in patient care (3.9%; P = .68). Those with unprotected exposure to a known case of COVID-19 were more likely than those not exposed to be positive for SARS-CoV-2, 51 of 792 (6.4% vs 3.3%; P = .0008). This risk was highest for those exposed outside work (7 of 33; 21%; P = .003). HCWs working in COVID-19 units were positive at a rate of 4.0% (95% CI, 3.8%–5.4%), no more than other inpatient areas, which were 5.0% positive (95% CI, 3.8%–6.4%). HCWs working with outpatients were at slightly lower risk, 2.8% positivity (95% CI, 1.9%–4.1%). The rates of infection ranged between 3.3% and 5.0% by job category. Employees were asked about symptoms experienced since March 2020. Positive serology occurred in 39 (2.8%) of 1,414 employees who did not recall any symptoms. Symptoms related to COVID-19, except sore throat, were strongly correlated with positive serology. Conclusions: When provided a safe work environment, the risk of COVID-19 in employees is comparable to that in the surrounding communities. Persons with patient care responsibilities have an absolute risk that is marginally higher.

Funding: No

Disclosures: None

Background: As the world prepared for and responded to the COVID-19 pandemic in early 2020, a rapid increase in demand for personal protective equipment (PPE) led to severe shortages worldwide. Acquisition of PPE in the general market was an integral part of pandemic response, along with the safeguarding of hospital supplies. We seek to quantify the difference in cost per unit (CPU) of PPE during the first wave of COVID-19 compared to prepandemic prices. Methods: We performed a retrospective review of market prices for PPE during the first surge of the pandemic in Chicago. Cost of PPE was tabulated and compared with prepandemic prices. The maximum cost per unit (CPU) of PPE was tabulated for each week, and the average cost throughout the pandemic was calculated. Disposable gowns, washable gowns, N95 respirators, face masks, and gloves were included in our analysis. Results: PPE prices were significantly higher during the pandemic compared to prepandemic prices (Figure 1). Disposable gown CPU peaked at $12 during the first week of March, 13.7 times higher than prepandemic prices, and the average gown CPU was 7.5 times higher than prepandemic prices. N95 respirators had a peak CPU of $12, and average CPU was 8 times higher than prepandemic prices. Face-mask CPU peaked at $0.55, 11 times higher, and averaged 9 times higher the regular price. Gloves averaged 2.5 times higher than the prepandemic CPU. Conclusions: Market prices for PPE were significantly elevated during the first weeks of the pandemic and remained high throughout the first wave of COVID-19. Multiple factors likely contributed to high prices, including demand shock, disrupted supply chains, and a rush to acquisition by healthcare systems and the general population alike. The impact of COVID-19 on prices highlights the importance of supply chains and national stockpiles for pandemic preparedness.

Funding: No

Disclosures: None

Figure 1.

Background: The novel coronavirus (COVID-19) pandemic has caused significant morbidity and mortality in California: 2,218,000 cases and 24,598 deaths had occurred by December 31, 2020. Deaths at skilled nursing facilities (SNFs) and assisted living facilities (ALFs) comprise 26.2% of deaths in California; the fatality rate (299 per 10,000 SNF and ALF residents) in such facilities is nearly 50 times the statewide COVID-19 mortality rate (6.4 per 10,000 California residents). For healthcare facility (SNF, ALF, acute-care hospitals) and correctional facility outbreak management, the California Department of Public Health (CDPH) Healthcare-Associated Infections (HAI) Program deployed trained infection preventionists (IPs) to perform on-site infection prevention and control (IPC) assessments and to provide recommendations to staff and local health departments (LHDs). We describe the number and distribution of visits across the state and common IPC challenges identified. Methods: From February 1, 2020, to December 31, 2020, CDPH IP visits were requested directly by facilities, coordinated through LHDs and other state agencies, or prompted by a facility’s increasing case count on twice weekly review of the daily California healthcare facility data survey (Survey 123). Deployed IPs evaluated facility COVID-19 IPC protocols, assessed facility staff adherence using a standardized assessment tool, and provided verbal feedback followed by written summary reports and recommendations. We categorized visits geographically into 5 California Health Officer Association regions and by month, and we reviewed visit reports for common findings. Results: In total, 623 visits were performed for 489 outbreaks at 465 distinct facilities across 46 LHDs; 71 facilities received ≥2 visits. Southern California facilities received 292 visits (46.9%), San Joaquin region facilities received 138 visits (22.2%), Bay Area facilities received 131 visits (21%), Greater Sacramento facilities received 54 visits (8.7%), and Rural North facilities received 8 visits (1.3%) (Figure 1). The highest number of visits per month occurred in December (n = 143, 22.9%), followed by July (n = 87, 13.9%), and April (n = 83, 13.3%). Common IPC challenges included inappropriate resident cohorting practices, improper use of personal protective equipment, and lapses in physical distancing, and source control in breakrooms. Conclusions: On-site visits by CDPH IPs during the COVID-19 pandemic in California, though resource-intensive, provided substantial technical support for healthcare facilities during outbreaks and identified key areas for IPC improvement. Ongoing CDPH HAI guidance and training materials for facility-based IP staff are now being informed by these IPC challenges.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Background: Up to half of all new SARS-CoV-2 infections are acquired from presymptomatic or asymptomatic individuals. Hemodialysis patients and healthcare providers (HCPs) may be at increased risk for COVID-19 due to the need for extended close contact. Universal masking and eye protection are strategies used to reduce SARS-CoV-2 exposure, particularly from presymptomatic or asymptomatic individuals. We describe an outbreak of COVID-19 in an outpatient hemodialysis center despite universal masking and universal HCP eye protection. Methods: An COVID-19 outbreak investigation was performed in a hemodialysis center where universal masking was in use by all HCPs and patients and universal eye protection (goggles, safety glasses) was in use by all HCPs when directly encountering patients. After a cluster of cases was identified in early November 2020, all patients and HCPs were tested for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (RT-PCR) when symptomatic and weekly until the conclusion of the outbreak. Results: From November 12, 2020, through December 7, 2020, 14 (23.3%) of 60 patients and 9 (28.1%) of 32 HCPs tested positive for SARS-CoV-2 by RT-PCR (Figure 1). The median ages of the patients and HCPs were 64 years (range, 42–87) and 42 years (range, 29–68), respectively. Also, 5 (5.4%) individuals (3 patients and 2 HCPs) were asymptomatic at the time of testing. Furthermore, 7 (7.6%) individuals (5 patients and 2 HPCs) were hospitalized; 2 patients and no HCPs died. No lapses in universal masking or, for HCPs, eye protection prior to or during the outbreak were identified during the investigation. All HCPs and patients wore medical-grade face masks that were discarded at the end of the day; HCPs wore safety glasses or goggles during patient interactions. Although audits of face mask and eye protection compliance were not performed, independent interviews supported high HCP and patient adherence prior to the outbreak. Neither the staff nor patients shared meals at or outside the hemodialysis center. Most patients and HCPs shared the same hemodialysis shift, suggesting the presence of an index case; however, a source case could not be identified despite an extensive investigation. Conclusions: Universal masking and eye protection have been shown to reduce transmission of SARS-CoV-2 from presymptomatic or asymptomatic individuals in the healthcare setting. This report suggests that such measures cannot prevent all outbreaks. We speculate that certain factors associated with hemodialysis care, such as prolonged close patient–HCP contact, may have facilitated this outbreak. Whether nonadherence to universal masking and eye protection or failure of empiric droplet precautions contributed to this outbreak remains unknown.

Funding: No

Disclosures: None

Background:Acinetobacter baumannii, one of the major causes of nosocomial infections in modern healthcare systems, is characterized by its great persistence in the environment and by its ability to rapidly develop resistance to many antimicrobials. Most A. baumannii infections occur in intubated critically ill patients, causing ventilator-associated pneumonia which is a leading cause of mortality. During the coronavirus disease 19 (COVID-19) pandemic an increase in hospital-acquired carbapenem-resistant A. baumannii (CRAB) infection and colonization in acute-care hospitals has been described. CRAB healthcare-associated infections are often linked to breaches of infection prevention and control (IPC). Beginning in April 2020, our hospital’s IPC unit ordered mandatory universal masking for all healthcare workers (HCWs). Shortages of personal protective equipment during the COVID-19 pandemic led to extended use of surgical face masks by HCWs in our hospital. We investigated whether the extended use of surgical face masks was linked to an increase of CRAB colonization in our intubated critically ill patients. Methods: Surgical masks were collected from doctors, nurses, and housekeeping staff working in 2 internal medicine departments, each including a 4-bed unit for intubated critically ill patients. All surgical masks were worn continuously for 4–5 hours before removal. “Cases“ were defined as HCWs who treated CRAB colonized critically ill patients. “Controls“ were defined as HCWs who did not enter the critically ill patient unit. Surgical masks were incubated with BHI enrichment broth (HyLabs Rehovot, Israel) for 48 hours at 35°C. BHI was seeded on multidrug-resistant (MDR)–selective CHROMagar plates (HyLabs) and incubated overnight at 35°C. Identification was performed using MALDI-ToF mass spectrophotometry (bioMérieux, France). Susceptibility was tested using Vitek 2 (bioMérieux). Results: In total, 55 HCWs participated in the study: 25 cases and 30 controls. Masks from 10 cases (40%) were colonized with Acinetobacter spp versus only 3 masks (10%) from controls (OR, 5.98; 95% CI, 1.42–25; P = .012). Of 13 masks contaminated with Acinetobacter spp, 8 of 10 contaminated masks among cases were colonized with CRAB, whereas only 1 of 3 masks of controls was colonized with CRAB. Conclusions: During the COVID-19 pandemic, extended surgical mask use while treating patients colonized with CRAB increased mask contamination with this bacterium. Surgical masks should be changed after treating a patient colonized with CRAB the same way gown and glove removal and hand hygiene are performed.

Funding: No

Disclosures: None

Background: Accurately tracing nosocomial transmission of coronavirus disease 2019 (COVID-19) is critical to developing effective infection prevention policies. Given the high prevalence and variable incubation period of SARS-CoV-2 infection, the utility of traditional contact tracing is limited. We describe a nosocomial outbreak in which whole-genome sequencing (WGS) was pivotal to identifying the primary case. Methods: This study was conducted at a New York City academic hospital. The index case was identified on August 13, 2020, and the last case on September 9, 2020. Hospital policy required all inpatients to be screened for COVID-19 on admission by SARS-CoV-2 molecular amplification testing. All healthcare workers (HCWs) were required to wear masks and eye protection for patient care. After a patient (patient 1), who tested SARS-CoV-2 negative on admission, was positive on preprocedure screening on hospital day 9, contact tracing was initiated. Two patients (patients 2 and 3) and 13 HCWs with high-risk exposures (HREs) to patient 1 were quarantined and referred for testing. Additional surveillance testing was performed on 18 inpatients and 84 HCWs on the affected unit. Patients 2 and 3 and 3 HCWs (HCW-1, -2, and -3), only 1 of whom had a high-risk exposure to patient 1, tested positive. WGS was performed to further investigate this outbreak. Results: The outbreak variant (clade 20A) was found in samples from 6 patients and 2 HCWs. Patients 2 and 3 were roommates of patient 1 in the 2 days before patient 1’s positive test, and they did not consistently wear masks in the room. HCW-1 placed a peripheral IV in patient 1 the day before patient 1’s positive test without wearing eye protection. Four additional cases in this cluster (patients 4–6 and HCW-4) were identified by surveillance WGS of positive tests. A review indicated that patient 1 was located ~3 m (~10 feet) away from patient 4 in the emergency department (ED) for 6 hours on hospital day 1, when the admission SARS-CoV-2 test from patient 4 was not positive. No epidemiologic link was found to patient 5 or 6 or HCW-4. The specimen from HCW-2 was inadequate for WGS. The specimen from HCW-3 was not linked to this cluster. Conclusions: This complex nosocomial outbreak highlights the importance of WGS in understanding transmission events. Patient 4 was not identified by traditional contact tracing but was linked to patient 1 and was recognized as the primary case through WGS, having likely infected patient 1 in the ED. Based on these findings, we focused our corrective actions on more promptly isolating suspected COVID-19 cases in the ED, increasing inpatient masking, and improving HCW adherence to universal eye protection.

Funding: No

Disclosures: None

Background: Asymptomatic SARS-CoV-2 infections play a crucial role in viral transmission. However, they are often difficult to identify given that widespread surveillance has not been the norm. We sought to determine whether COVID-19 rates reported at the county level could predict the positivity rates for SARS-CoV-2 among asymptomatic patients tested in a large academic health system. Methods: This observational study was conducted from April 23, 2020, to December 10, 2020, at Froedtert Health (FH) system, the largest academic health system in Wisconsin. On April 23, 2020, FH implemented SARS-CoV-2 surveillance among all consecutive admissions not suspected of COVID-19, all patients scheduled for elective procedures and deliveries, and all asymptomatic patients with known exposures. Samples were processed by the FH laboratory using molecular methods (RT-PCR). To obtain the daily number of newly confirmed COVID-19 cases in Milwaukee County, we accessed the Wisconsin Department of Health Services publicly available COVID-19 database. For the purpose of this study, COVID-19 rates were defined as the percentage of positive tests among all daily tests performed at the county level, while SARS-CoV-2 positivity rates were the percentage of positive tests among all daily surveillance tests performed at FH among asymptomatic patients. The association between COVID-19 rates in Milwaukee County and asymptomatic rates at FH were assessed using an autoregressive moving average time series analysis. To examine the association between these rates, we fitted a seventh-order autoregression for the residuals based on autocorrelation function and partial autocorrelation function plots of the residuals from linear regression. Results: From April 23, 2020, to December 10, 2020, there were 2,347 new asymptomatic infections detected at FH and 75,196 new COVID-19 cases reported in Milwaukee County. Figure 1 shows the time-series plot of asymptomatic SARS-CoV-2 positivity rates at FH and Figure 2 shows COVID-19 rates in Milwaukee County. As the COVID-19 rate in Milwaukee County increased by 1 unit, the asymptomatic infection rate in FH decreased by 0.024 unit (95% CI, −0.053 to 0.004; P = .095) after accounting for autocorrelation over time. Thus, there was no association between these rates. Conclusions: The positivity rates among asymptomatic patients at a large medical center were not predicted by the positivity rate at the county level. This finding suggests that the epidemiology at a county level may be determined by pockets in the population who may not interact, and thus not affect, the positivity rates among asymptomatic patients served by a hospital system within the county.

Funding: No

Disclosures: None

Figure 1.

Figure 2.

Background: We investigated the contact status of medical staff with confirmed or suspected patients with COVID-19 in Sichuan Province, China, as well as the use of personal protective equipment at the time of contact, and we explored the factors affecting the effective use of personal protective equipment. Methods: We performed a cross-sectional study by distributing a questionnaire on occupational protection and exposure of medical staff in the diagnosis and treatment of COVID-19 using a convenience sampling method for online surveys from February 23 to February 29, 2020. Results: In total, 13,829 valid questionnaires from 644 hospitals in Sichuan Province were retrieved, and 802 people were exposed to confirmed or suspected patients with COVID-19, accounting for 5.80%. 688 (85.79%) of 802 people who reported that they had taken effective personal protection measures for each exposure. Sex, work department, and length of service were the independent factors influencing the effective use of personal protective equipment in multivariate analysis (P < .05). Conclusions: Medical institutions need to continue to strengthen the training regarding standard precautions and personal protection, especially for general departments other than fever clinics and isolation wards, as well as medical staff with few working years, to ensure the occupational safety of medical staff.

Funding: No

Disclosures: None

Background: The County of San Diego Health and Human Services (SDHHSA) established a goal to vaccinate 1.9 million residents as quickly as possible to attain vaccine induced herd immunity. This strategy would minimize the emergence of more transmissible variants, to which some vaccines may be less effective. With this strategy in mind, UC San Diego Health (UCSDH) collaborated with the local health authorities and the San Diego Padres to build a superstation in downtown San Diego in the parking lot of a baseball stadium. Methods: Building on the experience of rapidly vaccinating the UCSDH workforce in mid-December 2020, UCSDH and SDHHSA partnered to more efficiently distribute SARS-CoV-2 vaccine in San Diego County by building a vaccine superstation. The San Diego Padres offered their parking lot as the site; it was centrally located, easily accessible, quick to set up, and semipermanent. They also provided infrastructure support, event coordination, and internet capability. Occupying a space of ~6.5 acres, the superstation included 12 lanes serving 12 cars each, with ~3 cycles every hour, as well as a pedestrian walk-up station. Altogether, the site had the capacity for >5,000 vaccinations daily. This effort required coordination among administration, healthcare providers, IT specialists, and support staff—a daily workforce of >300 persons. The workforce needs were met using a multipronged approach, including flexible staffing, coordination of volunteers, and recruitment of previously retired providers. The private–public partnership enabled the superstation to be up and running in 5 days. Results: The operation was quickly ramped up to provide >6,000 vaccines daily. Initially only open to healthcare workers, on January 17 the superstation was expanded to persons aged >75 years, with further expansion to those aged ≥65 years on January 23. From January 11 to February 5, >100,000 individuals received their first dose of vaccine at the superstation, corresponding to ~31% of all San Diego county vaccinations. Conclusions: Vaccination of as many people as quickly as possible is essential to controlling the pandemic. Unchecked replication of SARS-CoV-2 allows increases the chance that the virus may develop mutations that render vaccines and therapeutics less effective. Our model vaccine superstation was replicated at 3 more sites around the county, the limited allocation of vaccine has been the only barrier to further expansion. A force of 10 superstations could administer a first dose to the remaining 1.6 million county residents within 32 days.

Funding: No

Disclosures: None

Background: Outcomes among nursing home residents with asymptomatic compared to symptomatic COVID-19 are not well characterized. We assessed all-cause mortality among Veterans’ Affairs (VA) community living center (CLC) residents; we compared those residents with a negative SARS-CoV-2 test to residents with symptomatic, presymptomatic, and asymptomatic SARS-CoV-2 infections. Methods: We conducted a national retrospective cohort study of CLC residents tested for COVID-19 between March 1 and July 31, 2020, based on data compiled through the VA COVID-19 shared data resource. Among those with a positive SARS-CoV-2 test, residents were considered symptomatic if they had experienced COVID-19 symptoms in the 30 days prior to the test. Residents were considered presymptomatic if they did not experience symptoms in the 30 days prior to testing and developed a fever (>38°C) or required supplemental oxygen within 14 and 60 days, respectively, following the test. Residents were considered asymptomatic in the absence of these pre- and posttest symptoms. Results: From March 1 to July 31, 2020, of 9,052 CLC residents screened for COVID-19, 8,325 (92%) tested negative (Table 1). Among 727 residents with positive tests, 467 (64%) were symptomatic, 88 (12%) were presymptomatic, and 172 (24%) remained asymptomatic. We observed significant differences in the racial makeup of these disease groups. Among CLC residents who were symptomatic or presymptomatic, 176 (32%) of 555 were black compared to 39 (23%) of 172 who were asymptomatic and 1,810 (22%) of 8,325 who tested negative for SAR-CoV-2. All-cause 30-day mortality rates for symptomatic and presymptomatic residents were 25% and 34%, respectively, which exceeded the all-cause 30-day mortality of asymptomatic residents (12%) and residents with a negative test (6%) (Figure 1). Conclusions: More than one-third of CLC residents with COVID-19 were asymptomatic at the time of testing. This finding highlights the importance of vigilant infection prevention and control measures. Our finding that mortality among presymptomatic residents exceeded that of symptomatic residents raises consideration for enhancing supportive care measures, such as supplemental oxygen and mitigation of inflammatory reactions, as a means to reduce mortality among nursing home residents with presymptomatic SARS-CoV-2 infections.

Funding: No

Disclosures: None

Table 1.

Figure 1.