To examine rural–urban differences in temporal trends and risk of inappropriate antibiotic use by agent and duration among women with uncomplicated urinary tract infection (UTI).

Observational cohort study.

Using the IBM MarketScan Commercial Database (2010–2015), we identified US commercially insured women aged 18–44 years coded for uncomplicated UTI and prescribed an oral antibiotic agent. We classified antibiotic agents and durations as appropriate versus inappropriate based on clinical guidelines. Rural–urban status was defined by residence in a metropolitan statistical area. We used modified Poisson regression to determine the association between rural–urban status and inappropriate antibiotic receipt, accounting for patient- and provider-level characteristics. We used multivariable logistic regression to estimate trends in antibiotic use by rural–urban status.

Of 670,450 women with uncomplicated UTI, a large proportion received antibiotic prescriptions for inappropriate agents (46.7%) or durations (76.1%). Compared to urban women, rural women were more likely to receive prescriptions with inappropriately long durations (adjusted risk ratio 1.10, 95% CI, 1.10–1.10), which was consistent across subgroups. From 2011 to 2015, there was slight decline in the quarterly proportion of patients who received inappropriate agents (48.5% to 43.7%) and durations (78.3% to 73.4%). Rural–urban differences varied over time by agent (duration outcome only), geographic region, and provider specialty.

Inappropriate antibiotic prescribing is quite common for the treatment of uncomplicated UTI. Rural women are more likely to receive inappropriately long antibiotic durations. Antimicrobial stewardship interventions are needed to improve outpatient UTI antibiotic prescribing and to reduce unnecessary exposure to antibiotics, particularly in rural settings.

We assessed the magnitude of unidentified coronavirus disease 2019 (COVID-19) in our healthcare personnel (HCP) early in the COVID-19 pandemic, and we evaluated risk factors for infection to identify areas for improvement in infection control practice in a northern California academic medical center.

We reviewed anti–severe acute respiratory coronavirus virus 2 (SARS-CoV-2) receptor-binding domain (RBD) IgG serologic test results and self-reported risk factors for seropositivity among 10,449 asymptomatic HCP who underwent voluntary serology testing between April 20 and May 20, 2020.

In total, 136 employees (1.3%) tested positive for SARS-CoV-2 IgG. This included 41 individuals (30.1%) who had previously tested positive for SARS-CoV-2 by nasopharyngeal reverse-transcription polymerase chain reaction (RT-PCR) between March 13 and April 16, 2020. In multivariable analysis, employees of Hispanic ethnicity (odds ratio [OR], 2.01; 95% confidence interval [CI], 1.22–3.46) and those working in environmental services, food services, or patient transport (OR, 4.81; 95% CI, 2.08–10.30) were at increased risk for seropositivity compared to other groups. Employees reporting a household contact with COVID-19 were also at higher risk for seropositivity (OR, 3.25; 95% CI, 1.47–6.44), but those with a work, exposure alone were not (OR, 1.27; 95% CI, 0.58–2.47). Importantly, one-third of seropositive individuals reported no prior symptoms, no suspected exposures, and no prior positive RT-PCR test.

In this study, SARS-CoV-2 seropositivity among HCP early in the northern California epidemic appeared to be quite low and was more likely attributable to community rather than occupational exposure.

To determine risk factors for mortality among COVID-19 patients admitted to a system of community hospitals in the United States.

Retrospective analysis of patient data collected from the routine care of COVID-19 patients.

System of >180 acute-care facilities in the United States.

All admitted patients with positive identification of COVID-19 and a documented discharge as of May 12, 2020.

Determination of demographic characteristics, vital signs at admission, patient comorbidities and recorded discharge disposition in this population to construct a logistic regression estimating the odds of mortality, particular for those patients characterized as not being critically ill at admission.

In total, 6,180 COVID-19+ patients were identified as of May 12, 2020. Most COVID-19+ patients (4,808, 77.8%) were admitted directly to a medical-surgical unit with no documented critical care or mechanical ventilation within 8 hours of admission. After adjusting for demographic characteristics, comorbidities, and vital signs at admission in this subgroup, the largest driver of the odds of mortality was patient age (OR, 1.07; 95% CI, 1.06–1.08; P < .001). Decreased oxygen saturation at admission was associated with increased odds of mortality (OR, 1.09; 95% CI, 1.06–1.12; P < .001) as was diabetes (OR, 1.57; 95% CI, 1.21–2.03; P < .001).

The identification of factors observable at admission that are associated with mortality in COVID-19 patients who are initially admitted to non-critical care units may help care providers, hospital epidemiologists, and hospital safety experts better plan for the care of these patients.

Evidence-based infection control strategies are needed for healthcare workers (HCWs) following high-risk exposure to severe acute respiratory coronavirus virus 2 (SARS-CoV-2). In this study, we evaluated the negative predictive value (NPV) of a home-based 7-day infection control strategy.

HCWs advised by their infection control or occupational health officer to self-isolate due to a high-risk SARS-CoV-2 exposure were enrolled between May and October 2020. The strategy consisted of symptom-triggered nasopharyngeal SARS-CoV-2 RNA testing from day 0 to day 7 after exposure and standardized home-based nasopharyngeal swab and saliva testing on day 7. The NPV of this strategy was calculated for (1) clinical coronavirus disease 2019 (COVID-19) diagnosis from day 8–14 after exposure, and for (2) asymptomatic SARS-CoV-2 detected by standardized nasopharyngeal swab and saliva specimens collected at days 9, 10, and 14 after exposure. Interim results are reported in the context of a second wave threatening this essential workforce.

Among 30 HCWs enrolled, the mean age was 31 years (SD, ±9), and 24 (80%) were female. Moreover, 3 were diagnosed with COVID-19 by day 14 after exposure (secondary attack rate, 10.0%), and all cases were detected using the 7-day infection control strategy: the NPV for subsequent clinical COVID-19 or asymptomatic SARS-CoV-2 detection by day 14 was 100.0% (95% CI, 93.1%–100.0%).

Among HCWs with high-risk exposure to SARS-CoV-2, a home-based 7-day infection control strategy may have a high NPV for subsequent COVID-19 and asymptomatic SARS-CoV-2 detection. Ongoing data collection and data sharing are needed to improve the precision of the estimated NPV, and here we report interim results to inform infection control strategies in light of a second wave threatening this essential workforce.

We performed a systematic literature review and meta-analysis measuring the burden of antibiotic use during end-of-life (EOL) care.

We searched PubMed, CINAHL (EBSCO platform), and Embase (Elsevier platform), through July 2019 for studies with the following inclusion criteria in the initial analysis: antibiotic use in the EOL care patients (advanced dementia, cancer, organ failure, frailty or multi-morbidity). If the number of patients in palliative care consultation (PCC) was available, antibiotic use data were pooled to compare the proportion of patients who received antibiotics under PCC compared to those not receiving PCC. Random-effect models were used to obtain pooled mean differences, and heterogeneity was assessed using the I2 value.

Overall, 72 studies met the inclusion criteria and were included in the final review: 22 EOL studies included only patients with cancer; 17 studies included only patients with advanced dementia; and 33 studies included “mixed populations” of EOL patients. Although few studies reported antibiotic using standard metrics (eg, days of therapy), 48 of 72 studies (66.7%) reported antibiotic use in >50% of all patients. When the 3 studies that evaluated antibiotic use in PCC were pooled together, patients under PCC was more likely to receive antibiotics compared to patients not under PCC (pooled odds ratio, 1.73; 95% CI, 1.02–2.93).

Future studies are needed to evaluate the benefits and harms of using antibiotics for patients during EOL care in diverse patient populations.

Due to shortages of N95 respirators during the coronavirus disease 2019 (COVID-19) pandemic, it is necessary to estimate the number of N95s required for healthcare workers (HCWs) to inform manufacturing targets and resource allocation.

We developed a model to determine the number of N95 respirators needed for HCWs both in a single acute-care hospital and the United States.

For an acute-care hospital with 400 all-cause monthly admissions, the number of N95 respirators needed to manage COVID-19 patients admitted during a month ranges from 113 (95% interpercentile range [IPR], 50–229) if 0.5% of admissions are COVID-19 patients to 22,101 (95% IPR, 5,904–25,881) if 100% of admissions are COVID-19 patients (assuming single use per respirator, and 10 encounters between HCWs and each COVID-19 patient per day). The number of N95s needed decreases to a range of 22 (95% IPR, 10–43) to 4,445 (95% IPR, 1,975–8,684) if each N95 is used for 5 patient encounters. Varying monthly all-cause admissions to 2,000 requires 6,645–13,404 respirators with a 60% COVID-19 admission prevalence, 10 HCW–patient encounters, and reusing N95s 5–10 times. Nationally, the number of N95 respirators needed over the course of the pandemic ranges from 86 million (95% IPR, 37.1–200.6 million) to 1.6 billion (95% IPR, 0.7–3.6 billion) as 5%–90% of the population is exposed (single-use). This number ranges from 17.4 million (95% IPR, 7.3–41 million) to 312.3 million (95% IPR, 131.5–737.3 million) using each respirator for 5 encounters.

We quantified the number of N95 respirators needed for a given acute-care hospital and nationally during the COVID-19 pandemic under varying conditions.

Critical shortages of personal protective equipment, especially N95 respirators, during the coronavirus disease 2019 (COVID-19) pandemic continues to be a source of concern. Novel methods of N95 filtering face-piece respirator decontamination that can be scaled-up for in-hospital use can help address this concern and keep healthcare workers (HCWs) safe.

A multidisciplinary pragmatic study was conducted to evaluate the use of an ultrasonic room high-level disinfection system (HLDS) that generates aerosolized peracetic acid (PAA) and hydrogen peroxide for decontamination of large numbers of N95 respirators. A cycle duration that consistently achieved disinfection of N95 respirators (defined as ≥6 log10 reductions in bacteriophage MS2 and Geobacillus stearothermophilus spores inoculated onto respirators) was identified. The treated masks were assessed for changes to their hydrophobicity, material structure, strap elasticity, and filtration efficiency. PAA and hydrogen peroxide off-gassing from treated masks were also assessed.

The PAA room HLDS was effective for disinfection of bacteriophage MS2 and G. stearothermophilus spores on respirators in a 2,447 cubic-foot (69.6 cubic-meter) room with an aerosol deployment time of 16 minutes and a dwell time of 32 minutes. The total cycle time was 1 hour and 16 minutes. After 5 treatment cycles, no adverse effects were detected on filtration efficiency, structural integrity, or strap elasticity. There was no detectable off-gassing of PAA and hydrogen peroxide from the treated masks at 20 and 60 minutes after the disinfection cycle, respectively.

The PAA room disinfection system provides a rapidly scalable solution for in-hospital decontamination of large numbers of N95 respirators during the COVID-19 pandemic.

To report a conjunctivitis outbreak in a neonatology intensive care unit (NICU) and determine the associated economic impact.

Prospective observational study.

Centro de Educación Médica e Investigaciones Clínicas (CEMIC) University Hospital, a private, tertiary-care healthcare institution in Buenos Aires, Argentina.

The study included 52 NICU neonates and 59 NICU-related healthcare workers (HCWs) from CEMIC hospital.

Neonates and HCWs were swabbed for real-time polymerase chain reaction (PCR) testing, viral culture, and typing by sequencing. Infection control measures, structural and logistic changes were implemented. Billing records were analyzed to determine costs.

From January 30 to April 28, 2018, 52 neonates were hospitalized in the NICU. Among them, 14 of 52 (21%) had bilateral conjunctivitis with pseudomembranes. Symptomatic neonates and HCWs were HAdV-D8 positive. Ophthalmological symptoms had a median duration of 18 days (IQR, 13–24.5). PCR positivity and infectious range had a median duration of 18.5 days. As part of containment measures, the NICU and the high-risk pregnancy unit were closed to new patients. The NICU was divided into 2 areas for symptomatic and asymptomatic patients; a new room was assigned for the general nursery, and all deliveries from the high-risk pregnancy unit were redirected to other hospitals. The outbreak cost the hospital US$205,000: implementation of a new nursery room and extra salaries cost US$30,350 and estimated productivity loss during 1 month cost US$175,000.

Laboratory diagnosis confirmed the cause of this outbreak as HAdV-D8. The immediate adoption and reinforcement of rigorous infection control measures limited the nosocomial viral spread. This outbreak represented a serious institutional problem, causing morbidity, significant economic loss, and absenteeism.

Antibiotic resistance (AR) is a growing and highly prevalent problem in nursing homes. We describe selected AR phenotypes from pathogens causing urinary tract infections (UTIs) reported by nursing homes to the National Healthcare Safety Network (NHSN).

Pathogens and antibiotic susceptibility testing results for UTI events in nursing homes between January 2013 and December 2017 were analyzed. The pathogen distribution and pooled mean proportion of isolates that tested resistant to select antibiotic agents are reported.

US nursing homes voluntarily participating in the Long-Term Care Facility component of the NHSN.

Overall, 243 nursing homes reported 1 or more UTIs: 121 (50%) were nonprofit facilities, median bed size was 91 (range: 9–801), and average occupancy was 87%. In total, 6,157 pathogens were reported for 5,485 UTI events. Moreover, 9 pathogens accounted for 90% of all reported UTIs; the 3 most frequently identified were Escherichia coli (41%), Proteus species (14%), and Klebsiella pneumoniae/oxytoca (13%). Among E. coli, fluoroquinolone, and extended-spectrum cephalosporin resistance were most prevalent (50% and 20%, respectively). Although Staphylococcus aureus and Enterococcus faecium represented <5% of pathogens reported, they had the highest rates of resistance (67% methicillin resistant and 60% vancomycin resistant, respectively). Multidrug resistance was most common in Pseudomonas aeruginosa (11%). For the resistant phenotypes we assessed, 36% of all UTIs reported were associated with a resistant pathogen.

This is the first summary of AR among common pathogens causing UTIs reported to NHSN by nursing homes. Improved understanding of the resistance burden among common infections helps inform facility infection prevention and antibiotic stewardship efforts.

A growing body of evidence suggests that antibiotic allergy labels as documented in medical records are a risk factor for poor clinical outcomes. In this systematic review, we aimed to determine how antibiotic allergy labels influence 3 domains: antibiotic use and exposure, clinical outcomes, and healthcare-related costs.

We performed a systematic review to identify studies reporting outcomes in patients with antibiotic allergy labels compared to nonallergic counterparts. The search included PubMed, EMBASE, Cochrane CENTRAL, EBSCO, Cochrane Database of Abstracts of Reviews of Effects and Web of Science. Two reviewers independently screened studies for inclusion and abstracted data. Studies were graded using the Newcastle-Ottawa quality assessment scale. Study outcomes included antibiotic use, clinical outcomes, and economic outcomes.

In total, 41 studies met our criteria for inclusion. These studies varied in medical specialty, patient population, healthcare delivery system, and design, but most were conducted among adults age >18 years (85%) in the inpatient setting (82.5%). Among 34 studies examining antibiotic exposure, 32 (94%) found that patients with antibiotic allergy labels received more broad-spectrum antibiotics. Moreover, 31 studies examined clinical outcomes such as length of hospitalization, ICU admission, hospital readmission, multidrug-resistant or opportunistic infection, or mortality, and 27 (87%) found that allergy-labeled patients had at least 1 negative outcome. Of 9 studies examining healthcare costs, 7 (78%) found that allergy-labeled patients incurred significantly higher drug or hospital-related costs.

Antibiotic allergy labels have negative effects on antibiotic use, clinical outcomes, and economic outcomes in a variety of clinical settings and populations.

To examine whether the issue and dissemination of national guidelines in the Manual of Antimicrobial Stewardship had an impact on reducing antibiotic use for acute respiratory tract infection (ARTI) and gastroenteritis.

An interrupted time-series analysis was performed using a large nationwide database from June 2016 to June 2018. Outpatients with ARTI or gastroenteritis aged ≥6 years were identified. The outcome measures were any antibiotic use and broad-spectrum antibiotic use. The season-adjusted changes in the rate of antibiotic prescriptions for 2 periods before and after the guideline issue date were examined.

There were 13,177,735 patients with ARTI and 300,565 patients with gastroenteritis during the study period. Among patients with ARTI, there was a significant downward trend in antibiotic use during the 2-year study period (−0.06% per week; 95% CI, −0.07% to −0.04%). However, there was no significant change in trends of antibiotic use between the pre-issue period and post-issue period (trend difference, −0.01% per week; 95% CI, −0.10% to 0.07%). Similarly, for patients with gastroenteritis, there was no significant change in the trends of antibiotic use between the pre-issue period and post-issue period (trend difference, −0.02% per week; 95% CI, −0.04% to 0.01%). Similar associations were observed in analyses for broad-spectrum antibiotic use.

Despite the issue of national guidelines to promote the appropriate use of antibiotics, there were no significant changes in trends of antibiotic use for outpatients with ARTI or gastroenteritis between the pre-issue and post-issue periods.

To evaluate the impact of outpatient parenteral antimicrobial therapy (OPAT) on a public hospital in a middle-income country.

A retrospective, observational study analyzing the economic data retrieved on the dehospitalization of patients on antibiotic therapy.

Public university trauma hospital.

Data were collected from June 2017 to May 2020. Antibiotic cost, hospital length of stay, and risk of multidrug-resistant (MDR) infection or colonization were reviewed, along with the break-even point at which a balance occurs between OPAT antimicrobial costs and all in-hospital costs. A cumulative risk curve was constructed showing the incidence of MDR during the review period.

In total, 225 patients were studied. The implementation of OPAT resulted in a reduction of $156,681 (49.6%), which is equivalent to an average of $696 per patient, as well as a shortened length of stay, from 33.5 to 15.7 days. OPAT reduces the risk of acquiring infection by MDR bacteria by having the final treatments administered outside of the hospital environment. The breakeven curves, comparing the duration of the OPAT to daily medication costs, allowed for the prediction of the time and dollar costs of antibiotic therapy.

OPAT presented a significant cost savings, shortened length of stay, and reduced risk of contamination of patients by MDR.

Care homes are vulnerable to widespread transmission of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) with poor outcomes for staff and residents. Infection control interventions in care homes need to not only be effective in containing the spread of coronavirus disease 2019 (COVID-19) but also feasible to implement in this special setting which is both a healthcare institution and a home.

We developed an agent-based model that simulates the transmission dynamics of COVID-19 via contacts between individuals, including residents, staff members, and visitors in a care home setting. We explored a representative care home in Scotland in our base case and explore other care home setups in an uncertainty analysis. We evaluated the effectiveness of a range of intervention strategies in controlling the spread of COVID-19.

In the presence of the reference interventions that have been implemented in many care homes, including testing of new admissions, isolation of symptomatic residents, and restricted public visiting, routine testing of staff appears to be the most effective and practical approach. Routine testing of residents is no more effective as a reference strategy while routine testing of both staff and residents only shows a negligible additive effect. Modeling results are very sensitive to transmission probability per contact, but the qualitative finding is robust to varying parameter values in our uncertainty analysis.

Our model predictions suggest that routine testing should target staff in care homes in conjunction with adherence to strict hand hygiene and using personal protective equipment to reduce risk of transmission per contact.

To describe local experience in managing an outbreak of Candida auris in a tertiary-care setting.

In response to emerging Candida auris, an outbreak investigation was conducted at our hospital between March 2018 and June 2019. Once a patient was confirmed to have Candida auris, screening of exposed patients and healthcare workers (HCWs) was conducted. Postexposure screening included those who had had direct contact with or shared the same unit or ward with a laboratory-confirmed case. In response to the increasing number of cases, new infection control measures were implemented.

In total, 23 primary patients were detected over 15 months. Postexposure screening identified 11 more cases, and all were patients. Furthermore, ~28.6% of patients probably caught infection in another hospital or in the community. Infection control measures were strictly implemented including hand hygiene, personal protective equipment, patient hygiene, environmental cleaning, cohorting of patients and HCWs, and avoiding the sharing of equipment. The wave reached a peak in April 2019, followed by a sharp decrease in May 2019 and complete clearance in June 2019. The case patients were equally distributed between intensive care units (51.4%) and wards (48.6%). More infections (62.9%) occurred than colonizations (37.1%). Urinary tract infection (42.9%) and candidemia (17.1%) were the main infections. In total, 7 patients (20.0%) died during hospitalization; among them, 6 (17.1%) died within 30 days of diagnosis.

Active screening of exposed patients followed by strict infection control measures, including environmental cleaning, was successful in ending the outbreak. Preventing future outbreaks is challenging due to outside sources of infection and environmental resistance.

To determine the usefulness of adjusting antibiotic use (AU) by prevalence of bacterial isolates as an alternative method for risk adjustment beyond hospital characteristics.

Retrospective, observational, cross-sectional study.

Hospitals in the southeastern United States.

AU in days of therapy per 1,000 patient days and microbiologic data from 2015 and 2016 were collected from 26 hospitals. The prevalences of Pseudomonas aeruginosa, extended-spectrum β-lactamase (ESBL)–producing bacteria, methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant enterococci (VRE) were calculated and compared to the average prevalence of all hospitals in the network. This proportion was used to calculate the adjusted AU (a-AU) for various categories of antimicrobials. For example, a-AU of antipseudomonal β-lactams (APBL) was the AU of APBL divided by (prevalence of P. aeruginosa at that hospital divided by the average prevalence of P. aeruginosa). Hospitals were categorized by bed size and ranked by AU and a-AU, and the rankings were compared.

Most hospitals in 2015 and 2016, respectively, moved ≥2 positions in the ranking using a-AU of APBL (15 of 24, 63%; 22 of 26, 85%), carbapenems (14 of 23, 61%; 22 of 25; 88%), anti-MRSA agents (13 of 23, 57%; 18 of 26, 69%), and anti-VRE agents (18 of 24, 75%; 15 of 26, 58%). Use of a-AU resulted in a shift in quartile of hospital ranking for 50% of APBL agents, 57% of carbapenems, 35% of anti-MRSA agents, and 75% of anti-VRE agents in 2015 and 50% of APBL agents, 28% of carbapenems, 50% of anti-MRSA agents, and 58% of anti-VRE agents in 2016.

The a-AU considerably changes how hospitals compare among each other within a network. Adjusting AU by microbiological burden allows for a more balanced comparison among hospitals with variable baseline rates of resistant bacteria.

Evaluate the difference in antibiotic prescribing between various levels of resident training or attending types.

Observational, retrospective study.

Tertiary-care, academic medical center in Madison, Wisconsin.

We measured antibiotic utilization from January 1, 2016, through December 31, 2018, in our general medicine (GM) and hospitalist services. The GM1 service is staffed by outpatient internal medicine physicians, the GM2 service is staffed by geriatricians and hospitalists, and the GM3 service is staffed by only hospitalists. The GMA service is led by junior resident physicians, and the GMB service is led by senior resident physicians. We measured utilization using days of therapy (DOT) per 1,000 patient days (PD). In a secondary analysis based on antibiotic spectrum, we used average DOT per 1,000 PD.

Teaching services prescribed more antibiotics than nonteaching services (671.6 vs 575.2 DOT per 1,000 PD; P < .0001). Junior resident–led services used more antibiotics than senior resident–led services (740.9 vs 510.0 DOT per 1,000 PD; P < .0001). Overall, antibiotic prescribing was numerically similar between various attending physician backgrounds. A secondary analysis showed that GM services prescribed more broad-spectrum, anti-MRSA, and anti-pseudomonal antibiotics than the hospitalist services. GM junior resident–led services prescribed more broad-spectrum, anti-MRSA, and antipseudomonal therapy compared to their senior counterparts.

Antibiotics were prescribed at a significantly higher rate in services associated with trainees than those without. Services led by a junior resident physician prescribed antibiotics at a significantly higher rate than services led by a senior resident. Interventions to reduce unnecessary antibiotic exposure should be targeted toward resident physicians, especially junior trainees.

Influenza can be introduced and propagated in healthcare settings by healthcare workers (HCWs) working while ill with influenza. However, reasons driving this behavior are unclear. In this study, we examined barriers to and facilitators of absenteeism during the influenza season.

Cross-sectional mixed methods study.

Ambulatory and inpatient settings in a large, tertiary-care healthcare system.

An anonymous electronic survey was sent to HCWs between June 11 and July 13, 2018, asking participants to self-report influenza-like illness (ie, ILI symptoms of fever, chills, cough, or sore throat) during the 2017–2018 influenza season. We conducted a logistical regression analysis to identify factors associated with absenteeism.

Of 14,250 HCWs, 17% responded to the survey. Although 1,180 respondents (51%) reported symptoms of ILI, 575 (43%) did not stay home while ill. The most commonly perceived barriers to ILI absenteeism included being understaffed (odds ratio [OR], 1.78; P = .04), unable to find a replacement for work (OR, 2.26; P = .03), desiring not to use time off (OR, 2.25; P = .003), and paid by the hour or unable to afford being absent (OR, 2.05; P = .02). Common perceived facilitators of absenteeism included support from coworkers and management, clearer policy, better sick days availability, and lower perceived threat of disciplinary action.

Reporting to work with ILI symptoms is common among HCWs. Most barriers and facilitators are related to systems. Addressing system factors, such as policies regarding sick days and sick leave and ensuring adequate backup staffing, is likely to facilitate absenteeism among ill HCWs.

Tracheal intubation and mechanical ventilation provide essential support for patients with respiratory failure, but the course of mechanical ventilation may be complicated by adverse ventilator-associated events (VAEs), which may or may not be associated with infection. We sought to understand how the frequency of subglottic suction, an indicator of the quantity of sputum produced by ventilated patients, relates to the onset of all VAEs and infection-associated VAEs.

We performed a case-crossover study including 87 patients with VAEs, and we evaluated 848 days in the pre-VAE period at risk for a VAE.

Critically ill patients were recruited from the medical intensive care unit of an academic medical center.

We used the number of as-needed subglottic suctioning events performed per calendar day to quantify sputum production, and we compared the immediate pre-VAE period to the preceding period. We used CDC surveillance definitions for VAE and to categorize whether events were infection associated or not.

Sputum quantity measured by subglottic suction frequency is greater in the period immediately prior to VAE than in the preceding period. However, it does not discriminate well between infection-associated VAEs and VAEs without associated infection.

Subglottic suction frequency may serve as a valuable marker of sputum quantity, and it is associated with risk of a VAE. However, our results require validation in a broader population of mechanically ventilated patients and intensive care settings.

The coronavirus disease 2019 (COVID-19) pandemic has induced a reinforcement of infection control measures in the hospital setting. Here, we assess the impact of the COVID-19 pandemic on the incidence of nosocomial Clostridioides difficile infection (CDI).

We retrospectively compared the incidence density (cases per 10,000 patient days) of healthcare-facility–associated (HCFA) CDI in a tertiary-care hospital in Madrid, Spain, during the maximum incidence of COVID-19 (March 11 to May 11, 2020) with the same period of the previous year (control period). We also assessed the aggregate in-hospital antibiotic use (ie, defined daily doses [DDD] per 100 occupied bed days [BD]) and incidence density (ie, movements per 1,000 patient days) of patient mobility during both periods.

In total, 2,337 patients with reverse transcription-polymerase chain reaction–confirmed COVID-19 were admitted to the hospital during the COVID-19 period. Also, 12 HCFA CDI cases were reported at this time (incidence density, 2.68 per 10,000 patient days), whereas 34 HCFA CDI cases were identified during the control period (incidence density, 8.54 per 10,000 patient days) (P = .000257). Antibiotic consumption was slightly higher during the COVID-19 period (89.73 DDD per 100 BD) than during the control period (79.16 DDD per 100 BD). The incidence density of patient movements was 587.61 per 1,000 patient days during the control period and was significantly lower during the COVID-19 period (300.86 per 1,000 patient days) (P < .0001).

The observed reduction of ~70% in the incidence density of HCFA CDI in a context of no reduction in antibiotic use supports the importance of reducing nosocomial transmission by healthcare workers and asymptomatic colonized patients, reinforcing cleaning procedures and reducing patient mobility in the epidemiological control of CDI.

Understanding the extent of aerosol-based transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is important for tailoring interventions for control of the coronavirus disease 2019 (COVID-19) pandemic. Multiple studies have reported the detection of SARS-CoV-2 nucleic acid in air samples, but only one study has successfully recovered viable virus, although it is limited by its small sample size.

We aimed to determine the extent of shedding of viable SARS-CoV-2 in respiratory aerosols from COVID-19 patients.

In this observational air sampling study, air samples from airborne-infection isolation rooms (AIIRs) and a community isolation facility (CIF) housing COVID-19 patients were collected using a water vapor condensation method into liquid collection media. Samples were tested for presence of SARS-CoV-2 nucleic acid using quantitative real-time polymerase chain reaction (qRT-PCR), and qRT-PCR-positive samples were tested for viability using viral culture.

Samples from 6 (50%) of the 12 sampling cycles in hospital rooms were positive for SARS-CoV-2 RNA, including aerosols ranging from <1 µm to >4 µm in diameter. Of 9 samples from the CIF, 1 was positive via qRT-PCR. Viral RNA concentrations ranged from 179 to 2,738 ORF1ab gene copies per cubic meter of air. Virus cultures were negative after 4 blind passages.

Although SARS-CoV-2 is readily captured in aerosols, virus culture remains challenging despite optimized sampling methodologies to preserve virus viability. Further studies on aerosol-based transmission and control of SARS-CoV-2 are needed.