Nasal Iodophor Antiseptic vs Nasal Mupirocin Antibiotic in the Setting of Chlorhexidine Bathing to Prevent Infections in Adult ICUs: A Randomized Clinical Trial

Importance

Universal nasal mupirocin plus chlorhexidine gluconate (CHG) bathing in intensive care units (ICUs) prevents methicillin-resistant Staphylococcus aureus (MRSA) infections and all-cause bloodstream infections. Antibiotic resistance to mupirocin has raised questions about whether an antiseptic could be advantageous for ICU decolonization.

Objective

To compare the effectiveness of iodophor vs mupirocin for universal ICU nasal decolonization in combination with CHG bathing.

Design, Setting, and Participants

Two-group noninferiority, pragmatic, cluster-randomized trial conducted in US community hospitals, all of which used mupirocin-CHG for universal decolonization in ICUs at baseline. Adult ICU patients in 137 randomized hospitals during baseline (May 1, 2015-April 30, 2017) and intervention (November 1, 2017-April 30, 2019) were included.

Intervention

Universal decolonization involving switching to iodophor-CHG (intervention) or continuing mupirocin-CHG (baseline).

Main Outcomes and Measures

ICU-attributable S aureus clinical cultures (primary outcome), MRSA clinical cultures, and all-cause bloodstream infections were evaluated using proportional hazard models to assess differences from baseline to intervention periods between the strategies. Results were also compared with a 2009-2011 trial of mupirocin-CHG vs no decolonization in the same hospital network. The prespecified noninferiority margin for the primary outcome was 10%.

Results

Among the 801 668 admissions in 233 ICUs, the participants' mean (SD) age was 63.4 (17.2) years, 46.3% were female, and the mean (SD) ICU length of stay was 4.8 (4.7) days. Hazard ratios (HRs) for S aureus clinical isolates in the intervention vs baseline periods were 1.17 for iodophor-CHG (raw rate: 5.0 vs 4.3/1000 ICU-attributable days) and 0.99 for mupirocin-CHG (raw rate: 4.1 vs 4.0/1000 ICU-attributable days) (HR difference in differences significantly lower by 18.4% [95% CI, 10.7%-26.6%] for mupirocin-CHG, P < .001). For MRSA clinical cultures, HRs were 1.13 for iodophor-CHG (raw rate: 2.3 vs 2.1/1000 ICU-attributable days) and 0.99 for mupirocin-CHG (raw rate: 2.0 vs 2.0/1000 ICU-attributable days) (HR difference in differences significantly lower by 14.1% [95% CI, 3.7%-25.5%] for mupirocin-CHG, P = .007). For all-pathogen bloodstream infections, HRs were 1.00 (2.7 vs 2.7/1000) for iodophor-CHG and 1.01 (2.6 vs 2.6/1000) for mupirocin-CHG (nonsignificant HR difference in differences, -0.9% [95% CI, -9.0% to 8.0%]; P = .84). Compared with the 2009-2011 trial, the 30-day relative reduction in hazards in the mupirocin-CHG group relative to no decolonization (2009-2011 trial) were as follows: S aureus clinical cultures (current trial: 48.1% [95% CI, 35.6%-60.1%]; 2009-2011 trial: 58.8% [95% CI, 47.5%-70.7%]) and bloodstream infection rates (current trial: 70.4% [95% CI, 62.9%-77.8%]; 2009-2011 trial: 60.1% [95% CI, 49.1%-70.7%]).

Conclusions and Relevance

Nasal iodophor antiseptic did not meet criteria to be considered noninferior to nasal mupirocin antibiotic for the outcome of S aureus clinical cultures in adult ICU patients in the context of daily CHG bathing. In addition, the results were consistent with nasal iodophor being inferior to nasal mupirocin.

Trial Registration

ClinicalTrials.gov Identifier: NCT03140423.

Assessment of Hospital-Onset SARS-CoV-2 Infection Rates and Testing Practices in the US, 2020-2022

Importance

Characterizing the scale and factors associated with hospital-onset SARS-CoV-2 infections could help inform hospital and public health policies regarding prevention and surveillance needs for these infections.

Objective

To evaluate associations of hospital-onset SARS-CoV-2 infection rates with different periods of the COVID-19 pandemic, hospital characteristics, and testing practices.

Design, Setting, and Participants

This cohort study of US hospitals reporting SARS-CoV-2 testing data in the PINC AI Healthcare Database COVID-19 special release files was conducted from July 2020 through June 2022. Data were collected from hospitals that reported at least 1 SARS-CoV-2 reverse transcription-polymerase chain reaction or antigen test during hospitalizations discharged that month. For each hospital-month where the hospital reported sufficient data, all hospitalizations discharged in that month were included in the cohort. SARS-CoV-2 viral tests and results reported in the microbiology files for all hospitalizations in the study period by discharge month were identified. Data analysis was conducted from September 2022 to March 2023.

Exposure

Hospitalizations discharged in an included hospital-month.

Main Outcomes and Measures

Multivariable generalized estimating equation negative-binomial regression models were used to assess associations of monthly rates of hospital-onset SARS-CoV-2 infections per 1000 patient-days (defined as a first positive SARS-CoV-2 test during after hospitalization day 7) with the phase of the pandemic (defined as the predominant SARS-CoV-2 variant in circulation), admission testing rates, and hospital characteristics (hospital bed size, teaching status, urban vs rural designation, Census region, and patient distribution variables).

Results

A total of 5687 hospital-months from 288 distinct hospitals were included, which contributed 4 421 268 hospitalization records. Among 171 564 hospitalizations with a positive SARS-CoV-2 test, 7591 (4.4%) were found to be hospital onset and 6455 (3.8%) were indeterminate onset. The mean monthly hospital-onset infection rate per 1000 patient-days was 0.27 (95 CI, 0.26-0.29). Hospital-onset infections occurred in 2217 of 5687 hospital-months (39.0%). The monthly percentage of discharged patients tested for SARS-CoV-2 at admission varied; 1673 hospital-months (29.4%) had less than 25% of hospitalizations tested at admission; 2199 hospital-months (38.7%) had 25% to 50% of all hospitalizations tested, and 1815 hospital months (31.9%) had more than 50% of all hospitalizations tested at admission. Postadmission testing rates and community-onset infection rates increased with admission testing rates. In multivariable models restricted to hospital-months testing at least 25% of hospitalizations at admission, a 10% increase in community-onset SARS-CoV-2 infection rate was associated with a 178% increase in the hospital-onset infection rate (rate ratio, 2.78; 95% CI, 2.52-3.07). Additionally, the phase of the COVID-19 pandemic, the admission testing rate, Census region, and bed size were all significantly associated with hospital-onset SARS-CoV-2 infection rates.

Conclusions and Relevance

In this cohort study of hospitals reporting SARS-CoV-2 infections, there was an increase of hospital-onset SARS-CoV-2 infections when community-onset infections were higher, indicating a need for ongoing and enhanced surveillance and prevention efforts to reduce in-hospital transmission of SARS-CoV-2 infections, particularly when community-incidence of SARS-CoV-2 infections is high.

Changes in the Incidence of Invasive Bacterial Disease During the COVID-19 Pandemic in the United States, 2014-2020

BACKGROUND

Descriptions of changes in invasive bacterial disease (IBD) epidemiology during the coronavirus disease 2019 (COVID-19) pandemic in the United States are limited.

METHODS

We investigated changes in the incidence of IBD due to Streptococcus pneumoniae, Haemophilus influenzae, group A Streptococcus (GAS), and group B Streptococcus (GBS). We defined the COVID-19 pandemic period as 1 March to 31 December 2020. We compared observed IBD incidences during the pandemic to expected incidences, consistent with January 2014 to February 2020 trends. We conducted secondary analysis of a health care database to assess changes in testing by blood and cerebrospinal fluid (CSF) culture during the pandemic.

RESULTS

Compared with expected incidences, the observed incidences of IBD due to S. pneumoniae, H. influenzae, GAS, and GBS were 58%, 60%, 28%, and 12% lower during the pandemic period of 2020, respectively. Declines from expected incidences corresponded closely with implementation of COVID-19-associated nonpharmaceutical interventions (NPIs). Significant declines were observed across all age and race groups, and surveillance sites for S. pneumoniae and H. influenzae. Blood and CSF culture testing rates during the pandemic were comparable to previous years.

CONCLUSIONS

NPIs likely contributed to the decline in IBD incidence in the United States in 2020; observed declines were unlikely to be driven by reductions in testing.

Assessing Pathogen Transmission Opportunities: Variation in Nursing Home Staff-Resident Interactions

OBJECTIVES

The Centers for Disease Control and Prevention (CDC) recommends implementing Enhanced Barrier Precautions (EBP) for all nursing home (NH) residents known to be colonized with targeted multidrug-resistant organisms (MDROs), wounds, or medical devices. Differences in health care personnel (HCP) and resident interactions between units may affect risk of acquiring and transmitting MDROs, affecting EBP implementation. We studied HCP-resident interactions across a variety of NHs to characterize MDRO transmission opportunities.

DESIGN

2 cross-sectional visits.

SETTING AND PARTICIPANTS

Four CDC Epicenter sites and CDC Emerging Infection Program sites in 7 states recruited NHs with a mix of unit care types (≥30 beds or ≥2 units). HCP were observed providing resident care.

METHODS

Room-based observations and HCP interviews assessed HCP-resident interactions, care type provided, and equipment use. Observations and interviews were conducted for 7-8 hours in 3-6-month intervals per unit. Chart reviews collected deidentified resident demographics and MDRO risk factors (eg, indwelling devices, pressure injuries, and antibiotic use).

RESULTS

We recruited 25 NHs (49 units) with no loss to follow-up, conducted 2540 room-based observations (total duration: 405 hours), and 924 HCP interviews. HCP averaged 2.5 interactions per resident per hour (long-term care units) to 3.4 per resident per hour (ventilator care units). Nurses provided care to more residents (n = 12) than certified nursing assistants (CNAs) and respiratory therapists (RTs) (CNA: 9.8 and RT: 9) but nurses performed significantly fewer task types per interaction compared to CNAs (incidence rate ratio (IRR): 0.61, P < .05). Short-stay (IRR: 0.89) and ventilator-capable (IRR: 0.94) units had less varied care compared with long-term care units (P < .05), although HCP visited residents in these units at similar rates.

CONCLUSIONS AND IMPLICATIONS

Resident-HCP interaction rates are similar across NH unit types, differing primarily in types of care provided. Current and future interventions such as EBP, care bundling, or targeted infection prevention education should consider unit-specific HCP-resident interaction patterns.

Declines in the utilization of hospital-based care during COVID-19 pandemic

The disruptions of the coronavirus disease 2019 (COVID-19) pandemic impacted the delivery and utilization of healthcare services with potential long-term implications for population health and the hospital workforce. Using electronic health record data from over 700 US acute care hospitals, we documented changes in admissions to hospital service areas (inpatient, observation, emergency room [ER], and same-day surgery) during 2019-2020 and examined whether surges of COVID-19 hospitalizations corresponded with increased inpatient disease severity and death rate. We found that in 2020, hospitalizations declined by 50% in April, with greatest declines occurring in same-day surgery (-73%). The youngest patients (0-17) experienced largest declines in ER, observation, and same-day surgery admissions; inpatient admissions declined the most among the oldest patients (65+). Infectious disease admissions increased by 52%. The monthly measures of inpatient case mix index, length of stay, and non-COVID death rate were higher in all months in 2020 compared with respective months in 2019.

Comparison of the Risk of Recurrent Clostridioides Difficile Infections Among Patients in 2018 Versus 2013

Among persons with an initial Clostridioides difficile infection (CDI) across 10 US sites in 2018 compared with 2013, 18.3% versus 21.1% had ≥1 recurrent CDI (rCDI) within 180 days. We observed a 16% lower adjusted risk of rCDI in 2018 versus 2013 (P < .0001).

Antibiotic-Resistant Infections Among Inpatients with Coronavirus Disease 2019 (COVID-19) in US Hospitals

We described bacterial/fungal coinfections and antibiotic-resistant infections among inpatients with a diagnosis of coronavirus disease 2019 (COVID-19) and compared findings in those with a diagnosis of influenza like illness. Less than 10% of inpatients with COVID-19 had bacterial/fungal coinfection. Longer lengths of stay, critical care stay, and mechanical ventilation contribute to increased incidence of hospital-onset infections among inpatients with COVID-19.

Modeling the Effectiveness of Healthcare Personnel Reactive Testing and Screening for the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Omicron Variant Within Nursing Homes

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Omicron variant has been hypothesized to exhibit faster clearance (time from peak viral concentration to clearance of acute infection), decreased sensitivity of antigen tests, and increased immune escape (the ability of the variant to evade immunity conferred by past infection or vaccination) compared to prior variants. These factors necessitate reevaluation of prevention and control strategies, particularly in high-risk, congregate settings like nursing homes that have been heavily impacted by other coronavirus disease 2019 (COVID-19) variants. We used a simple model representing individual-level viral shedding dynamics to estimate the optimal strategy for testing nursing home healthcare personnel and quantify potential reduction in transmission of COVID-19. This provides a framework for prospectively evaluating testing strategies in emerging variant scenarios when data are limited. We find that case-initiated testing prevents 38% of transmission within a facility if implemented within a day of an index case testing positive, and screening testing strategies could prevent 30% to 78% of transmission within a facility if implemented daily, depending on test sensitivity.

Improving mathematical modeling of interventions to prevent healthcare-associated infections by interrupting transmission or pathogens: How common modeling assumptions about colonized individuals impact intervention effectiveness estimates

Mathematical models are used to gauge the impact of interventions for healthcare-associated infections. As with any analytic method, such models require many assumptions. Two common assumptions are that asymptomatically colonized individuals are more likely to be hospitalized and that they spend longer in the hospital per admission because of their colonization status. These assumptions have no biological basis and could impact the estimated effects of interventions in unintended ways. Therefore, we developed a model of methicillin-resistant Staphylococcus aureus transmission to explicitly evaluate the impact of these assumptions. We found that assuming that asymptomatically colonized individuals were more likely to be admitted to the hospital or spend longer in the hospital than uncolonized individuals biased results compared to a more realistic model that did not make either assumption. Results were heavily biased when estimating the impact of an intervention that directly reduced transmission in a hospital. In contrast, results were moderately biased when estimating the impact of an intervention that decolonized hospital patients. Our findings can inform choices modelers face when constructing models of healthcare-associated infection interventions and thereby improve their validity.

Stopping Hospital Infections With Environmental Services (SHINE): A Cluster-randomized Trial of Intensive Monitoring Methods for Terminal Room Cleaning on Rates of Multidrug-resistant Organisms in the Intensive Care Unit

BACKGROUND

Multidrug-resistant organisms (MDROs) frequently contaminate hospital environments. We performed a multicenter, cluster-randomized, crossover trial of 2 methods for monitoring of terminal cleaning effectiveness.

METHODS

Six intensive care units (ICUs) at 3 medical centers received both interventions sequentially, in randomized order. Ten surfaces were surveyed each in 5 rooms weekly, after terminal cleaning, with adenosine triphosphate (ATP) monitoring or an ultraviolet fluorescent marker (UV/F). Results were delivered to environmental services staff in real time with failing surfaces recleaned. We measured monthly rates of MDRO infection or colonization, including methicillin-resistant Staphylococcus aureus, Clostridioides difficile, vancomycin-resistant Enterococcus, and MDR gram-negative bacilli (MDR-GNB) during a 12-month baseline period and sequential 6-month intervention periods, separated by a 2-month washout. Primary analysis compared only the randomized intervention periods, whereas secondary analysis included the baseline.

RESULTS

The ATP method was associated with a reduction in incidence rate of MDRO infection or colonization compared with the UV/F period (incidence rate ratio [IRR] 0.876; 95% confidence interval [CI], 0.807-0.951; P = .002). Including the baseline period, the ATP method was associated with reduced infection with MDROs (IRR 0.924; 95% CI, 0.855-0.998; P = .04), and MDR-GNB infection or colonization (IRR 0.856; 95% CI, 0.825-0.887; P < .001). The UV/F intervention was not associated with a statistically significant impact on these outcomes. Room turnaround time increased by a median of 1 minute with the ATP intervention and 4.5 minutes with UV/F compared with baseline.

CONCLUSIONS

Intensive monitoring of ICU terminal room cleaning with an ATP modality is associated with a reduction of MDRO infection and colonization.

Factors influencing environmental sampling recovery of healthcare pathogens from non-porous surfaces with cellulose sponges

Results from sampling healthcare surfaces for pathogens are difficult to interpret without understanding the factors that influence pathogen detection. We investigated the recovery of four healthcare-associated pathogens from three common surface materials, and how a body fluid simulant (artificial test soil, ATS), deposition method, and contamination levels influence the percent of organisms recovered (%R). Known quantities of carbapenemase-producing KPC+ Klebsiella pneumoniae (KPC), Acinetobacter baumannii, vancomycin-resistant Enterococcus faecalis, and Clostridioides difficile spores (CD) were suspended in Butterfield's buffer or ATS, deposited on 323cm2 steel, plastic, and laminate surfaces, allowed to dry 1h, then sampled with a cellulose sponge wipe. Bacteria were eluted, cultured, CFU counted and %R determined relative to the inoculum. The %R varied by organism, from <1% (KPC) to almost 60% (CD) and was more dependent upon the organism's characteristics and presence of ATS than on surface type. KPC persistence as determined by culture also declined by >1 log10 within the 60 min drying time. For all organisms, the %R was significantly greater if suspended in ATS than if suspended in Butterfield's buffer (p<0.05), and for most organisms the %R was not significantly different when sampled from any of the three surfaces. Organisms deposited in multiple droplets were recovered at equal or higher %R than if spread evenly on the surface. This work assists in interpreting data collected while investigating a healthcare infection outbreak or while conducting infection intervention studies.

Epidemiology, Outcomes, and Trends of Patients With Sepsis and Opioid-Related Hospitalizations in U.S. Hospitals

OBJECTIVES

Widespread use and misuse of prescription and illicit opioids have exposed millions to health risks including serious infectious complications. Little is known, however, about the association between opioid use and sepsis.

DESIGN

Retrospective cohort study.

SETTING

About 373 U.S. hospitals.

PATIENTS

Adults hospitalized between January 2009 and September 2015.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Sepsis was identified by clinical indicators of concurrent infection and organ dysfunction. Opioid-related hospitalizations were identified by the International Classification of Diseases, 9th Revision, Clinical Modification codes and/or inpatient orders for buprenorphine. Clinical characteristics and outcomes were compared by sepsis and opioid-related hospitalization status. The association between opioid-related hospitalization and all-cause, in-hospital mortality in patients with sepsis was assessed using mixed-effects logistic models to adjust for baseline characteristics and severity of illness.The cohort included 6,715,286 hospitalizations; 375,479 (5.6%) had sepsis, 130,399 (1.9%) had opioid-related hospitalizations, and 8,764 (0.1%) had both. Compared with sepsis patients without opioid-related hospitalizations (n = 366,715), sepsis patients with opioid-related hospitalizations (n = 8,764) were younger (mean 52.3 vs 66.9 yr) and healthier (mean Elixhauser score 5.4 vs 10.5), had more bloodstream infections from Gram-positive and fungal pathogens (68.9% vs 47.0% and 10.6% vs 6.4%, respectively), and had lower in-hospital mortality rates (10.6% vs 16.2%; adjusted odds ratio, 0.73; 95% CI, 0.60-0.79; p < 0.001 for all comparisons). Of 1,803 patients with opioid-related hospitalizations who died in-hospital, 928 (51.5%) had sepsis. Opioid-related hospitalizations accounted for 1.5% of all sepsis-associated deaths, including 5.7% of sepsis deaths among patients less than 50 years old. From 2009 to 2015, the proportion of sepsis hospitalizations that were opioid-related increased by 77% (95% CI, 40.7-123.5%).

CONCLUSIONS

Sepsis is an important cause of morbidity and mortality in patients with opioid-related hospitalizations, and opioid-related hospitalizations contribute disproportionately to sepsis-associated deaths among younger patients. In addition to ongoing efforts to combat the opioid crisis, public health agencies should focus on raising awareness about sepsis among patients who use opioids and their providers.

Modeling Effectiveness of Testing Strategies to Prevent Coronavirus Disease 2019 (COVID-19) in Nursing Homes-United States, 2020

Background

SARS-CoV-2 outbreaks in nursing homes can be large with high case fatality. Identifying asymptomatic individuals early through serial testing is recommended to control COVID-19 in nursing homes, both in response to an outbreak (“outbreak testing” of residents and healthcare personnel) and in facilities without outbreaks (“non-outbreak testing” of healthcare personnel). The effectiveness of outbreak testing and isolation with or without non-outbreak testing was evaluated.

Methods

Using published SARS-CoV-2 transmission parameters, the fraction of SARS-CoV-2 transmissions prevented through serial testing (weekly, every three days, or daily) and isolation of asymptomatic persons compared to symptom-based testing and isolation was evaluated through mathematical modeling using a Reed-Frost model to estimate the percentage of cases prevented (i.e., “effectiveness”) through either outbreak testing alone or outbreak plus non-outbreak testing. The potential effect of simultaneous decreases (by 10%) in the effectiveness of isolating infected individuals when instituting testing strategies was also evaluated.

Results

Modeling suggests that outbreak testing could prevent 54% (weekly testing with 48-hour test turnaround) to 92% (daily testing with immediate results and 50% relative sensitivity) of SARS-CoV-2 infections. Adding non-outbreak testing could prevent up to an additional 8% of SARS-CoV-2 infections (depending on test frequency and turnaround time). However, added benefits of non-outbreak testing were mostly negated if accompanied by decreases in infection control practice.

Conclusions

When combined with high-quality infection control practices, outbreak testing could be an effective approach to preventing COVID-19 in nursing homes, particularly if optimized through increased test frequency and use of tests with rapid turnaround.

Performance Evaluation of Serial SARS-CoV-2 Rapid Antigen Testing During a Nursing Home Outbreak

BACKGROUND

To address high COVID-19 burden in U.S. nursing homes, rapid SARS-CoV-2 antigen tests have been widely distributed in those facilities. However, performance data are lacking, especially in asymptomatic people.

OBJECTIVE

To evaluate the performance of SARS-CoV-2 antigen testing when used for facility-wide testing during a nursing home outbreak.

DESIGN

A prospective evaluation involving 3 facility-wide rounds of testing where paired respiratory specimens were collected to evaluate the performance of the BinaxNOW antigen test compared with virus culture and real-time reverse transcription polymerase chain reaction (RT-PCR). Early and late infection were defined using changes in RT-PCR cycle threshold values and prior test results.

SETTING

A nursing home with an ongoing SARS-CoV-2 outbreak.

PARTICIPANTS

532 paired specimens collected from 234 available residents and staff.

MEASUREMENTS

Percentage of positive agreement (PPA) and percentage of negative agreement (PNA) for BinaxNOW compared with RT-PCR and virus culture.

RESULTS

BinaxNOW PPA with virus culture, used for detection of replication-competent virus, was 95%. However, the overall PPA of antigen testing with RT-PCR was 69%, and PNA was 98%. When only the first positive test result was analyzed for each participant, PPA of antigen testing with RT-PCR was 82% among 45 symptomatic people and 52% among 343 asymptomatic people. Compared with RT-PCR and virus culture, the BinaxNOW test performed well in early infection (86% and 95%, respectively) and poorly in late infection (51% and no recovered virus, respectively).

LIMITATION

Accurate symptom ascertainment was challenging in nursing home residents; test performance may not be representative of testing done by nonlaboratory staff.

CONCLUSION

Despite lower positive agreement compared with RT-PCR, antigen test positivity had higher agreement with shedding of replication-competent virus. These results suggest that antigen testing could be a useful tool to rapidly identify contagious people at risk for transmitting SARS-CoV-2 during nascent outbreaks and help reduce COVID-19 burden in nursing homes.

PRIMARY FUNDING SOURCE

None.

Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States

Provision of safe drinking water in the United States is a great public health achievement. However, new waterborne disease challenges have emerged (e.g., aging infrastructure, chlorine-tolerant and biofilm-related pathogens, increased recreational water use). Comprehensive estimates of the health burden for all water exposure routes (ingestion, contact, inhalation) and sources (drinking, recreational, environmental) are needed. We estimated total illnesses, emergency department (ED) visits, hospitalizations, deaths, and direct healthcare costs for 17 waterborne infectious diseases. About 7.15 million waterborne illnesses occur annually (95% credible interval [CrI] 3.88 million–12.0 million), results in 601,000 ED visits (95% CrI 364,000–866,000), 118,000 hospitalizations (95% CrI 86,800–150,000), and 6,630 deaths (95% CrI 4,520–8,870) and incurring US $3.33 billion (95% CrI 1.37 billion–8.77 billion) in direct healthcare costs. Otitis externa and norovirus infection were the most common illnesses. Most hospitalizations and deaths were caused by biofilm-associated pathogens (nontuberculous mycobacteria, Pseudomonas, Legionella), costing US $2.39 billion annually.

Evaluating the Presence of Replication-Competent SARS-CoV-2 from Nursing Home Residents with Persistently Positive RT-PCR Results

Replication-competent virus has not been detected in individuals with mild to moderate COVID-19 more than 10 days after symptom onset. It is unknown whether these findings apply to nursing home residents. Of 273 specimens collected from nursing home residents >10 days from the initial positive test, none were culture positive.

Bacterial Infections Associated With Substance Use Disorders, Large Cohort of United States Hospitals, 2012-2017

BACKGROUND

Rises in the incidence of bacterial infections, such as infective endocarditis (IE), have been reported in conjunction with the opioid crisis. However, recent trends for IE and other serious infections among persons with substance use disorders (SUDs) are unknown.

METHODS

Using the Premier Healthcare Database, we identified hospitalizations from 2012 through 2017 among adults with primary discharge diagnoses of bacterial infections and secondary SUD diagnoses, using International Classification of Diseases, Clinical Modification Ninth and Tenth Revision codes. We calculated annual rates of infections with SUD diagnoses and evaluated temporal trends. Blood and cardiac tissue specimens were identified from IE hospitalizations to describe the microbiology distribution and temporal trends among hospitalizations with and without SUDs.

RESULTS

Among 72 481 weighted IE admissions recorded, SUD diagnoses increased from 19.9% in 2012 to 39.4% in 2017 (P < .0001). Hospitalizations with SUDs increased from 1.1 to 2.1 per 100 000 persons for IE, 1.4 to 2.4 per 100 000 persons for osteomyelitis, 0.5 to 0.9 per 100 000 persons for central nervous system abscesses, and 24.4 to 32.9 per 100 000 persons for skin and soft tissue infections. For adults aged 18-44 years, IE-SUD hospitalizations more than doubled, from 1.6 in 2012 to 3.6 in 2017 per 100 000 persons. Among all IE-SUD hospitalizations, 50.3% had a Staphylococcus aureus infection, compared with 19.4% of IE hospitalizations without SUDs.

CONCLUSIONS

Rates of hospitalization for serious infections among persons with SUDs are increasing, driven primarily by younger age groups. The differences in the microbiology of IE hospitalizations suggest that SUDs are changing the epidemiology of these infections.

Environmental Contamination of Contact Precaution and Non-Contact Precaution Patient Rooms in Six Acute Care Facilities

BACKGROUND

Environmental contamination is an important source of hospital multidrug-resistant organism (MDRO) transmission. Factors such as patient MDRO contact precautions (CP) status, patient proximity to surfaces, and unit type likely influence MDRO contamination and bacterial bioburden levels on patient room surfaces. Identifying factors associated with environmental contamination in patient rooms and on shared unit surfaces could help identify important environmental MDRO transmission routes.

METHODS

Surfaces were sampled from MDRO CP and non-CP rooms, nursing stations, and mobile equipment in acute care, intensive care, and transplant units within 6 acute care hospitals using a convenience sampling approach blinded to cleaning events. Precaution rooms had patients with clinical or surveillance tests positive for methicillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci, carbapenem-resistant Enterobacteriaceae or Acinetobacter within the previous 6 months, or Clostridioides difficile toxin within the past 30 days. Rooms not meeting this definition were considered non-CP rooms. Samples were cultured for the above MDROs and total bioburden.

RESULTS

Overall, an estimated 13% of rooms were contaminated with at least 1 MDRO. MDROs were detected more frequently in CP rooms (32% of 209 room-sample events) than non-CP rooms (12% of 234 room-sample events). Surface bioburden did not differ significantly between CP and non-CP rooms or MDRO-positive and MDRO-negative rooms.

CONCLUSIONS

CP room surfaces are contaminated more frequently than non-CP room surfaces; however, contamination of non-CP room surfaces is not uncommon and may be an important reservoir for ongoing MDRO transmission. MDRO contamination of non-CP rooms may indicate asymptomatic patient MDRO carriage, inadequate terminal cleaning, or cross-contamination of room surfaces via healthcare personnel hands.

Risk Factors Associated With SARS-CoV-2 Seropositivity Among US Health Care Personnel

IMPORTANCE

Risks for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care personnel (HCP) are unclear.

OBJECTIVE

To evaluate the risk factors associated with SARS-CoV-2 seropositivity among HCP with the a priori hypothesis that community exposure but not health care exposure was associated with seropositivity.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study was conducted among volunteer HCP at 4 large health care systems in 3 US states. Sites shared deidentified data sets, including previously collected serology results, questionnaire results on community and workplace exposures at the time of serology, and 3-digit residential zip code prefix of HCP. Site-specific responses were mapped to a common metadata set. Residential weekly coronavirus disease 2019 (COVID-19) cumulative incidence was calculated from state-based COVID-19 case and census data.

EXPOSURES

Model variables included demographic (age, race, sex, ethnicity), community (known COVID-19 contact, COVID-19 cumulative incidence by 3-digit zip code prefix), and health care (workplace, job role, COVID-19 patient contact) factors.

MAIN OUTCOME AND MEASURES

The main outcome was SARS-CoV-2 seropositivity. Risk factors for seropositivity were estimated using a mixed-effects logistic regression model with a random intercept to account for clustering by site.

RESULTS

Among 24 749 HCP, most were younger than 50 years (17 233 [69.6%]), were women (19 361 [78.2%]), were White individuals (15 157 [61.2%]), and reported workplace contact with patients with COVID-19 (12 413 [50.2%]). Many HCP worked in the inpatient setting (8893 [35.9%]) and were nurses (7830 [31.6%]). Cumulative incidence of COVID-19 per 10 000 in the community up to 1 week prior to serology testing ranged from 8.2 to 275.6; 20 072 HCP (81.1%) reported no COVID-19 contact in the community. Seropositivity was 4.4% (95% CI, 4.1%-4.6%; 1080 HCP) overall. In multivariable analysis, community COVID-19 contact and community COVID-19 cumulative incidence were associated with seropositivity (community contact: adjusted odds ratio [aOR], 3.5; 95% CI, 2.9-4.1; community cumulative incidence: aOR, 1.8; 95% CI, 1.3-2.6). No assessed workplace factors were associated with seropositivity, including nurse job role (aOR, 1.1; 95% CI, 0.9-1.3), working in the emergency department (aOR, 1.0; 95% CI, 0.8-1.3), or workplace contact with patients with COVID-19 (aOR, 1.1; 95% CI, 0.9-1.3).

CONCLUSIONS AND RELEVANCE

In this cross-sectional study of US HCP in 3 states, community exposures were associated with seropositivity to SARS-CoV-2, but workplace factors, including workplace role, environment, or contact with patients with known COVID-19, were not. These findings provide reassurance that current infection prevention practices in diverse health care settings are effective in preventing transmission of SARS-CoV-2 from patients to HCP.

National Estimates of Healthcare Costs Associated With Multidrug-Resistant Bacterial Infections Among Hospitalized Patients in the United States

Background

Treating patients with infections due to multidrug-resistant pathogens often requires substantial healthcare resources. The purpose of this study was to report estimates of the healthcare costs associated with infections due to multidrug-resistant bacteria in the United States (US).

Methods

We performed retrospective cohort studies of patients admitted for inpatient stays in the Department of Veterans Affairs healthcare system between January 2007 and October 2015. We performed multivariable generalized linear models to estimate the attributable cost by comparing outcomes in patients with and without positive cultures for multidrug-resistant bacteria. Finally, we multiplied these pathogen-specific, per-infection attributable cost estimates by national counts of infections due to each pathogen from patients hospitalized in a cohort of 722 US hospitals from 2017 to generate estimates of the population-level healthcare costs in the US attributable to these infections.

Results

Our analysis cohort consisted of 16 676 patients with community-onset infections and 172 712 matched controls and 8246 patients with hospital-onset infections and 66 939 matched controls. The highest cost was seen in hospital-onset invasive infections, with attributable costs (95% confidence intervals) ranging from $30 998 ($25 272–$36 724) for methicillin-resistant Staphylococcus aureus to $74 306 ($20 377–$128 235) for carbapenem-resistant (CR) Acinetobacter. The highest attributable costs for community-onset invasive infections were seen in CR Acinetobacter ($62 396; $20 370–$104 422). Treatment of these infections cost an estimated $4.6 billion ($4.1 billion–$5.1 billion) in 2017 in the US for community- and hospital-onset infections combined.

Conclusions

We found that antimicrobial-resistant infections led to substantial healthcare costs.

Signs, Symptoms, and Comorbidities Associated With Onset and Prognosis of COVID-19 in a Nursing Home

Background

Effective halting of outbreaks in skilled nursing facilities (SNFs) depends on the earliest recognition of cases. We assessed confirmed COVID-19 cases at an SNF impacted by COVID-19 in the United States to identify early indications of COVID-19 infection.

Methods

We performed retrospective reviews of electronic health records for residents with laboratory-confirmed SARS-CoV-2 during February 28–March 16, 2020. Records were abstracted for comorbidities, signs and symptoms, and illness outcomes during the 2 weeks before and after the date of positive specimen collection. Relative risks (RRs) of hospitalization and death were calculated.

Results

Of the 118 residents tested among approximately 130 residents from Facility A during February 28–March 16, 2020, 101 (86%) were found to test positive for SARS-CoV-2. At initial presentation, about two-thirds of SARS-CoV-2–positive residents had an abnormal vital sign or change in oxygen status. Most (90.2%) symptomatic residents had elevated temperature, change in mental status, lethargy, change in oxygen status, or cough; 9 (11.0%) did not have fever, cough, or shortness of breath during their clinical course. Those with change in oxygen status had an increased relative risk (RR) of 30-day mortality [51.1% vs 29.7%, RR 1.7, 95% confidence interval (CI) 1.0–3.0]. RR of hospitalization was higher for residents with underlying hepatic disease (1.6, 95% CI 1.1–2.2) or obesity (1.5, 95% CI 1.1–2.1); RR of death was not statistically significant.

Conclusions and Implications

Our findings reinforce the critical role that monitoring of signs and symptoms can have in identifying COVID-19 cases early. SNFs should ensure they have a systematic approach for responding to abnormal vital signs and oxygen saturation and consider ensuring common signs and symptoms identified in Facility A are among those they monitor.

Association Between Antibiotic Use and Hospital-onset Clostridioides difficile Infection in US Acute Care Hospitals, 2006-2012: An Ecologic Analysis

BACKGROUND

Unnecessary antibiotic use (AU) contributes to increased rates of Clostridioides difficile infection (CDI). The impact of antibiotic restriction on hospital-onset CDI (HO-CDI) has not been assessed in a large group of US acute care hospitals (ACHs).

METHODS

We examined cross-sectional and temporal associations between rates of hospital-level AU and HO-CDI using data from 549 ACHs. HO-CDI was defined as a discharge with a secondary International Classification of Diseases, Ninth Revision, Clinical Modification code for CDI (008.45), and treatment with metronidazole or oral vancomycin > 3 days after admission. Analyses were performed using multivariable generalized estimating equation models adjusting for patient and hospital characteristics.

RESULTS

During 2006-2012, the unadjusted annual rates of HO-CDI and total AU were 7.3 per 10 000 patient-days (PD) (95% confidence interval [CI], 7.1-7.5) and 811 days of therapy (DOT)/1000 PD (95% CI, 803-820), respectively. In the cross-sectional analysis, for every 50 DOT/1000 PD increase in total AU, there was a 4.4% increase in HO-CDI. For every 10 DOT/1000 PD increase in use of third- and fourth-generation cephalosporins or carbapenems, there was a 2.1% and 2.9% increase in HO-CDI, respectively. In the time-series analysis, the 6 ACHs with a ≥30% decrease in total AU had a 33% decrease in HO-CDI (rate ratio, 0.67 [95% CI, .47-.96]); ACHs with a ≥20% decrease in fluoroquinolone or third- and fourth-generation cephalosporin use had a corresponding decrease in HO-CDI of 8% and 13%, respectively.

CONCLUSIONS

At an ecologic level, reductions in total AU, use of fluoroquinolones, and use of third- and fourth-generation cephalosporins were each associated with decreased HO-CDI rates.

Transmission of SARS-CoV-2 Involving Residents Receiving Dialysis in a Nursing Home - Maryland, April 2020

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), can spread rapidly in nursing homes once it is introduced (1,2). To prevent outbreaks, more data are needed to identify sources of introduction and means of transmission within nursing homes. Nursing home residents who receive hemodialysis (dialysis) might be at higher risk for SARS-CoV-2 infections because of their frequent exposures outside the nursing home to both community dialysis patients and staff members at dialysis centers (3). Investigation of a COVID-19 outbreak in a Maryland nursing home (facility A) identified a higher prevalence of infection among residents undergoing dialysis (47%; 15 of 32) than among those not receiving dialysis (16%; 22 of 138) (p<0.001). Among residents with COVID-19, the 30-day hospitalization rate among those receiving dialysis (53%) was higher than that among residents not receiving dialysis (18%) (p = 0.03); the proportion of dialysis patients who died was 40% compared with those who did not receive dialysis (27%) (p = 0.42).Careful consideration of infection control practices throughout the dialysis process (e.g., transportation, time spent in waiting areas, spacing of machines, and cohorting), clear communication between nursing homes and dialysis centers, and coordination of testing practices between these sites are critical to preventing COVID-19 outbreaks in this medically vulnerable population.

Facility-Wide Testing for SARS-CoV-2 in Nursing Homes - Seven U.S. Jurisdictions, March-June 2020

Undetected infection with SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) contributes to transmission in nursing homes, settings where large outbreaks with high resident mortality have occurred (1,2). Facility-wide testing of residents and health care personnel (HCP) can identify asymptomatic and presymptomatic infections and facilitate infection prevention and control interventions (3-5). Seven state or local health departments conducted initial facility-wide testing of residents and staff members in 288 nursing homes during March 24-June 14, 2020. Two of the seven health departments conducted testing in 195 nursing homes as part of facility-wide testing all nursing homes in their state, which were in low-incidence areas (i.e., the median preceding 14-day cumulative incidence in the surrounding county for each jurisdiction was 19 and 38 cases per 100,000 persons); 125 of the 195 nursing homes had not reported any COVID-19 cases before the testing. Ninety-five of 22,977 (0.4%) persons tested in 29 (23%) of these 125 facilities had positive SARS-CoV-2 test results. The other five health departments targeted facility-wide testing to 93 nursing homes, where 13,443 persons were tested, and 1,619 (12%) had positive SARS-CoV-2 test results. In regression analyses among 88 of these nursing homes with a documented case before facility-wide testing occurred, each additional day between identification of the first case and completion of facility-wide testing was associated with identification of 1.3 additional cases. Among 62 facilities that could differentiate results by resident and HCP status, an estimated 1.3 HCP cases were identified for every three resident cases. Performing facility-wide testing immediately after identification of a case commonly identifies additional unrecognized cases and, therefore, might maximize the benefits of infection prevention and control interventions. In contrast, facility-wide testing in low-incidence areas without a case has a lower proportion of test positivity; strategies are needed to further optimize testing in these settings.

Outbreak Investigation of COVID-19 Among Residents and Staff of an Independent and Assisted Living Community for Older Adults in Seattle, Washington

IMPORTANCE

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused epidemic spread of coronavirus disease 2019 (COVID-19) in the Seattle, Washington, metropolitan area, with morbidity and mortality concentrated among residents of skilled nursing facilities. The prevalence of COVID-19 among older adults in independent/assisted living is not understood.

OBJECTIVES

To conduct surveillance for SARS-CoV-2 and describe symptoms of COVID-19 among residents and staff of an independent/assisted living community.

DESIGN, SETTING, AND PARTICIPANTS

In March 2020, public health surveillance of staff and residents was conducted on site at an assisted and independent living residence for older adults in Seattle, Washington, after exposure to 2 residents who were hospitalized with COVID-19.

EXPOSURES

Surveillance for SARS-CoV-2 infection in a congregate setting implementing social isolation and infection prevention protocols.

MAIN OUTCOMES AND MEASURES

SARS-CoV-2 real-time polymerase chain reaction was performed on nasopharyngeal swabs from residents and staff; a symptom questionnaire was completed assessing fever, cough, and other symptoms for the preceding 14 days. Residents were retested for SARS-CoV-2 7 days after initial screening.

RESULTS

Testing was performed on 80 residents; 62 were women (77%), with mean age of 86 (range, 69-102) years. SARS-CoV-2 was detected in 3 of 80 residents (3.8%); none felt ill, 1 male resident reported resolved cough and 1 loose stool during the preceding 14 days. Virus was also detected in 2 of 62 staff (3.2%); both were symptomatic. One week later, resident SARS-CoV-2 testing was repeated and 1 new infection detected (asymptomatic). All residents remained in isolation and were clinically stable 14 days after the second test.

CONCLUSIONS AND RELEVANCE

Detection of SARS-CoV-2 in asymptomatic residents highlights challenges in protecting older adults living in congregate settings. In this study, symptom screening failed to identify residents with infections and all 4 residents with SARS-CoV-2 remained asymptomatic after 14 days. Although 1 asymptomatic infection was found on retesting, a widespread facility outbreak was avoided. Compared with skilled nursing settings, in assisted/independent living communities, early surveillance to identify asymptomatic persons among residents and staff, in combination with adherence to recommended preventive strategies, may reduce viral spread.

Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can spread rapidly within skilled nursing facilities. After identification of a case of Covid-19 in a skilled nursing facility, we assessed transmission and evaluated the adequacy of symptom-based screening to identify infections in residents.

METHODS

We conducted two serial point-prevalence surveys, 1 week apart, in which assenting residents of the facility underwent nasopharyngeal and oropharyngeal testing for SARS-CoV-2, including real-time reverse-transcriptase polymerase chain reaction (rRT-PCR), viral culture, and sequencing. Symptoms that had been present during the preceding 14 days were recorded. Asymptomatic residents who tested positive were reassessed 7 days later. Residents with SARS-CoV-2 infection were categorized as symptomatic with typical symptoms (fever, cough, or shortness of breath), symptomatic with only atypical symptoms, presymptomatic, or asymptomatic.

RESULTS

Twenty-three days after the first positive test result in a resident at this skilled nursing facility, 57 of 89 residents (64%) tested positive for SARS-CoV-2. Among 76 residents who participated in point-prevalence surveys, 48 (63%) tested positive. Of these 48 residents, 27 (56%) were asymptomatic at the time of testing; 24 subsequently developed symptoms (median time to onset, 4 days). Samples from these 24 presymptomatic residents had a median rRT-PCR cycle threshold value of 23.1, and viable virus was recovered from 17 residents. As of April 3, of the 57 residents with SARS-CoV-2 infection, 11 had been hospitalized (3 in the intensive care unit) and 15 had died (mortality, 26%). Of the 34 residents whose specimens were sequenced, 27 (79%) had sequences that fit into two clusters with a difference of one nucleotide.

CONCLUSIONS

Rapid and widespread transmission of SARS-CoV-2 was demonstrated in this skilled nursing facility. More than half of residents with positive test results were asymptomatic at the time of testing and most likely contributed to transmission. Infection-control strategies focused solely on symptomatic residents were not sufficient to prevent transmission after SARS-CoV-2 introduction into this facility.

Symptom Screening at Illness Onset of Health Care Personnel With SARS-CoV-2 Infection in King County, Washington

This study assessed the spectrum of initial symptoms at the onset of polymerase chain reaction–confirmed coronavirus disease 2019 (COVID-19) among health care personnel in King County, Washington.

Epidemiology of Covid-19 in a Long-Term Care Facility in King County, Washington

BACKGROUND

Long-term care facilities are high-risk settings for severe outcomes from outbreaks of Covid-19, owing to both the advanced age and frequent chronic underlying health conditions of the residents and the movement of health care personnel among facilities in a region.

METHODS

After identification on February 28, 2020, of a confirmed case of Covid-19 in a skilled nursing facility in King County, Washington, Public Health-Seattle and King County, aided by the Centers for Disease Control and Prevention, launched a case investigation, contact tracing, quarantine of exposed persons, isolation of confirmed and suspected cases, and on-site enhancement of infection prevention and control.

RESULTS

As of March 18, a total of 167 confirmed cases of Covid-19 affecting 101 residents, 50 health care personnel, and 16 visitors were found to be epidemiologically linked to the facility. Most cases among residents included respiratory illness consistent with Covid-19; however, in 7 residents no symptoms were documented. Hospitalization rates for facility residents, visitors, and staff were 54.5%, 50.0%, and 6.0%, respectively. The case fatality rate for residents was 33.7% (34 of 101). As of March 18, a total of 30 long-term care facilities with at least one confirmed case of Covid-19 had been identified in King County.

CONCLUSIONS

In the context of rapidly escalating Covid-19 outbreaks, proactive steps by long-term care facilities to identify and exclude potentially infected staff and visitors, actively monitor for potentially infected patients, and implement appropriate infection prevention and control measures are needed to prevent the introduction of Covid-19.

Asymptomatic and Presymptomatic SARS-CoV-2 Infections in Residents of a Long-Term Care Skilled Nursing Facility - King County, Washington, March 2020

Older adults are susceptible to severe coronavirus disease 2019 (COVID-19) outcomes as a consequence of their age and, in some cases, underlying health conditions (1). A COVID-19 outbreak in a long-term care skilled nursing facility (SNF) in King County, Washington that was first identified on February 28, 2020, highlighted the potential for rapid spread among residents of these types of facilities (2). On March 1, a health care provider at a second long-term care skilled nursing facility (facility A) in King County, Washington, had a positive test result for SARS-CoV-2, the novel coronavirus that causes COVID-19, after working while symptomatic on February 26 and 28. By March 6, seven residents of this second facility were symptomatic and had positive test results for SARS-CoV-2. On March 13, CDC performed symptom assessments and SARS-CoV-2 testing for 76 (93%) of the 82 facility A residents to evaluate the utility of symptom screening for identification of COVID-19 in SNF residents. Residents were categorized as asymptomatic or symptomatic at the time of testing, based on the absence or presence of fever, cough, shortness of breath, or other symptoms on the day of testing or during the preceding 14 days. Among 23 (30%) residents with positive test results, 10 (43%) had symptoms on the date of testing, and 13 (57%) were asymptomatic. Seven days after testing, 10 of these 13 previously asymptomatic residents had developed symptoms and were recategorized as presymptomatic at the time of testing. The reverse transcription-polymerase chain reaction (RT-PCR) testing cycle threshold (Ct) values indicated large quantities of viral RNA in asymptomatic, presymptomatic, and symptomatic residents, suggesting the potential for transmission regardless of symptoms. Symptom-based screening in SNFs could fail to identify approximately half of residents with COVID-19. Long-term care facilities should take proactive steps to prevent introduction of SARS-CoV-2 (3). Once a confirmed case is identified in an SNF, all residents should be placed on isolation precautions if possible (3), with considerations for extended use or reuse of personal protective equipment (PPE) as needed (4).

Asymptomatic and Presymptomatic SARS-CoV-2 Infections in Residents of a Long-Term Care Skilled Nursing Facility - King County, Washington, March 2020

Older adults are susceptible to severe coronavirus disease 2019 (COVID-19) outcomes as a consequence of their age and, in some cases, underlying health conditions (1). A COVID-19 outbreak in a long-term care skilled nursing facility (SNF) in King County, Washington that was first identified on February 28, 2020, highlighted the potential for rapid spread among residents of these types of facilities (2). On March 1, a health care provider at a second long-term care skilled nursing facility (facility A) in King County, Washington, had a positive test result for SARS-CoV-2, the novel coronavirus that causes COVID-19, after working while symptomatic on February 26 and 28. By March 6, seven residents of this second facility were symptomatic and had positive test results for SARS-CoV-2. On March 13, CDC performed symptom assessments and SARS-CoV-2 testing for 76 (93%) of the 82 facility A residents to evaluate the utility of symptom screening for identification of COVID-19 in SNF residents. Residents were categorized as asymptomatic or symptomatic at the time of testing, based on the absence or presence of fever, cough, shortness of breath, or other symptoms on the day of testing or during the preceding 14 days. Among 23 (30%) residents with positive test results, 10 (43%) had symptoms on the date of testing, and 13 (57%) were asymptomatic. Seven days after testing, 10 of these 13 previously asymptomatic residents had developed symptoms and were recategorized as presymptomatic at the time of testing. The reverse transcription-polymerase chain reaction (RT-PCR) testing cycle threshold (Ct) values indicated large quantities of viral RNA in asymptomatic, presymptomatic, and symptomatic residents, suggesting the potential for transmission regardless of symptoms. Symptom-based screening in SNFs could fail to identify approximately half of residents with COVID-19. Long-term care facilities should take proactive steps to prevent introduction of SARS-CoV-2 (3). Once a confirmed case is identified in an SNF, all residents should be placed on isolation precautions if possible (3), with considerations for extended use or reuse of personal protective equipment (PPE) as needed (4).

Multidrug-Resistant Bacterial Infections in U.S. Hospitalized Patients, 2012-2017

BACKGROUND

Multidrug-resistant (MDR) bacteria that are commonly associated with health care cause a substantial health burden. Updated national estimates for this group of pathogens are needed to inform public health action.

METHODS

Using data from patients hospitalized in a cohort of 890 U.S. hospitals during the period 2012-2017, we generated national case counts for both hospital-onset and community-onset infections caused by methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococcus (VRE), extended-spectrum cephalosporin resistance in Enterobacteriaceae suggestive of extended-spectrum beta-lactamase (ESBL) production, carbapenem-resistant Enterobacteriaceae, carbapenem-resistant acinetobacter species, and MDR Pseudomonas aeruginosa.

RESULTS

The hospital cohort in the study accounted for 41.6 million hospitalizations (>20% of U.S. hospitalizations annually). The overall rate of clinical cultures was 292 cultures per 1000 patient-days and was stable throughout the time period. In 2017, these pathogens caused an estimated 622,390 infections (95% confidence interval [CI], 579,125 to 665,655) among hospitalized patients. Of these infections, 517,818 (83%) had their onset in the community, and 104,572 (17%) had their onset in the hospital. MRSA and ESBL infections accounted for the majority of the infections (52% and 32%, respectively). Between 2012 and 2017, the incidence decreased for MRSA infection (from 114.18 to 93.68 cases per 10,000 hospitalizations), VRE infection (from 24.15 to 15.76 per 10,000), carbapenem-resistant acinetobacter species infection (from 3.33 to 2.47 per 10,000), and MDR P. aeruginosa infection (from 13.10 to 9.43 per 10,000), with decreases ranging from -20.5% to -39.2%. The incidence of carbapenem-resistant Enterobacteriaceae infection did not change significantly (from 3.36 to 3.79 cases per 10,000 hospitalizations). The incidence of ESBL infection increased by 53.3% (from 37.55 to 57.12 cases per 10,000 hospitalizations), a change driven by an increase in community-onset cases.

CONCLUSIONS

Health care-associated antimicrobial resistance places a substantial burden on patients in the United States. Further work is needed to identify improved interventions for both the inpatient and outpatient settings. (Funded by the Centers for Disease Control and Prevention.).

COVID-19 in a Long-Term Care Facility - King County, Washington, February 27-March 9, 2020

On February 28, 2020, a case of coronavirus disease (COVID-19) was identified in a woman resident of a long-term care skilled nursing facility (facility A) in King County, Washington.* Epidemiologic investigation of facility A identified 129 cases of COVID-19 associated with facility A, including 81 of the residents, 34 staff members, and 14 visitors; 23 persons died. Limitations in effective infection control and prevention and staff members working in multiple facilities contributed to intra- and interfacility spread. COVID-19 can spread rapidly in long-term residential care facilities, and persons with chronic underlying medical conditions are at greater risk for COVID-19-associated severe disease and death. Long-term care facilities should take proactive steps to protect the health of residents and preserve the health care workforce by identifying and excluding potentially infected staff members and visitors, ensuring early recognition of potentially infected patients, and implementing appropriate infection control measures.

Sample Size Estimates for Cluster-Randomized Trials in Hospital Infection Control and Antimicrobial Stewardship

IMPORTANCE

An important step in designing, executing, and evaluating cluster-randomized trials (CRTs) is understanding the correlation and thus nonindependence that exists among individuals in a cluster. In hospital epidemiology, there is a shortage of CRTs that have published their intraclass correlation coefficient or coefficient of variation (CV), making prospective sample size calculations difficult for investigators.

OBJECTIVES

To estimate the number of hospitals needed to power parallel CRTs of interventions to reduce health care-associated infection outcomes and to demonstrate how different parameters such as CV and expected effect size are associated with the sample size estimates in practice.

DESIGN, SETTING, AND PARTICIPANTS

This longitudinal cohort study estimated parameters for sample size calculations using national rates developed by the Centers for Disease Control and Prevention for methicillin-resistant Staphylococcus aureus (MRSA) bacteremia, central-line-associated bloodstream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), and Clostridium difficile infections (CDI) from 2016. For MRSA and vancomycin-resistant enterococci (VRE) acquisition, outcomes were estimated using data from 2012 from the Benefits of Universal Glove and Gown study. Data were collected from June 2017 through September 2018 and analyzed from September 2018 through January 2019.

MAIN OUTCOMES AND MEASURES

Calculated number of clusters needed for adequate power to detect an intervention effect using a 2-group parallel CRT.

RESULTS

To study an intervention with a 30% decrease in daily rates, 73 total clusters were needed (37 in the intervention group and 36 in the control group) for MRSA bacteremia, 82 for CAUTI, 60 for CLABSI, and 31 for CDI. If a 10% decrease in rates was expected, 768 clusters were needed for MRSA bacteremia, 875 for CAUTI, 631 for CLABSI, and 329 for CDI. For MRSA or VRE acquisition, 50 or 40 total clusters, respectively, were required to observe a 30% decrease, whereas 540 or 426 clusters, respectively, were required to detect a 10% decrease.

CONCLUSIONS AND RELEVANCE

This study suggests that large sample sizes are needed to appropriately power parallel CRTs targeting infection prevention outcomes. Sample sizes are most associated with expected effect size and CV of hospital rates.

Improving the Use of Personal Protective Equipment: Applying Lessons Learned

Unrecognized transmission of pathogens in healthcare settings can lead to colonization and infection of both patients and healthcare personnel. The use of personal protective equipment (PPE) is an important strategy to protect healthcare personnel from contamination and to prevent the spread of pathogens to subsequent patients. However, optimal PPE use is difficult, and healthcare personnel may alter delivery of care because of the PPE. Here, we summarize recent research from the Prevention Epicenters Program on healthcare personnel contamination and improvement of the routine use of PPE as well as Ebola-specific PPE. Future efforts to optimize the use of PPE should include increasing adherence to protocols for PPE use, improving PPE design, and further research into the risks, benefits, and best practices of PPE use.

2147. Sample Size Estimates for Cluster Randomized Trials in Infection Control and Antimicrobial Stewardship

Background

Cluster randomized control trials (CRCTs) are used frequently in the field of infection control and antimicrobial stewardship because randomization at the patient level is often not feasible due to contamination, ethical, or logistical issues. The correlation and thus non-independence that exists among individual patients in a cluster must be accounted for when estimating sample size for such trials, yet many studies neglect to consider or report the intracluster correlation coefficient (ICC) and the resulting coefficient of variation (CV) in rates between hospitals. The aim of this study was to estimate the sample sizes needed to adequately power studies of hospital-level interventions to reduce rates of healthcare-associated infections.

Methods

We calculated the minimum number of clusters or hospitals that would need to be included in a study to have good power to detect an impact of the intervention given a range of different assumptions. We estimated parameters needed for these calculations using national rates from the National Healthcare Safety Network (NHSN) for methicillin-resistant Staphylococcus aureus (MRSA) bacteremia, central-line associated bloodstream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), C. difficile infections (CDI) and variation between hospitals in these rates. These calculations were based on the assumption that hospitals were uniform and moderate in size and were studied for 1 year.

Results

To study an intervention leading to a 50% decrease in daily rates and using the C vs. calculated from NHSN, 22 average-sized hospitals for MRSA bacteremia are needed, 34 for CAUTI, 9 for CDI, and 27 for CLABSI to have a statistically significant decrease with a type I error rate of 0.05 and a type II error rate of 0.8. If a 10% decrease in rates is expected instead, 709, 1205, 279, and 866 hospitals, respectively, are needed.

Conclusion

Sample size estimates for CRCTs are most influenced by the CV and the expected effect size. Given the large sample size requirements, it is likely that many CRCTs in hospital epidemiology are under-powered. We hope that these findings lead to more definitive CRCTs in the field of hospital epidemiology that are properly powered and more studies reporting their ICC or CV.

Disclosures

All authors: No reported disclosures.

519. Longer Length of Antibiotic Therapy for Community-Acquired Pneumonia and Risk of Clostridium difficile Infection

Background

Methods

Results

Conclusion

Disclosures

287. The Attributable Mortality of Prosthetic Joint Infection After Primary Hip and Knee Arthroplasty Among Medicare Beneficiaries, 2005–2012

Background

Total hip (THA) and total knee (TKA) arthroplasty are the most common elective surgical procedures performed in the USA. Most are performed in older adults and lead to improved quality of life; however, complications such as prosthetic joint infection (PJI) can occur. Little is known regarding the mortality attributable to PJI after THA or TKA.

Methods

Claims data from the 2004 to 2012 Medicare 5% sample Standard Analytic Files were used to find eligible beneficiaries, with ICD-9-CM procedure codes identifying primary THA (81.51) or primary TKA (81.54), and diagnosis code 996.66 indicating PJI during the year following the procedure. Inclusion criteria included traditional Medicare coverage during the year prior and two years following the procedure and original reason for entitlement due to age. Exclusion criteria included missing surgery date, additional primary procedures within 1 year, and PJI diagnosis prior or during index stay. The attributable mortality of PJI during the 2 years following primary hip and knee arthroplasty among Medicare beneficiaries was calculated by fitting Kaplan–Meier survival curves and performing a time-dependent analysis based on PJI timing using an Extended Cox Proportion Hazard model.

Results

A total of 248,340 hip and knee arthroplasties were performed on 5% Medicare sample beneficiaries between 2005 and 2012. The final cohort included 117,515 arthroplasties: 37,098 (32%) hip and 80,429 (68%) knee, of which 80,377 (68%) were performed in women and 61,807 (53%) in patients greater than 75 years of age. PJI was diagnosed in one percent of hip (n = 338) and knee (n = 726) arthroplasties, of which 112 (11%) died. The crude mortality rate was 3.2 (95% CI: 2.3,4.2) and 3.7 (95% CI: 2.9,4.8) times greater in patients with PJI than without PJI following THA and TKA, respectively. Controlling for comorbid conditions and the time-dependent nature of PJI, the risk of death with PJI was 2.5 (95% CI: 1.9,3.3) times higher following THA and 2.6 (95% CI: 2.0,4.3) times higher following TKA than for non-PJI.

Conclusion

Medicare beneficiaries who develop PJI after THA or TKA have an increased risk of death during the first 2 years following the procedure, supporting the importance of better understanding risk factors and preventing PJI following these elective procedures.

Disclosures

All authors: No reported disclosures.

Outbreaks Associated with Treated Recreational Water - United States, 2000-2014

Outbreaks associated with exposure to treated recreational water can be caused by pathogens or chemicals in venues such as pools, hot tubs/spas, and interactive water play venues (i.e., water playgrounds). During 2000-2014, public health officials from 46 states and Puerto Rico reported 493 outbreaks associated with treated recreational water. These outbreaks resulted in at least 27,219 cases and eight deaths. Among the 363 outbreaks with a confirmed infectious etiology, 212 (58%) were caused by Cryptosporidium (which causes predominantly gastrointestinal illness), 57 (16%) by Legionella (which causes Legionnaires' disease, a severe pneumonia, and Pontiac fever, a milder illness with flu-like symptoms), and 47 (13%) by Pseudomonas (which causes folliculitis ["hot tub rash"] and otitis externa ["swimmers' ear"]). Investigations of the 363 outbreaks identified 24,453 cases; 21,766 (89%) were caused by Cryptosporidium, 920 (4%) by Pseudomonas, and 624 (3%) by Legionella. At least six of the eight reported deaths occurred in persons affected by outbreaks caused by Legionella. Hotels were the leading setting, associated with 157 (32%) of the 493 outbreaks. Overall, the outbreaks had a bimodal temporal distribution: 275 (56%) outbreaks started during June-August and 46 (9%) in March. Assessment of trends in the annual counts of outbreaks caused by Cryptosporidium, Legionella, or Pseudomonas indicate mixed progress in preventing transmission. Pathogens able to evade chlorine inactivation have become leading outbreak etiologies. The consequent outbreak and case counts and mortality underscore the utility of CDC's Model Aquatic Health Code (https://www.cdc.gov/mahc) to prevent outbreaks associated with treated recreational water.

Vital Signs: Health Care-Associated Legionnaires' Disease Surveillance Data From 20 States and a Large Metropolitan Area-United States, 2015

BACKGROUND

Legionnaires' disease, a severe pneumonia, is typically acquired through inhalation of aerosolized water containing Legionella bacteria. Legionella can grow in the complex water systems of buildings, including health care facilities. Effective water management programs could prevent the growth of Legionella in building water systems.

METHODS

Using national surveillance data, Legionnaires' disease cases were characterized from the 21 jurisdictions (20 U.S. states and one large metropolitan area) that reported exposure information for ≥90% of 2015 Legionella infections. An assessment of whether cases were health care-associated was completed; definite health care association was defined as hospitalization or long-term care facility residence for the entire 10 days preceding symptom onset, and possible association was defined as any exposure to a health care facility for a portion of the 10 days preceding symptom onset. All other Legionnaires' disease cases were considered unrelated to health care.

RESULTS

A total of 2,809 confirmed Legionnaires' disease cases were reported from the 21 jurisdictions, including 85 (3%) definite and 468 (17%) possible health care-associated cases. Among the 21 jurisdictions, 16 (76%) reported 1-21 definite health care-associated cases per jurisdiction. Among definite health care-associated cases, the majority (75, 88%) occurred in persons aged ≥60 years, and exposures occurred at 72 facilities (15 hospitals and 57 long-term care facilities). The case fatality rate was 25% for definite and 10% for possible health care-associated Legionnaires' disease.

CONCLUSIONS AND IMPLICATIONS FOR PUBLIC HEALTH PRACTICE

Exposure to Legionella from health care facility water systems can result in Legionnaires' disease. The high case fatality rate of health care-associated Legionnaires' disease highlights the importance of case prevention and response activities, including implementation of effective water management programs and timely case identification.

Vital Signs: Health Care-Associated Legionnaires' Disease Surveillance Data from 20 States and a Large Metropolitan Area - United States, 2015

Background

Legionnaires’ disease, a severe pneumonia, is typically acquired through inhalation of aerosolized water containing Legionella bacteria. Legionella can grow in the complex water systems of buildings, including health care facilities. Effective water management programs could prevent the growth of Legionella in building water systems.

Methods

Using national surveillance data, Legionnaires’ disease cases were characterized from the 21 jurisdictions (20 U.S. states and one large metropolitan area) that reported exposure information for ≥90% of 2015 Legionella infections. An assessment of whether cases were health care–associated was completed; definite health care association was defined as hospitalization or long-term care facility residence for the entire 10 days preceding symptom onset, and possible association was defined as any exposure to a health care facility for a portion of the 10 days preceding symptom onset. All other Legionnaires’ disease cases were considered unrelated to health care.

Results

A total of 2,809 confirmed Legionnaires’ disease cases were reported from the 21 jurisdictions, including 85 (3%) definite and 468 (17%) possible health care–associated cases. Among the 21 jurisdictions, 16 (76%) reported 1–21 definite health care–associated cases per jurisdiction. Among definite health care–associated cases, the majority (75, 88%) occurred in persons aged ≥60 years, and exposures occurred at 72 facilities (15 hospitals and 57 long-term care facilities). The case fatality rate was 25% for definite and 10% for possible health care–associated Legionnaires’ disease.

Conclusions and Implications for Public Health Practice

Exposure to Legionella from health care facility water systems can result in Legionnaires’ disease. The high case fatality rate of health care–associated Legionnaires’ disease highlights the importance of case prevention and response activities, including implementation of effective water management programs and timely case identification.