Nursing home residents may be particularly vulnerable to coronavirus disease 2019 (COVID-19). Therefore, a question is when and how often nursing homes should test staff for COVID-19 and how this may change as severe acute respiratory coronavirus virus 2 (SARS-CoV-2) evolves.

We developed an agent-based model representing a typical nursing home, COVID-19 spread, and its health and economic outcomes to determine the clinical and economic value of various screening and isolation strategies and how it may change under various circumstances.

Under winter 2023–2024 SARS-CoV-2 omicron variant conditions, symptom-based antigen testing averted 4.5 COVID-19 cases compared to no testing, saving $191 in direct medical costs. Testing implementation costs far outweighed these savings, resulting in net costs of $990 from the Centers for Medicare & Medicaid Services perspective, $1,545 from the third-party payer perspective, and $57,155 from the societal perspective. Testing did not return sufficient positive health effects to make it cost-effective [$50,000 per quality-adjusted life-year (QALY) threshold], but it exceeded this threshold in ≥59% of simulation trials. Testing remained cost-ineffective when routinely testing staff and varying face mask compliance, vaccine efficacy, and booster coverage. However, all antigen testing strategies became cost-effective (≤$31,906 per QALY) or cost saving (saving ≤$18,372) when the severe outcome risk was ≥3 times higher than that of current omicron variants.

SARS-CoV-2 testing costs outweighed benefits under winter 2023–2024 conditions; however, testing became cost-effective with increasingly severe clinical outcomes. Cost-effectiveness can change as the epidemic evolves because it depends on clinical severity and other intervention use. Thus, nursing home administrators and policy makers should monitor and evaluate viral virulence and other interventions over time.

National validation of claims-based surveillance for surgical-site infections (SSIs) following colon surgery and abdominal hysterectomy.

Retrospective cohort study.

US hospitals selected for data validation by Centers for Medicare & Medicaid Services (CMS).

The study included 550 hospitals performing colon surgery and 458 hospitals performing abdominal hysterectomy in federal fiscal year 2013.

We requested 1,200 medical records from hospitals selected for validation as part of the CMS Hospital Inpatient Quality Reporting program. For colon surgery, we sampled 60% with a billing code suggestive of SSI during their index admission and/or readmission within 30 days and 40% who were readmitted without one of these codes. For abdominal hysterectomy, we included all patients with an SSI code during their index admission, all patients readmitted within 30 days, and a sample of those with a prolonged surgical admission (length of stay > 7 days). We calculated sensitivity and positive predictive value for the different groups.

We identified 142 colon-surgery SSIs (46 superficial SSIs and 96 deep and organ-space SSIs) and 127 abdominal-hysterectomy SSIs (58 superficial SSIs and 69 deep and organ-space SSIs). Extrapolating to the full CMS data validation cohort, we estimated an SSI rate of 8.3% for colon surgery and 3.0% for abdominal hysterectomy. Our colon-surgery surveillance codes identified 93% of SSIs, with 1 SSI identified for every 2.6 patients reviewed. Our abdominal-hysterectomy surveillance codes identified 73% of SSIs, with 1 SSI identified for every 1.6 patients reviewed.

Using claims to target record review for SSI validation performed well in a national sample.

Quantify the frequency and drivers of unreported coronavirus disease 2019 (COVID-19) symptoms among nursing home (NH) staff.

Confidential telephone survey.

The study was conducted in 70 NHs in Orange County, California, December 2020–February 2022.

The study included 120 NH staff with COVID-19.

We designed a 40-item telephone survey of NH staff to assess COVID-19 symptom reporting behavior and types of barriers [monetary, logistic, and emotional (fear or stigma)] and facilitators of symptom reporting using 5-point Likert scales. Summary statistics, reliability of survey constructs, and construct and discriminant validity were assessed.

Overall, 49% of surveys were completed during the 2020–2021 COVID-19 winter wave and 51% were completed during severe acute respiratory coronavirus virus 2 (SARS-CoV-2) δ (delta)/ (omicron) waves, with a relatively even distribution of certified nursing assistants, licensed vocational or registered nurses, and nonfrontline staff. Most COVID-19 cases (71%) were detected during mandated weekly NH surveillance testing and most staff (67%) had ≥1 symptom prior to their test. Only 34% of those with symptoms disclosed their symptom to a supervisor. Responses were consistent across 8 discrete survey constructs with Cronbach α > 0.70. In the first wave of the pandemic, fear and lack of knowledge were drivers of symptom reporting. In later waves, adequate staffing and sick days were drivers of symptom reporting. COVID-19 help lines and encouragement from supervisors facilitated symptom reporting and testing.

Mandatory COVID-19 testing for NH staff is key to identifying staff COVID-19 cases due to reluctance to speak up about existing symptoms. Active encouragement from supervisors to report symptoms and stay home when ill was a major driver of symptom reporting and resultant infection prevention and worker safety measures.

To compare strategies for hospital ranking based on colon surgical-site infection (SSI) rate by combining all colon procedures versus stratifying by surgical approach (ie, laparoscopic vs open).

Retrospective cohort study.

We identified SSIs among Medicare beneficiaries undergoing colon surgery from 2009 through 2013 using previously validated methods. We created a risk prediction model for SSI using age, sex, race, comorbidities, surgical approach (laparoscopy vs open), and concomitant colon and noncolon procedures. Adjusted SSI rates were used to rank hospitals. Subanalyses were performed for common colon procedures and procedure types for which there were both open and laparoscopic procedures. We generated ranks using only open and only laparoscopic procedures, overall and for each subanalysis. Rankings were compared using a Spearman correlation coefficient.

In total, 694,813 colon procedures were identified among 508,135 Medicare beneficiaries. The overall SSI rate was 7.6%. The laparoscopic approach was associated with lower SSI risk (OR, 0.5; 95% CI, 0.4–0.5), and higher SSI risk was associated with concomitant abdominal surgeries (OR, 1.4; 95% CI, 1.4–1.5) and higher Elixhauser score (OR, 1.1; 95% CI, 1.0–1.1). Hospital rankings for laparascopic procedures were poorly correlated with rankings for open procedures (r = 0.23).

Hospital rankings based on total colon procedures fail to account for differences in SSI risk from laparoscopic vs open procedures. Stratifying rankings by surgical approach yields a more equitable comparison of surgical performance.

To describe the genomic analysis and epidemiologic response related to a slow and prolonged methicillin-resistant Staphylococcus aureus (MRSA) outbreak.

Prospective observational study.

Neonatal intensive care unit (NICU).

We conducted an epidemiologic investigation of a NICU MRSA outbreak involving serial baby and staff screening to identify opportunities for decolonization. Whole-genome sequencing was performed on MRSA isolates.

A NICU with excellent hand hygiene compliance and longstanding minimal healthcare-associated infections experienced an MRSA outbreak involving 15 babies and 6 healthcare personnel (HCP). In total, 12 cases occurred slowly over a 1-year period (mean, 30.7 days apart) followed by 3 additional cases 7 months later. Multiple progressive infection prevention interventions were implemented, including contact precautions and cohorting of MRSA-positive babies, hand hygiene observers, enhanced environmental cleaning, screening of babies and staff, and decolonization of carriers. Only decolonization of HCP found to be persistent carriers of MRSA was successful in stopping transmission and ending the outbreak. Genomic analyses identified bidirectional transmission between babies and HCP during the outbreak.

In comparison to fast outbreaks, outbreaks that are “slow and sustained” may be more common to units with strong existing infection prevention practices such that a series of breaches have to align to result in a case. We identified a slow outbreak that persisted among staff and babies and was only stopped by identifying and decolonizing persistent MRSA carriage among staff. A repeated decolonization regimen was successful in allowing previously persistent carriers to safely continue work duties.

To characterize and compare severe acute respiratory coronavirus virus 2 (SARS-CoV-2)–specific immune responses in plasma and gingival crevicular fluid (GCF) from nursing home residents during and after natural infection.

Prospective cohort.

Nursing home.

SARS-CoV-2–infected nursing home residents.

A convenience sample of 14 SARS-CoV-2–infected nursing home residents, enrolled 4–13 days after real-time reverse transcription polymerase chain reaction diagnosis, were followed for 42 days. After diagnosis, plasma SARS-CoV-2–specific pan-Immunoglobulin (Ig), IgG, IgA, IgM, and neutralizing antibodies were measured at 5 time points, and GCF SARS-CoV-2–specific IgG and IgA were measured at 4 time points.

All participants demonstrated immune responses to SARS-CoV-2 infection. Among 12 phlebotomized participants, plasma was positive for pan-Ig and IgG in all 12 participants. Neutralizing antibodies were positive in 11 participants; IgM was positive in 10 participants, and IgA was positive in 9 participants. Among 14 participants with GCF specimens, GCF was positive for IgG in 13 participants and for IgA in 12 participants. Immunoglobulin responses in plasma and GCF had similar kinetics; median times to peak antibody response were similar across specimen types (4 weeks for IgG; 3 weeks for IgA). Participants with pan-Ig, IgG, and IgA detected in plasma and GCF IgG remained positive throughout this evaluation, 46–55 days after diagnosis. All participants were viral-culture negative by the first detection of antibodies.

Nursing home residents had detectable SARS-CoV-2 antibodies in plasma and GCF after infection. Kinetics of antibodies detected in GCF mirrored those from plasma. Noninvasive GCF may be useful for detecting and monitoring immunologic responses in populations unable or unwilling to be phlebotomized.

To assess the utility of an automated, statistically-based outbreak detection system to identify clusters of hospital-acquired microorganisms.

Multicenter retrospective cohort study.

The study included 43 hospitals using a common infection prevention surveillance system.

A space–time permutation scan statistic was applied to hospital microbiology, admission, discharge, and transfer data to identify clustering of microorganisms within hospital locations and services. Infection preventionists were asked to rate the importance of each cluster. A convenience sample of 10 hospitals also provided information about clusters previously identified through their usual surveillance methods.

We identified 230 clusters in 43 hospitals involving Gram-positive and -negative bacteria and fungi. Half of the clusters progressed after initial detection, suggesting that early detection could trigger interventions to curtail further spread. Infection preventionists reported that they would have wanted to be alerted about 81% of these clusters. Factors associated with clusters judged to be moderately or highly concerning included high statistical significance, large size, and clusters involving Clostridioides difficile or multidrug-resistant organisms. Based on comparison data provided by the convenience sample of hospitals, only 9 (18%) of 51 clusters detected by usual surveillance met statistical significance, and of the 70 clusters not previously detected, 58 (83%) involved organisms not routinely targeted by the hospitals’ surveillance programs. All infection prevention programs felt that an automated outbreak detection tool would improve their ability to detect outbreaks and streamline their work.

Automated, statistically-based outbreak detection can increase the consistency, scope, and comprehensiveness of detecting hospital-associated transmission.

To evaluate the National Health Safety Network (NHSN) hospital-onset Clostridioides difficile infection (HO-CDI) standardized infection ratio (SIR) risk adjustment for general acute-care hospitals with large numbers of intensive care unit (ICU), oncology unit, and hematopoietic cell transplant (HCT) patients.

Retrospective cohort study.

Eight tertiary-care referral general hospitals in California.

We used FY 2016 data and the published 2015 rebaseline NHSN HO-CDI SIR. We compared facility-wide inpatient HO-CDI events and SIRs, with and without ICU data, oncology and/or HCT unit data, and ICU bed adjustment.

For these hospitals, the median unmodified HO-CDI SIR was 1.24 (interquartile range [IQR], 1.15–1.34); 7 hospitals qualified for the highest ICU bed adjustment; 1 hospital received the second highest ICU bed adjustment; and all had oncology-HCT units with no additional adjustment per the NHSN. Removal of ICU data and the ICU bed adjustment decreased HO-CDI events (median, −25%; IQR, −20% to −29%) but increased the SIR at all hospitals (median, 104%; IQR, 90%–105%). Removal of oncology-HCT unit data decreased HO-CDI events (median, −15%; IQR, −14% to −21%) and decreased the SIR at all hospitals (median, −8%; IQR, −4% to −11%).

For tertiary-care referral hospitals with specialized ICUs and a large number of ICU beds, the ICU bed adjustor functions as a global adjustment in the SIR calculation, accounting for the increased complexity of patients in ICUs and non-ICUs at these facilities. However, the SIR decrease with removal of oncology and HCT unit data, even with the ICU bed adjustment, suggests that an additional adjustment should be considered for oncology and HCT units within general hospitals, perhaps similar to what is done for ICU beds in the current SIR.