Surveillance of central-line–associated bloodstream infections requires the labor-intensive counting of central-line days (CLDs). This workload could be reduced by sampling. Our objective was to evaluate the accuracy of various sampling strategies in the estimation of CLDs in intensive care units (ICUs) and to establish a set of rules to identify optimal sampling strategies depending on ICU characteristics.

Analyses of existing data collected according to the European protocol for patient-based surveillance of ICU-acquired infections in Belgium between 2004 and 2012.

CLD data were reported by 56 ICUs in 39 hospitals during 364 trimesters.

We compared estimated CLD data obtained from weekly and monthly sampling schemes with the observed exhaustive CLD data over the trimester by assessing the CLD percentage error (ie, observed CLDs – estimated CLDs/observed CLDs). We identified predictors of improved accuracy using linear mixed models.

When sampling once per week or 3 times per month, 80% of ICU trimesters had a CLD percentage error within 10%. When sampling twice per week, this was >90% of ICU trimesters. Sampling on Tuesdays provided the best estimations. In the linear mixed model, the observed CLD count was the best predictor for a smaller percentage error. The following sampling strategies provided an estimate within 10% of the actual CLD for 97% of the ICU trimesters with 90% confidence: 3 times per month in an ICU with >650 CLDs per trimester or each Tuesday in an ICU with >480 CLDs per trimester.

Sampling of CLDs provides an acceptable alternative to daily collection of CLD data.

Infect Control Hosp Epidemiol 2016;37:549–554

To understand the transmission dynamics of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) in a hospital outbreak to inform infection control actions.

Retrospective cohort study.

General medical and elderly inpatient wards in a hospital in England.

Coronavirus disease 2019 (COVID-19) patients were classified as community or healthcare associated by time from admission to onset or positivity using European Centre for Disease Prevention and Control definitions. COVID-19 symptoms were classified as asymptomatic, nonrespiratory, or respiratory. Infectiousness was calculated from 2 days prior to 14 days after symptom onset or positive test. Cases were defined as healthcare-associated COVID-19 when infection was acquired from the wards under investigation. COVID-19 exposures were calculated based on symptoms and bed proximity to an infectious patient. Risk ratios and adjusted odds ratios (aORs) were calculated from univariable and multivariable logistic regression.

Of 153 patients, 65 were COVID-19 patients and 45 of these were healthcare-associated cases. Exposure to a COVID-19 patient with respiratory symptoms was associated with healthcare-associated infection irrespective of proximity (aOR, 3.81; 95% CI, 1.6.3–8.87). Nonrespiratory exposure was only significant within 2.5 m (aOR, 5.21; 95% CI, 1.15–23.48). A small increase in risk ratio was observed for exposure to a respiratory patient for >1 day compared to 1 day from 2.04 (95% CI, 0.99–4.22) to 2.36 (95% CI, 1.44–3.88).

Respiratory exposure anywhere within a 4-bed bay was a risk, whereas nonrespiratory exposure required bed distance ≤2.5 m. Standard infection control measures required beds to be >2 m apart. Our findings suggest that this may be insufficient to stop SARS-CoV-2 transmission. We recommend improving cohorting and further studies into bed distance and transmission factors.

To evaluate the use of a perianal swab to detect CDI.

A perianal swab was collected from each inpatient with a positive stool sample for C. difficile (by polymerase chain reaction [PCR] test) and was tested for C. difficile by PCR and by culture. The variables evaluated included demographics, CDI severity, bathing before perianal swab collection, hours between stool sample and perianal swab, cycle threshold (Ct) to PCR positivity, and doses of CDI treatment before stool sample and before perianal swab.

Of 83 perianal swabs, 59 (71.1%) tested positive for C. difficile by PCR when perianal swabs were collected an average of 21 hours after the stool sample. Compared with the respective stool sample, the perianal sample was less likely to grow C. difficile (P=.005) and had a higher PCR Ct (P<.001). A direct, significant but weak correlation was detected between the Ct for a positive perianal sample and the respective stool sample (r=0.36; P=.006). An inverse dose relationship was detected between PCR positivity and CDI treatment doses before perianal swab collection (P=.27).

Perianal swabs are a simple method to detect C. difficile tcdB gene by PCR, with a sensitivity of 71%. These data were limited because stool samples and perianal swabs were not collected simultaneously. Compared with stool samples, the perianal Ct values and culture results were consistent with a lower bacterial load on the perianal sample due to the receipt of more CDI treatment before collection or unknown factors affecting perianal skin colonization.

Infect Control Hosp Epidemiol 2017;38:658–662

To determine the origin of grouped cases of Pneumocystis pneumonia in solid-organ transplant recipients at our institution.

A case series with clinical examinations, genotyping, and an epidemiological survey.

A university hospital in France.

We report 12 solid-organ transplant recipients with successive cases of Pneumocystis pneumonia that occurred over 3 years; 10 of these cases occurred in a single year.

We used molecular typing of P. jirovecii strains by multilocus sequence typing and clinical epidemiological survey to determine potential dates and places of transmission.

Between May 2014 and March 2015, 10 solid-organ transplant recipients (5 kidney transplants, 4 heart transplants, and 1 lung transplant) presented with Pneumocystis pneumonia. Molecular genotyping revealed the same P. jirovecii strain in at least 6 patients. This Pneumocystis strain was not identified in control patients (ie, nontransplant patients presenting with pulmonary pneumocystosis) during this period. The epidemiological survey guided by sequencing results provided information on the probable or possible dates and places of contamination for 5 of these patients. The mobile infectious diseases unit played a coordination role in the clinical management (adaptation of the local guidelines) and epidemiological survey.

Our cardiac and kidney transplant units experienced grouped cases of pulmonary pneumocystosis. Genotyping and epidemiological surveying results suggested interhuman contamination, which was quickly eliminated thanks to multidisciplinary coordination.

Infect Control Hosp Epidemiol 2017;38:179–185

To evaluate the impact of a coordinated approach for the isolation, diagnosis, and treatment of patients with tuberculosis.

Retrospective cohort study.

Bronx-Lebanon Hospital Center, an inner-city hospital in the South Bronx, New York City.

Patients with smear-positive, culture-confirmed pulmonary tuberculosis.

Institution of a coordinated tuberculosis team.

Admissions of 46 patients before and 39 patients after the formation of a tuberculosis team were reviewed. Before institution of the tuberculosis team, 35% of patients were isolated within 24 hours of presentation, 41% never were isolated, and the mean number of days patients were not isolated was 19. After implementation of the tuberculosis team, 59% of patients were isolated within 24 hours, only 5% were never isolated, and the mean number of days patients were not isolated was 3.5. These differences were statistically significant. There also was a corresponding decrease in length of hospitalization. In addition, there were noticeable improvements in patient and staff morale and attitudes.

The tuberculosis team likely has decreased the risk of nosocomial tuberculosis transmission by increasing the proportion of infectious tuberculosis patients admitted into AFB isolation and by reducing (by 780) the number of days out of isolation while smear positive. There also were concomitant financial savings.

Understand how the built environment can affect safety and efficiency outcomes during doffing of personal protective equipment (PPE) in the context of coronavirus disease 2019 (COVID-19) patient care.

We conducted (1) field observations and surveys administered to healthcare workers (HCWs) performing PPE doffing, (2) focus groups with HCWs and infection prevention experts, and (3) a with healthcare design experts.

This study was conducted in 4 inpatient units treating patients with COVID-19, in 3 hospitals of a single healthcare system.

The study included 24 nurses, 2 physicians, 1 respiratory therapist, and 2 infection preventionists.

The doffing task sequence and the layout of doffing spaces varied considerably across sites, with field observations showing most doffing tasks occurring around the patient room door and PPE support stations. Behaviors perceived as most risky included touching contaminated items and inadequate hand hygiene. Doffing space layout and types of PPE storage and work surfaces were often associated with inadequate cleaning and improper storage of PPE. Focus groups and the design charrette provided insights on how design affording standardization, accessibility, and flexibility can support PPE doffing safety and efficiency in this context.

There is a need to define, organize and standardize PPE doffing spaces in healthcare settings and to understand the environmental implications of COVID-19–specific issues related to supply shortage and staff workload. Low-effort and low-cost design adaptations of the layout and design of PPE doffing spaces may improve HCW safety and efficiency in existing healthcare facilities.