Measurement of SARS-CoV-2 in air and on surfaces in Scottish hospitals.

BACKGROUND: There are still uncertainties in our knowledge of the amount of SARS-CoV-2 virus present in the environment - where it can be found, and potential exposure determinants - limiting our ability to effectively model and compare interventions for risk management. AIM: This study measured SARS-CoV-2 in three hospitals in Scotland on surfaces and in air, alongside ventilation and patient care activities. METHODS: Air sampling at 200 L/min for 20 min and surface sampling were performed in two wards designated to treat COVID-19-positive patients and two non-COVID-19 wards across three hospitals in November and December 2020. FINDINGS: Detectable samples of SARS-CoV-2 were found in COVID-19 treatment wards but not in non-COVID-19 wards. Most samples were below assay detection limits, but maximum concentrations reached 1.7×103 genomic copies/m3 in air and 1.9×104 copies per surface swab (3.2×102 copies/cm2 for surface loading). The estimated geometric mean air concentration (geometric standard deviation) across all hospitals was 0.41 (71) genomic copies/m3 and the corresponding values for surface contamination were 2.9 (29) copies/swab. SARS-CoV-2 RNA was found in non-patient areas (patient/visitor waiting rooms and personal protective equipment changing areas) associated with COVID-19 treatment wards. CONCLUSION: Non-patient areas of the hospital may pose risks for infection transmission and further attention should be paid to these areas. Standardization of sampling methods will improve understanding of levels of environmental contamination. The pandemic has demonstrated a need to review and act upon the challenges of older hospital buildings meeting current ventilation guidance.

Safe design and maintenance of bone marrow transplant units: a narrative review.

BACKGROUND: Patients undergoing bone marrow transplantation or chemotherapy for cancer are profoundly immunosuppressed. They are at risk for both endogenous and exogenous infections and require enhanced protection from infection while in hospital. OBJECTIVES: The aim of this narrative review was to determine the optimal design features of bone marrow transplant (BMT) units for reducing infection risk in these vulnerable patients. SOURCES: A literature search was performed on PubMed and other databases for documents published between January 2000 and October 2021. Keywords were: bone marrow transplant unit OR hematopoietic stem cell transplant unit OR haematology unit OR haemato-oncology unit AND design OR design guidelines OR design criteria OR ventilation specification OR HEPA filtration OR water outbreaks OR water system design. CONTENT: Guidelines and other papers pertaining to BMT unit design are discussed. Key design features identified from the literature to reduce infection risks include high efficiency particulate air filtration, positive-pressure ventilation, sufficient air changes and sealed rooms. The evidence for each of these parameters and other findings are discussed. We found no guidelines specific to water quality and control in BMT units. IMPLICATIONS: Guidelines on the various components of design were found, but no comprehensive guidance documents addressing all relevant aspects, such as ventilation, water, and other design features, were found. Literary publications and policy documents were combined and summarised to highlight key design features aimed at reducing infection risk in this vulnerable patient group. We propose the development of international guidance for the design of BMT units encompassing all components.

Practical Indicators for Risk of Airborne Transmission in Shared Indoor Environments and Their Application to COVID-19 Outbreaks.

Some infectious diseases, including COVID-19, can undergo airborne transmission. This may happen at close proximity, but as time indoors increases, infections can occur in shared room air despite distancing. We propose two indicators of infection risk for this situation, that is, relative risk parameter (Hr) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission.

Healthcare-acquired clusters of COVID-19 across multiple wards in a Scottish health board.

BACKGROUND: Healthcare-acquired COVID-19 has been an additional burden on hospitals managing increasing numbers of patients with SARS-CoV-2. One acute hospital (W) among three in a Scottish healthboard experienced an unexpected surge of COVID-19 clusters. AIM: To investigate possible causes of COVID-19 clusters at Hospital W. METHODS: Daily surveillance provided total numbers of patients and staff involved in clusters in three acute hospitals (H, M and W) and care homes across the healthboard. All clusters were investigated and documented, along with patient boarding, community infection rates and outdoor temperatures from October 2020 to March 2021. Selected SARS-CoV-2 strains were genotyped. FINDINGS: There were 19 COVID-19 clusters on 14 wards at Hospital W during the six-month study period, lasting from two to 42 days (average, five days; median, 14 days) and involving an average of nine patients (range 1-24) and seven staff (range 0-17). COVID-19 clusters in Hospitals H and M reflected community infection rates. An outbreak management team implemented a control package including daily surveillance; ward closures; universal masking; screening; restricting staff and patient movement; enhanced cleaning; and improved ventilation. Forty clusters occurred across all three hospitals before a January window-opening policy, after which there were three during the remainder of the study. CONCLUSION: The winter surge of COVID-19 clusters was multi-factorial, but clearly exacerbated by moving trauma patients around the hospital. An extended infection prevention and control package including enhanced natural ventilation helped reduce COVID-19 clusters in acute hospitals.

Epidemiology of healthcare-associated infection reported from a hospital-wide incidence study: considerations for infection prevention and control planning.

BACKGROUND: The measure of disease frequency most widely used to report healthcare-associated infection (HAI) is the point-prevalence survey. Incidence studies are rarely performed due to time and cost constraints; they show which patients are affected by HAI, when and where, and inform planning and design of infection prevention and control (IPC) measures. AIM: To determine the epidemiology of HAI within a general and a teaching hospital in Scotland. METHODS: A prospective observational incidence study was undertaken for one year from April 2018 using data collected as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. A novel, robust approach was undertaken, using record linkage to national administrative data to provide full admission and discharge information. Cases were recorded if they met international HAI definitions. FINDINGS: Incidence of HAI for the combined hospitals was 250 HAI cases per 100,000 acute occupied bed-days (AOBD). Highest frequency was in urinary tract (51.2 per 100,000 AOBD), bloodstream (44.7), and lower respiratory tract infection (42.2). The most frequently reported organisms were Escherichia coli, Staphylococcus aureus, and norovirus. Incidence of HAI was higher in older people and emergency cases. There was an increase in the rate of HAI in summer months (pneumonia, respiratory, surgical, and gastrointestinal infection) and in winter months norovirus gastrointestinal infection (P < 0.0001). The highest incidence specialties were intensive care, renal medicine, and cardiothoracic surgery. HAI occurred at a median of 9 days (interquartile range: 4-19) after admission. Incidence data were extrapolated to provide an annual national estimate of HAI in NHS Scotland of 7437 (95% confidence interval: 7021-7849) cases. CONCLUSION: This study provides a unique overview of incidence of HAI and identifies the burden of HAI at the national level for the first time. Understanding the incidence in different clinical settings, at different times, will allow targeting of IPC measures to those patients who would benefit the most.

Impact of healthcare-associated infection on length of stay.

BACKGROUND: Increased length of stay (LOS) for patients is an important measure of the burden of healthcare-associated infection (HAI). AIM: To estimate the excess LOS attributable to HAI. METHODS: This was a one-year prospective incidence study of HAI observed in one teaching hospital and one general hospital in NHS Scotland as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. All adult inpatients with an overnight stay were included. HAI was diagnosed using European Centres for Disease Prevention and Control definitions. A multi-state model was used to account for the time-varying nature of HAI and the competing risks of death and discharge. FINDINGS: The excess LOS attributable to HAI was 7.8 days (95% confidence interval (CI): 5.7-9.9). Median LOS for HAI patients was 30 days and for non-HAI patients was 3 days. Using a simple comparison of duration of hospital stay for HAI cases and non-cases would overestimate the excess LOS by 3.5 times (27 days compared with 7.8 days). The greatest impact on LOS was due to pneumonia (16.3 days; 95% CI: 7.5-25.2), bloodstream infections (11.4 days; 5.8-17.0) and surgical site infection (SSI) (9.8 days; 4.5-15.0). It is estimated that 58,000 bed-days are occupied due to HAI annually. CONCLUSION: A reduction of 10% in HAI incidence could make 5800 bed-days available. These could be used to treat 1706 elective patients in Scotland annually and help reduce the number of patients awaiting planned treatment. This study has important implications for investment decisions in infection prevention and control interventions locally, nationally, and internationally.

Personalized infection prevention and control: identifying patients at risk of healthcare-associated infection.

BACKGROUND: Few healthcare-associated infection (HAI) studies focus on risk of HAI at the point of admission. Understanding this will enable planning and management of care with infection prevention at the heart of the patient journey from the point of admission. AIM: To determine intrinsic characteristics of patients at hospital admission and extrinsic events, during the two years preceding admission, that increase risk of developing HAI. METHODS: An incidence survey of adults within two hospitals in NHS Scotland was undertaken for one year in 2018/19 as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. The primary outcome measure was developing any HAI using recognized case definitions. The cohort was derived from routine hospital episode data and linkage to community dispensed prescribing data. FINDINGS: The risk factors present on admission observed as being the most significant for the acquisition of HAI were: being treated in a teaching hospital, increasing age, comorbidities of cancer, cardiovascular disease, chronic renal failure and diabetes; and emergency admission. Relative risk of developing HAI increased with intensive care unit, high-dependency unit, and surgical specialties, and surgery <30 days before admission and a total length of stay of >30 days in the two years to admission. CONCLUSION: Targeting patients at risk of HAI from the point of admission maximizes the potential for prevention, especially when extrinsic risk factors are known and managed. This study proposes a new approach to infection prevention and control (IPC), identifying those patients at greatest risk of developing a particular type of HAI who might be potential candidates for personalized IPC interventions.

Bed-days and costs associated with the inpatient burden of healthcare-associated infection in the UK.

BACKGROUND: Healthcare-associated infection (HAI) is associated with increased morbidity and mortality resulting in excess costs. AIM: To investigate the impact of all types of HAI on the inpatient cost of HAI using different approaches. METHODS: The incidence, types of HAI, and excess length of stay were estimated using data collected as part of the Evaluation of Cost of Nosocomial Infection (ECONI) study. Scottish NHS reference costs were used to estimate unit costs for bed-days. Variable (cash) costs associated with infection prevention and control (IPC) measures and treatment were calculated for each HAI type and overall. The inpatient cost of HAI is presented in terms of bed-days lost, bed-day costs, and cash costs. FINDINGS: In Scotland 58,010 (95% confidence interval: 41,730-74,840) bed-days were estimated to be lost to HAI during 2018/19, costing £46.4 million (19m-129m). The total annual cost in the UK is estimated to be £774 million (328m-2,192m). Bloodstream infection and pneumonia were the most costly HAI types per case. Cash costs are a small proportion of the total cost of HAI, contributing 2.4% of total costs. CONCLUSION: Reliable estimates of the cost burden of HAI management are important for assessing the cost-effectiveness of IPC programmes. This unique study presents robust economic data, demonstrating that HAI remains a burden to the UK NHS and bed-days capture the majority of inpatient costs. These findings can be used to inform the economic evaluation and decision analytic modelling of competing IPC programmes at local and national level.

Evaluating the post-discharge cost of healthcare-associated infection in NHS Scotland.

BACKGROUND: Whereas the cost burden of healthcare-associated infection (HAI) extends beyond the inpatient stay into the post-discharge period, few studies have focused on post-discharge costs. AIM: To investigate the impact of all types of HAI on the magnitude and distribution of post-discharge costs observed in acute and community services for patients who developed HAI during their inpatient stay. METHODS: Using data from the Evaluation of Cost of Nosocomial Infection (ECONI) study and regression methods, this study identifies the marginal effect of HAI on the 90-daypost-discharge resource use and costs. To calculate monetary values, unit costs were applied to estimates of excess resource use per case of HAI. FINDINGS: Post-discharge costs increase inpatient HAI costs by 36%, with an annual national cost of £10,832,437. The total extra cost per patient with HAI was £1,457 (95% confidence interval: 1,004-4,244) in the 90 days post discharge. Patients with HAI had longer LOS if they were readmitted and were prescribed more antibiotics in the community. The results suggest that HAI did not have an impact on the number of readmissions or repeat surgeries within 90 days of discharge. The majority (95%) of the excess costs was on acute care services after readmission. Bloodstream infection, gastrointestinal infection, and pneumonia had the biggest impact on post-discharge cost. CONCLUSION: HAI increases costs and antibiotic consumption in the post-discharge period. Economic evaluations of IPC studies should incorporate post-discharge costs. These findings can be used nationally and internationally to support decision-making on the impact of IPC interventions.

How dirty is your QWERTY? The risk of healthcare pathogen transmission from computer keyboards.

INTRODUCTION: Healthcare environmental surfaces may be contaminated with micro-organisms that cause healthcare-associated infections (HCAIs). Special attention is paid to near-patient surfaces but sites outside the patient zone receive less attention. This paper presents data on keyboard contamination and the risk of pathogen transmission from keyboards. METHODS: Keyboards from nursing stations in three hospitals and a dental practice were analysed for bacterial contamination. Surfaces were pre-treated to remove planktonic bacteria so that any remaining bacteria were presumed to be associated with biofilm. Bacterial transfer from keyboard keys was studied following wiping with sterile water or sodium hypochlorite. The presence of multi-drug-resistant organisms (MDROs) was sought using selective culture. RESULTS: Moist swabbing did not detect bacteria from any keyboard samples. Use of enrichment broth, however, demonstrated MDROs from most samples. Gram-negative bacteria were recovered from almost half (45%) of the samples, with meticillin-resistant Staphylococcus aureus, vancomycin-resistant enterococcus and MDR Acinetobacter spp. recovered from 72%, 31% and 17% of samples, respectively. Isolates were transferred from 69% of samples after wiping with sterile water, and from 54% of samples after wiping with 1000 ppm sodium hypochlorite. DISCUSSION: While moist swabbing failed to detect bacteria from keyboards, pathogens were recovered using enrichment culture. Use of water- or NaOCl-soaked wipes transferred bacteria from most samples tested. This study implies that hospital keyboards situated outside the patient zone commonly harbour dry surface biofilms (DSBs) that offer a potential reservoir for transferable pathogens. While the role of keyboards in transmission is uncertain, there is a need to pursue effective solutions for eliminating DSBs from keyboards.

Dismantling myths on the airborne transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).

The coronavirus disease 2019 (COVID-19) pandemic has caused untold disruption throughout the world. Understanding the mechanisms for transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is key to preventing further spread, but there is confusion over the meaning of 'airborne' whenever transmission is discussed. Scientific ambivalence originates from evidence published many years ago which has generated mythological beliefs that obscure current thinking. This article collates and explores some of the most commonly held dogmas on airborne transmission in order to stimulate revision of the science in the light of current evidence. Six 'myths' are presented, explained and ultimately refuted on the basis of recently published papers and expert opinion from previous work related to similar viruses. There is little doubt that SARS-CoV-2 is transmitted via a range of airborne particle sizes subject to all the usual ventilation parameters and human behaviour. Experts from specialties encompassing aerosol studies, ventilation, engineering, physics, virology and clinical medicine have joined together to produce this review to consolidate the evidence for airborne transmission mechanisms, and offer justification for modern strategies for prevention and control of COVID-19 in health care and the community.

Why is mock care not a good proxy for predicting hand contamination during patient care?

BACKGROUND: Healthcare worker (HCW) behaviours, such as the sequence of their contacts with surfaces and hand hygiene moments, are important for understanding disease transmission. AIM: To propose a method for recording sequences of HCW behaviours during mock vs actual procedures, and to evaluate differences for use in infection risk modelling and staff training. METHODS: Procedures for three types of care were observed under mock and actual settings: intravenous (IV) drip care, observational care and doctors' rounds on a respiratory ward in a university teaching hospital. Contacts and hand hygiene behaviours were recorded in real-time using either a handheld tablet or video cameras. FINDINGS: Actual patient care demonstrated 70% more surface contacts than mock care. It was also 2.4 min longer than mock care, but equal in terms of patient contacts. On average, doctors' rounds took 7.5 min (2.5 min for mock care), whilst auxiliary nurses took 4.9 min for observational care (2.4 min for mock care). Registered nurses took 3.2 min for mock IV care and 3.8 min for actual IV care; this translated into a 44% increase in contacts. In 51% of actual care episodes and 37% of mock care episodes, hand hygiene was performed before patient contact; in comparison, 15% of staff delivering actual care performed hand hygiene after patient contact on leaving the room vs 22% for mock care. The number of overall touches in the patient room was a modest predictor of hand hygiene. Using a model to predict hand contamination from surface contacts for Staphylococcus aureus, Escherichia coli and norovirus, mock care underestimated micro-organisms on hands by approximately 30%.

Influence of ventilation use and occupant behaviour on surface microorganisms in contemporary social housing.

In the context of increasingly airtight homes, there is currently little known about the type and diversity of microorganisms in the home, or factors that could affect their abundance, diversity and nature. In this study, we examined the type and prevalence of cultivable microorganisms at eight different sites in 100 homes of older adults located in Glasgow, Scotland. The microbiological sampling was undertaken alongside a household survey that collated information on household demographics, occupant behaviour, building characteristics, antibiotic use and general health information. Each of the sampled sites revealed its own distinct microbiological character, in both species and number of cultivable microbes. While some potential human pathogens were identified, none were found to be multidrug resistant. We examined whether the variability in bacterial communities could be attributed to differences in building characteristics, occupant behaviour or household factors. Sampled sites furnished specific microbiological characteristics which reflected room function and touch frequency. We found that homes that reported opening windows more often were strongly associated with lower numbers of Gram-negative organisms at indoor sites (p < 0.0001). This work offers one of the first detailed analysis of cultivable microbes in homes of older adults and their relationship with building and occupancy related factors, in a UK context.

Measuring environmental contamination in critical care using dilute hydrogen peroxide (DHP) technology: An observational cross-over study.

BACKGROUND: The environment has an important role in the transmission of healthcare associated infections. This has encouraged interest in novel methods to improve hygiene in hospitals. One such technology is the use of hydrogen peroxide to decontaminate rooms and equipment; there are, however, few studies that have investigated the effect of continuous dilute hydrogen peroxide (DHP) in the clinical environment. The aim of this study was to examine the use of dilute hydrogen peroxide (DHP) in a critical care unit and measure the microbiological impact on surface contamination. METHODS: We conducted a prospective observational cross-over study in a ten-bed critical care unit in one rural Australian hospital. Selected high-touch sites were screened using dipslides across three study phases: baseline; continuous DHP; and no DHP (control). Quantitative aerobic colony counts (ACC) were assessed against a benchmark standard of ACC >2.5 cfu/cm2 to indicate hygiene failure. RESULTS: There were low levels of microbial contamination in the unit for baseline; DHP; and no DHP phases: 2.2% (95% CI 0.7-5.4%) vs 7.7% (95% CI 4.3-13.0%) vs 6% (95% CI 3.2-10.4%) hygiene failures, respectively. Significant reduction in ACCs did not occur when the DHP was operating compared with baseline and control phases. CONCLUSION: Further work is needed to determine whether continuous DHP technology has a role in decontamination for healthcare settings.