S. Stewart, *, C. Robertson, S. Kennedy, K. Kavanagh, L. Haahr, S. Manoukian, H. Mason, S. Dancer, B. Cook , J. Reilly.
Personalized infection prevention and control: identifying patients at risk of healthcare-associated infection.  
Journal of Hospital Infection 114 (2021) 32e42.

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 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. 

F. Chiappa, B. Frascella, G.P. Vigezzi, M. Moro, L. Diamanti, L. Gentile, P. Lago, N. Clementi, C. Signorelli, N. Mancini, A. Odone.
The efficacy of ultraviolet light-emitting technology against coronaviruses: a systematic review.
Journal of Hospital Infection 114 (2021) 63e78  

SUMMARY

The ongoing pandemic of COVID-19 has underlined the importance of adopting effective infection prevention and control (IPC) measures in hospital and community settings. Ultraviolet (UV)-based technologies represent promising IPC tools: their effective application for sanitation has been extensively evaluated in the past but scant, heterogeneous and inconclusive evidence is available on their effect on SARS-CoV-2 transmission. With the aim of pooling the available evidence on the efficacy of UV technologies against coronaviruses, we conducted a systematic review following PRISMA guidelines, searching Medline, Embase and the Cochrane Library, and the main clinical trials’ registries (WHO ICTRP, ClinicalTrials.gov, Cochrane and EU Clinical Trial Register). Quantitative data on studies’ interventions were summarized in tables, pooled by different coronavirus species and strain, UV source, characteristics of UV light exposure and outcomes. Eighteen papers met our inclusion criteria, published between 1972 and 2020. Six focused on SARS-CoV-2, four on SARS-CoV-1, one on MERS-CoV, three on seasonal coronaviruses, and four on animal coronaviruses. All were experimental studies. Overall, despite wide heterogenicity within included studies, complete inactivation of coronaviruses on surfaces or aerosolized, including SARS-CoV-2, was reported to take a maximum exposure time of 15 min and to need a maximum distance from the UV emitter of up to 1 m. Advances in UV-based technologies in the field of sanitation and their proved high virucidal potential against SARS-CoV-2 support their use for IPC in hospital and community settings and their contribution towards ending the COVID-19 pandemic. National and international guidelines are to be updated and parameters and conditions of use need to be identified to ensure both efficacy and safety of UV technology application for effective infection prevention and control in both healthcare and non-healthcare settings

O. Assadian, S. Harbarth, M. Vos, J.K. Knobloch, A. Asensio, A.F. Widmer
Practical recommendations for routine cleaning and disinfection procedures in healthcare institutions: a narrative review.
Journal of Hospital Infection 113 (2021) 104e114.   

Healthcare-associated infections (HAIs) are the most common adverse outcomes due to delivery of medical care. HAIs increase morbidity and mortality, prolong hospital stay, and are associated with additional healthcare costs. Contaminated surfaces, particularly those that are touched frequently, act as reservoirs for pathogens and contribute towards pathogen transmission. Therefore, healthcare hygiene requires a comprehensive approach whereby different strategies may be implemented together, next to targeted, risk-based approaches, in order to reduce the risk of HAIs for patients. This approach includes hand hygiene in conjunction with environmental cleaning and disinfection of surfaces and clinical equipment. This review focuses on routine environmental cleaning and disinfection including areas with a moderate risk of contamination, such as general wards. As scientific evidence has not yet resulted in universally accepted guidelines nor led to universally accepted practical recommendations pertaining to surface cleaning and disinfection, this review provides expert guidance for healthcare workers in their daily practice. It also covers outbreak situations and suggests practical guidance for clinically relevant pathogens. Key elements of environmental cleaning and disinfection, including a fundamental clinical risk assessment, choice of appropriate disinfectants and cleaning equipment, definitions for standardized cleaning processes and the relevance of structured training, are reviewed in detail with a focus on practical topics and implementation.

A. Aganovic, G. Cao, T. Fecer,  B. Ljunqvist, B. Lytsy, A. Radtke, B. Reinmüller, R. Traversari 
Ventilation design conditions associated with airborne bacteria levels within the wound area during surgical procedures: a systematic review. 
Journal of Hospital Infection 113 (2021) 85e95

Without confirmation of the ventilation design conditions (typology and airflow rate), the common practice of identifying unidirectional airflow (UDAF) systems as equivalent to ultra-clean air ventilation systems may be misleading, but also any claims about the ineffectiveness of UDAF systems should be doubted. The aim of this review was to assess and compare ventilation system design conditions for which ultra-clean air (mean <10 cfu/m3 within 50 cm from the wound has been reported. Six medical databases were systematically searched for indentify and select studies reporting  intraoperative airborn levels expressed as cfu/m3  close to the wound site and ventilation system design conditions. Available data on confonding factors such as the number of persons present in the operating room, number, number of doors openings, and clothing material were also included. Predictors for achieving mean airborne bacteria levels within <10 cfu/m3 were identified using a penalized multivariate logistic regression model. Twelve studies met the eligibility criteria and were included for analysis. UDAF systems considered had significantly higher air volume flows compared with turbulent ventlation (TV) systems considered. Ultra-clean environments were reported in all UDAF ventilated (N=7) rooms compared with four of 11 operatings rooms equipped with TV. On multivariate analysis, the total number of air exchange rates (P = 0,019; odds ratio, (OR) 95% confidence interval (CI) : 0.66-0.96) and type of clothing material (P= 0.031 ;  OR 95% CI : 0.01-0.71) were significantly associated with achieving mean levels of airborne bacteria <10cfu/m3. High-volume UDAF systems complyinng with DIN 1946-4 :2008 standards for the air flow rate ceiling diffuser size unconditionally achieve ultra-clean air close to the wound site. In conclusion the studied article demonstrate that high-volume UDAF systems performed as ultra-clean air systems and are superior to TV systems in reducing aurborne bacteria levels close to the wound site.

R.G. Bentvelsen, y , E. Holten, N.H. Chavannes, K.E. Veldkamp
eHealth for the prevention of healthcare-associated infections: a scoping review. 
Journal of Hospital Infection 113 (2021) 96e103.

Background: The increase in smartphone use and mobile health applications (apps) holds potential to use apps to reduce and detect healthcare-associated infections (HAIs) in clinical practice.

Aim: To obtain an overview of available apps for HAI prevention, by selecting the clinically relevant apps and scoring functionality, quality and usefulness. 

Methods: This scoping review of available apps in the iOS and Android app stores uses an in-house-developed tool (scraper https://holtder.github.io/talos) to systematically aggregate available apps relevant for HAI prevention. The apps are evaluated on functionality, assessed on quality using the ‘Mobile Application Rating Scale’ (MARS), and assessed on potential use in clinical infection prevention. Findings: Using the scraper with CDC HAI topics through 146 search terms resulted in 92,726 potentially relevant apps, of which 28 apps met the inclusion criteria. The majority of these apps have the functionality to inform (27 of 28 apps) or to instruct (20/28). MARS scores for the 28 apps were high in the following domains: functionality (4.19/5), aesthetics (3.49/5), and information (3.74/5), with relatively low scores in engagement (2.97/5), resulting in a good average score (3.57/5).

Conclusion: Low engagement scores restrict apps that intend to inform or instruct, possibly explained by the often-academic nature of the development of these apps. Although the number of HAI prevention apps increased by 60% in 5 years, the proportion of clinically relevant apps is limited. The variation in HAI app quality and lack of user engagement, could be improved by co-creation and development in the clinical setting

Meghan A. Baker, MD, ScD, Deborah S. Yokoe, MD, MPH, John Stelling, MD, MPH, Ken Kleinman, ScD, Rebecca E. Kaganov, BA, Alyssa R. Letourneau, MD, MPH, Neha Varma, MPH, Thomas O’Brien, MD, Martin Kulldorff, PhD, Damilola Babalola, MD, MPH, Craig Barrett, Pharm.D., BCPS, Marci Drees, MD, MS, Micaela H. Coady, MS, Amanda Isaacs, MSPH, Richard Platt, MD, MSc, Susan S. Huang, MD, MPH, For the CDC Prevention Epicenters Program  
Automated Outbreak Detection of Hospital-Associated Pathogens: Value to Infection Prevention Programs. 
Infect Control Hosp Epidemiol. 2020 September; 41(9): 1016–1021. doi:10.1017/ice.2020.233

Objective:  To assess the utility of an automated, statistically-based outbreak detection system to identify clusters of hospital-acquired microorganisms Design: Multicenter retrospective cohort study Setting: 43 hospitals using a common infection prevention surveillance system 

Methods: A space-time permutation scan statistic was applied to hospitals’ microbiology and 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. Results: 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, andclusters involving Clostridioides difficile or multidrug-resistant organisms. Based on comparison data provided by the convenience sample of hospitals, only 18% (9/51) of the clusters detected by usual surveillance met statistical significance and of their 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. 

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