Introduction The COVID-19 pandemic has made well-fitting face masks a critical piece of protective equipment for healthcare workers and civilians. While the importance of wearing face masks has been acknowledged, there remains a lack of understanding about the role of good fit in rendering protective equipment useful. In addition, supply chain constraints have caused some organizations to abandon traditional quantitative or/and qualitative fit testing, and instead, have implemented subjective fit checking. Our study seeks to quantitatively evaluate the level of fit offered by various types of masks, and most importantly, assess the accuracy of implementing fit checks by comparing fit check results to quantitative fit testing results. Methods Seven participants first evaluated N95 and KN95 respirators by performing a fit check. Participants then underwent quantitative fit testing wearing five N95 respirators, a KN95 respirator, a surgical mask, and fabric masks. Results N95 respirators offered higher degrees of protection than the other categories of masks tested; however, it should be noted that most N95 respirators failed to fit the participants adequately. Fit check responses had poor correlation with quantitative fit factor scores. KN95, surgical, and fabric masks achieved low fit factor scores, with little protective difference recorded between respiratory protection options. In addition, small facial differences were observed to have a significant impact on quantitative fit. Conclusion Fit is critical to the level of protection offered by respirators. For an N95 respirator to provide the promised protection, it must fit the participant. Performing a fit check via NHS self-assessment guidelines was an unreliable way of determining fit.
ObjectiveWe examined the ability of fabrics which might be used to create home-made face masks to filter out ultrafine (0.02–0.1 µm) particles at the velocity of adult human coughing.MethodsTwenty commonly available fabrics and materials were evaluated for their ability to reduce air concentrations of ultrafine particles at coughing face velocities. Further assessment was made on the filtration ability of selected fabrics while damp and of fabric combinations which might be used to construct home-made masks.ResultsSingle fabric layers blocked a range of ultrafine particles. When fabrics were layered, a higher percentage of ultrafine particles were filtered. The average filtration efficiency of single layer fabrics and of layered combination was found to be 35% and 45%, respectively. Non-woven fusible interfacing, when combined with other fabrics, could add up to 11% additional filtration efficiency. However, fabric and fabric combinations were more difficult to breathe through than N95 masks.ConclusionsThe current coronavirus pandemic has left many communities without access to N95 face masks. Our findings suggest that face masks made from layered common fabric can help filter ultrafine particles and provide some protection for the wearer when commercial face masks are unavailable.
ObjectivesTo systematically review the evidence base for a systems approach to healthcare design, delivery or improvement.DesignSystematic review with meta-analyses.MethodsIncluded were studies in any patients, in any healthcare setting where a systems approach was compared with usual care which reported quantitative results for any outcomes for both groups. We searched Medline, Embase, HMIC, Health Business Elite, Web of Science, Scopus, PsycINFO and CINAHL from inception to 28 May 2019 for relevant studies. These were screened, and data extracted independently and in duplicate. Study outcomes were stratified by study design and whether they reported patient and/or service outcomes. Meta-analysis was conducted with Revman software V.5.3 using ORs—heterogeneity was assessed using I2 statistics.ResultsOf 11 405 records 35 studies were included, of which 28 (80%) were before-and-after design only, five were both before-and-after and concurrent design, and two were randomised controlled trials (RCTs). There was heterogeneity of interventions and wide variation in reported outcome types. Almost all results showed health improvement where systems approaches were used. Study quality varied widely. Exploratory meta-analysis of these suggested favourable effects on both patient outcomes (n=14, OR=0.52 (95% CI 0.38 to 0.71) I2=91%), and service outcomes (n=18, OR=0.40 (95% CI 0.31 to 0.52) I2=97%).ConclusionsThis study suggests that a systems approaches to healthcare design and delivery results in a statistically significant improvement to both patient and service outcomes. However, better quality studies, particularly RCTs are needed.PROSPERO registration numberCRD42017065920.
Introduction: The COVID-19 pandemic has made well-fitting face masks a critical piece of protective equipment for healthcare workers and civilians. While the importance of wearing face masks has been acknowledged, there remains a lack of understanding about the role of good fit in rendering protective equipment useful. In addition, supply chain constraints have caused some organizations to abandon traditional quantitative or qualitative fit testing, and instead, have implemented subjective fit checking. Our study seeks to quantitatively evaluate the level of fit offered by various types of masks, and most importantly, assess the accuracy of implementing fit checks by comparing fit check results to quantitative fit testing results. Methods: Seven participants first evaluated N95 and KN95 masks by performing a fit check. Participants then underwent quantitative fit testing wearing five N95 masks, a KN95 mask, a surgical mask, and fabric masks. Results: N95 masks offered higher degrees of protection than the other categories of masks tested; however, it should be noted that most N95 masks failed to fit the participants adequately. Fit check responses had poor correlation with quantitative fit scores. All non-N95 masks achieved low fit scores. Conclusion: Fit is critical to the level of protection offered by masks. For an N95 mask to provide the promised protection, it must fit the participant. Performing a fit check was an unreliable way of determining fit.
The COVID-19 pandemic has drawn unprecedented attention to the use of masks and fabric face coverings to prevent the spread of respiratory viruses, such as SARS-CoV-2. The fit of a mask has been identified as one the primary factors in determining the effectiveness of masks. If substantial gaps exist between the mask and the wearers face, air may take the path of least resistance through gaps and avoid filtration, both during inhalation and exhalation. A number of techniques, referred to as fit hacks have emerged to improve the fit of face masks. In this paper we test a variety of fit hacks on surgical masks and KN95 masks to compare their effectiveness. We identify fit hacks which greatly improved the fit of masks, and thus their effectiveness.
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