Barriers to healthcare-worker adherence to infection prevention and control practices in British Columbia during the coronavirus disease 2019 (COVID-19) pandemic: A cross-sectional study.

OBJECTIVE: The coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of robust infection prevention and control (IPAC) practices to maintain patient and staff safety. However, healthcare workers (HCWs) face many barriers that affect their ability to follow these practices. We identified barriers affecting HCW adherence to IPAC practices during the pandemic in British Columbia, Canada. DESIGN: Cross-sectional web-based survey. SETTING: Acute care, long-term care or assisted living, outpatient, mental health, prehospital care, and home care. PARTICIPANTS: Eligible respondents included direct-care providers and IPAC professionals working in these settings in all health authorities across British Columbia. METHODS: We conducted a web-based survey from August to September 2021 to assess respondent knowledge and attitudes toward IPAC within the context of the COVID-19 pandemic. Respondents were asked to rate the extent to which various barriers affected their ability to follow IPAC practices throughout the pandemic and to make suggestions for improvement. RESULTS: The final analysis included 2,488 responses; 36% of respondents worked in acute care. Overall, perceptions of IPAC practice among non-IPAC professionals were positive. The main self-perceived barriers to adherence included inadequate staffing to cover absences (58%), limited space in staff rooms (57%), multibed rooms (51%), and confusing messages about IPAC practices (51%). Common suggestions for improvement included receiving more support from IPAC leadership and clearer communication about required IPAC practices. CONCLUSIONS: Our findings highlight frontline HCW perspectives regarding priority areas of improvement for IPAC practices. They will inform policy and guideline development to prevent transmission of COVID-19 and future emerging infections.

Barriers to infection prevention and control in long-term care/assisted living settings in British Columbia during the COVID-19 pandemic: a cross-sectional survey.

BACKGROUND: The COVID-19 pandemic disproportionately impacted long-term care and assisted living (LTC/AL) facilities in Canada, where infection prevention and control (IPAC) programs had been suboptimal. We aimed to identify barriers affecting healthcare workers' (HCW) adherence to IPAC practices during the pandemic in British Columbia in LTC/AL compared to acute care settings. METHODS: We conducted a web-based survey of direct care providers and IPAC professionals across BC from August to September 2021, focused on knowledge and attitudes toward IPAC within the context of the COVID-19 pandemic, and barriers that affected respondents' abilities to follow IPAC practices throughout the pandemic. RESULTS: The final analysis included 896 acute care respondents and 441 from LTC/AL. More LTC/AL respondents reported experiencing the following barriers: following IPAC guidance was of lower priority compared to other tasks (29.1% vs. 14.7%, FDR = 0.001) and not their responsibility (28.0% vs. 11.2%, FDR = 0.001); limited supplies for personal protective equipment (PPE) (49.0% vs. 33.6%, FDR = 0.001), hand hygiene products (42.2% vs. 28.8%, FDR = 0.001), and cleaning/disinfection products (44.1% vs. 30.3%, FDR = 0.001); deficits in IPAC leadership support (46.2% vs. 38.9%, FDR = 0.012), IPAC education and training (46.9% vs. 32.0%, FDR = 0.001), and patient care knowledge for managing COVID-19 infections (46.6% vs. 36.0%, FDR = 0.001). CONCLUSIONS: This survey found that barriers to HCWs' adherence to IPAC practices during the COVID-19 pandemic were different in LTC/AL settings compared to acute care. Improvement efforts should focus on strengthening IPAC programs in LTC/AL, particularly enhanced IPAC staffing/leadership, increased training and education, and improving access to PPE, hand hygiene, and cleaning products.

Simultaneous multi-crop land suitability prediction from remote sensing data using semi-supervised learning.

Land suitability models for Canada are currently based on single-crop inventories and expert opinion. We present a data-driven multi-layer perceptron that simultaneously predicts the land suitability of several crops in Canada, including barley, peas, spring wheat, canola, oats, and soy. Available crop yields from 2013-2020 are downscaled to the farm level by masking the district level crop yield data to focus only on areas where crops are cultivated and leveraging soil-climate-landscape variables obtained from Google Earth Engine for crop yield prediction. This new semi-supervised learning approach can accommodate data from different spatial resolutions and enables training with unlabelled data. The incorporation of a crop indicator function further allows for the training of a multi-crop model that can capture the interdependences and correlations between various crops, thereby leading to more accurate predictions. Through k-fold cross-validation, we show that compared to the single crop models, our multi-crop model could produce up to a 2.82 fold reduction in mean absolute error for any particular crop. We found that barley, oats, and mixed grains were more tolerant to soil-climate-landscape variations and could be grown in many regions of Canada, while non-grain crops were more sensitive to environmental factors. Predicted crop suitability was associated with a region's growing season length, which supports climate change projections that regions of northern Canada will become more suitable for agricultural use. The proposed multi-crop model could facilitate assessment of the suitability of northern lands for crop cultivation and be incorporated into cost-benefit analyses.

Comparative transcriptomics analysis pipeline for the meta-analysis of phylogenetically divergent datasets (CoRMAP).

BACKGROUND: Transcriptional regulation is a fundamental mechanism underlying biological functions. In recent years, a broad array of RNA-Seq tools have been used to measure transcription levels in biological experiments, in whole organisms, tissues, and at the single cell level. Collectively, this is a vast comparative dataset on transcriptional processes across organisms. Yet, due to technical differences between the studies (sequencing, experimental design, and analysis) extracting usable comparative information and conducting meta-analyses remains challenging. RESULTS: We introduce Comparative RNA-Seq Metadata Analysis Pipeline (CoRMAP), a meta-analysis tool to retrieve comparative gene expression data from any RNA-Seq dataset using de novo assembly, standardized gene expression tools and the implementation of OrthoMCL, a gene orthology search algorithm. It employs the use of orthogroup assignments to ensure the accurate comparison of gene expression levels between experiments and species. Here we demonstrate the use of CoRMAP on two mouse brain transcriptomes with similar scope, that were collected several years from each other using different sequencing technologies and analysis methods. We also compare the performance of CoRMAP with a functional mapping tool, previously published. CONCLUSION: CoRMAP provides a framework for the meta-analysis of RNA-Seq data from divergent taxonomic groups. This method facilitates the retrieval and comparison of gene expression levels from published data sets using standardized assembly and analysis. CoRMAP does not rely on reference genomes and consequently facilitates direct comparison between diverse studies on a range of organisms.

Hand hygiene knowledge, attitudes, and practices among hospital inpatients: A descriptive study.

BACKGROUND: Pathogens may be transmitted in hospitals via patients' own hands, but little is known about the facilitators and barriers of hand hygiene among inpatients. This study aimed to assess the hand hygiene knowledge, attitudes, and practices of adult inpatients at 5 hospitals. METHODS: The study consisted of a cross-sectional survey distributed followed by structured interviews with randomly selected inpatients. Qualitative data were analyzed independently by 2 researchers using the Theoretical Domains Framework. RESULTS: A total of 268 surveys were completed, with 66.4% of patients reporting always performing hand hygiene after toileting and 49.2% before eating. The majority of patients (74.6%) stated that they did not want to receive more information about hand hygiene while in the hospital. Key themes identified from 23 interviews include knowledge; environmental context and resources; memory, attention, and decision processes; and social influences. CONCLUSIONS: Self-reported patient hand hygiene rates are suboptimal and there are knowledge gaps among patients as to when to perform hand hygiene, but patients are not receptive to receiving traditional educational interventions. Future interventions to improve patient hand hygiene should focus on other behavior change domains, including environmental context and resources (eg, access to hand sanitizer at the bedside), memory, attention, and decision processes (eg, posters or other reminders), and social influences (eg, role modeling).

DSRIG: Incorporating graphical structure in the regularized modeling of SNP data.

Genetic selection of farm animals plays an important role in genetic improvement programs. Regularized regression methods on single nucleotide polymorphism (SNP) data from a set of candidate genes can help to identify genes that are associated with the trait of interest. This complex task must also consider the relative effect sizes on the desired trait and account for the relationships among the candidate SNPs so that selection of a SNP does not promote other undesirable traits through breeding. We present the Doubly Sparse Regression Incorporating Graphical structure (DSRIG), a novel regularized method for genetic selection that exploits the relationships among candidate SNPs to improve prediction. DSRIG was applied in the prediction of skatole and androstenone levels, two compounds known to be associated with boar taint. DSRIG was shown to provide a predictive benefit when compared to ordinary least squares (OLS) and the least absolute shrinkage and selection operator (LASSO) in a cross-validation procedure. The relative sizes of the coefficient estimates over the cross-validation procedure were compared to determine which SNPs may have the greatest impact on expression of the boar taint compounds and a consensus graph was used to infer the relationships among SNPs.

The firing characteristics of foot sole cutaneous mechanoreceptor afferents in response to vibration stimuli.

Single unit microneurography was used to record the firing characteristics of the four classes of foot sole cutaneous afferents [fast and slowly adapting type I and II (FAI, FAII, SAI, and SAII)] in response to sinusoidal vibratory stimuli. Frequency (3-250 Hz) and amplitude (0.001-2 mm) combinations were applied to afferent receptive fields through a 6-mm diameter probe. The impulses per cycle, defined as the number of action potentials evoked per vibration sine wave, were measured over 1 s of vibration at each frequency-amplitude combination tested. Afferent entrainment threshold (lowest amplitude at which an afferent could entrain 1:1 to the vibration frequency) and afferent firing threshold (minimum amplitude for which impulses per cycle was greater than zero) were then obtained for each frequency. Increases in vibration frequency are generally associated with decreases in expected impulses per cycle (P < 0.001), but each foot sole afferent class appears uniquely tuned to vibration stimuli. FAII afferents tended to have the lowest entrainment and firing thresholds (P < 0.001 for both); however, these afferents seem to be sensitive across frequency. In contrast to FAII afferents, SAI and SAII afferents tended to demonstrate optimal entrainment to frequencies below 20 Hz and FAI afferents faithfully encoded frequencies between 8 and 60 Hz. Contrary to the selective activation of distinct afferent classes in the hand, application of class-specific frequencies in the foot sole is confounded due to the high sensitivity of FAII afferents. These findings may aid in the development of sensorimotor control models or the design of balance enhancement interventions.NEW & NOTEWORTHY Our work provides a mechanistic look at the capacity of foot sole cutaneous afferents to respond to vibration of varying frequency and amplitude. We found that foot sole afferent classes are uniquely tuned to vibration stimuli; however, unlike in the hand, they cannot be independently activated by class-specific frequencies. Viewing the foot sole as a sensory structure, the present findings may aid in the refinement of sensorimotor control models and design of balance enhancement interventions.

On computing standard errors for marginal structural Cox models.

In recent decades, marginal structural models have gained popularity for proper adjustment of time-dependent confounders in longitudinal studies through time-dependent weighting. When the marginal model is a Cox model, using current standard statistical software packages was thought to be problematic because they were not developed to compute standard errors in the presence of time-dependent weights. We address this practical modelling issue by extending the standard calculations for Cox models with case weights to time-dependent weights and show that the coxph procedure in R can readily compute asymptotic robust standard errors. Through a simulation study, we show that the robust standard errors are rather conservative, though corresponding confidence intervals have good coverage. A second contribution of this paper is to introduce a Cox score bootstrap procedure to compute the standard errors. We show that this method is efficient and tends to outperform the non-parametric bootstrap in small samples.

Ethnic differences in the time trend of female breast cancer incidence: Singapore, 1968-2002.

BACKGROUND: From 1968 to 2002, Singapore experienced an almost three-fold increase in breast cancer incidence. This increase appeared to be different across the three main ethnic groups: Chinese, Malays and Indians. This paper used age-period-cohort (APC) modelling, to determine the effects of age at diagnosis, calendar period, and birth cohort on breast cancer incidence for each ethnic group. METHODS: This study included all breast cancer cases (n = 15,269) in the three ethnic groups, reported to the Singapore Cancer Registry from 1968 to 2002 between the ages 25 to 79. Age-specific fertility rates from the Department of Statistics were used to explore the role of fertility. RESULTS: In the 1970s, Indian women had the highest age-standardized breast cancer but by the mid-1980s the highest rates were seen among the Chinese. Remarkable differences were seen in the age-specific incidence rates by ethnic groups. After age 49, the incidence rates for the Chinese and Malays leveled off whereas it continued to rise in the Indians. While our analyses provided some evidence that an age-drift model described the trend seen in the Indians, age-period-cohort model and age-cohort model had the best fit for the Chinese and Malays aged 25 to 79 respectively. Overall, Chinese and Malay women born in later cohorts were at increased risk of developing breast cancer relative to their counterparts in the earlier cohorts. The three ethnic groups experienced similar changes in their fertility in the 1970s, which likely explained much of the increase in their breast cancer incidence but not the ethnic differences. There was a stronger inverse association between total fertility rate and pre-menopausal breast cancer incidence in the Chinese and Malays than the Indians. CONCLUSION: The observed dissimilarity among ethnic groups suggests ethnic differences in exposure or response to certain risk factors. It is likely that longer and subtler differences in childbearing trends and other risk factors may further explain these ethnic differences.

Dragon Promoter Mapper (DPM): a Bayesian framework for modelling promoter structures.

UNLABELLED: Dragon Promoter Mapper (DPM) is a tool to model promoter structure of co-regulated genes using methodology of Bayesian networks. DPM exploits an exhaustive set of motif features (such as motif, its strand, the order of motif occurrence and mutual distance between the adjacent motifs) and generates models from the target promoter sequences, which may be used to (1) detect regions in a genomic sequence which are similar to the target promoters or (2) to classify other promoters as similar or not to the target promoter group. DPM can also be used for modelling of enhancers and silencers. AVAILABILITY: http://defiant.i2r.a-star.edu.sg/projects/BayesPromoter/ CONTACT: vlad@sanbi.ac.za SUPPLEMENTARY INFORMATION: Manual for using DPM web server is provided at http://defiant.i2r.a-star.edu.sg/projects/BayesPromoter/html/manual/manual.htm.

Promoter modeling: the case study of mammalian histone promoters.

MOTIVATION: Histone proteins play important roles in chromosomal functions. They are significantly evolutionarily conserved across species, which suggests similarity in their transcription regulation. The abundance of experimental data on histone promoters provides an excellent background for the evaluation of computational methods. Our study addresses the issue of how well computational analysis can contribute to unveiling the biologically relevant content of promoter regions for a large number of mammalian histone genes taken across several species, and suggests the consensus promoter models of different histone groups. RESULTS: This is the first study to unveil the detailed promoter structures of all five mammalian histone groups and their subgroups. This is also the most comprehensive computational analysis of histone promoters performed to date. The most exciting fact is that the results correlate very well with the biologically known facts and experimental data. Our analysis convincingly demonstrates that computational approach can significantly contribute to elucidation of promoter content (identification of biologically relevant signals) complementing tedious wet-lab experiments. We believe that this type of analysis can be easily applied to other functional gene classes, thus providing a general framework for modelling promoter groups. These results also provide the basis to hunt for genes co-regulated with histone genes across mammalian genomes.