Cough aerosol in healthy participants: fundamental knowledge to optimize droplet-spread infectious respiratory disease management

<p>Abstract</p> <p>Background</p> <p>The Influenza A H1N1 virus can be transmitted via direct, indirect, and airborne route to non-infected subjects when an infected patient coughs, which expels a number of different sized droplets to the surrounding environment as an aerosol. The objective of the current study was to characterize the human cough aerosol pattern with the aim of developing a standard human cough bioaerosol model for Influenza Pandemic control.</p> <p>Method</p> <p>45 healthy non-smokers participated in the open bench study by giving their best effort cough. A laser diffraction system was used to obtain accurate, time-dependent, quantitative measurements of the size and number of droplets expelled by the cough aerosol.</p> <p>Results</p> <p>Voluntary coughs generated droplets ranging from 0.1 - 900 microns in size. Droplets of less than one-micron size represent 97% of the total number of measured droplets contained in the cough aerosol. Age, sex, weight, height and corporal mass have no statistically significant effect on the aerosol composition in terms of size and number of droplets.</p> <p>Conclusions</p> <p>We have developed a standard human cough aerosol model. We have quantitatively characterized the pattern, size, and number of droplets present in the most important mode of person-to-person transmission of IRD: the cough bioaerosol. Small size droplets (< 1 μm) predominated the total number of droplets expelled when coughing. The cough aerosol is the single source of direct, indirect and/or airborne transmission of respiratory infections like the Influenza A H1N1 virus.</p> <p>Study design</p> <p>Open bench, Observational, Cough, Aerosol study</p

Optimizing Preprocessing and Analysis Pipelines for Single-Subject fMRI: 2. Interactions with ICA, PCA, Task Contrast and Inter-Subject Heterogeneity

A variety of preprocessing techniques are available to correct subject-dependant artifacts in fMRI, caused by head motion and physiological noise. Although it has been established that the chosen preprocessing steps (or “pipeline”) may significantly affect fMRI results, it is not well understood how preprocessing choices interact with other parts of the fMRI experimental design. In this study, we examine how two experimental factors interact with preprocessing: between-subject heterogeneity, and strength of task contrast. Two levels of cognitive contrast were examined in an fMRI adaptation of the Trail-Making Test, with data from young, healthy adults. The importance of standard preprocessing with motion correction, physiological noise correction, motion parameter regression and temporal detrending were examined for the two task contrasts. We also tested subspace estimation using Principal Component Analysis (PCA), and Independent Component Analysis (ICA). Results were obtained for Penalized Discriminant Analysis, and model performance quantified with reproducibility (R) and prediction metrics (P). Simulation methods were also used to test for potential biases from individual-subject optimization. Our results demonstrate that (1) individual pipeline optimization is not significantly more biased than fixed preprocessing. In addition, (2) when applying a fixed pipeline across all subjects, the task contrast significantly affects pipeline performance; in particular, the effects of PCA and ICA models vary with contrast, and are not by themselves optimal preprocessing steps. Also, (3) selecting the optimal pipeline for each subject improves within-subject (P,R) and between-subject overlap, with the weaker cognitive contrast being more sensitive to pipeline optimization. These results demonstrate that sensitivity of fMRI results is influenced not only by preprocessing choices, but also by interactions with other experimental design factors. This paper outlines a quantitative procedure to denoise data that would otherwise be discarded due to artifact; this is particularly relevant for weak signal contrasts in single-subject, small-sample and clinical datasets

“It’s an emotional roller coaster… But sometimes it’s fucking awesome” : Meaning and Motivation of Work for Peers in Overdose Response Environments in British Columbia

The province of British Columbia (BC), Canada is amid dual public health emergencies in which the overdose epidemic declared in 2016 has been exacerbated by restrictions imposed by the Coronavirus Disease of 2019 (COVID-19) pandemic. Experiential workers, commonly known as ‘peers’ (workers with past or present drug use experience) are at the forefront of overdose response initiatives and are essential in creating safe spaces for people who use drugs (PWUD) in harm reduction. Working in overdose response environments can be stressful, with lasting emotional and mental health effects. There is limited knowledge about the personal meaning that experiential workers derive from their work, which serve as motivators for them to take on these often stressful roles.Medicine, Faculty ofNon UBCPopulation and Public Health (SPPH), School ofReviewedFacultyResearche