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MacSphere is McMaster University's Institutional Repository (IR). The purpose of an IR is to bring together all of a University's research under one umbrella, with an aim to preserve and provide access to that research. The research and scholarly output included in MacSphere has been selected and deposited by the individual university departments and centres on campus.

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Recent Submissions

SARS-CoV-2 Testing, Test Positivity, and Vaccination in Social Housing Residents Compared to the General Population: A Retrospective Population-Based Cohort Study
(Journal of Epidemiology and Community Health, 2025-03) Gina Agarwal, Homa Keshavarz, Ricardo Angeles, Melissa Pirrie, Francine Marzanek, Francis Nguyen, Jasdeep Brar, Michael Paterson, Christie Koester, Mikayla Plishka, Guneet Mahal, Sahar Popal, Manasvi Vanama
Background: The consideration of unique social housing needs has largely been absent from the COVID-19 response, particularly in tailoring strategies to improve access to testing and vaccine uptake among vulnerable and high-risk populations in Ontario. Given the growing population of social housing residents, this study aimed to compare SARS-CoV-2 testing, positivity, and vaccination rates in a social housing population with those in a general population cohort in Ontario, Canada. Methods: This population-based cohort study used administrative health data from Ontario to examine SARS-CoV-2 testing, positivity and vaccination rates in social housing residents compared with the general population from 1 January 2020 to 31 December 2021. All comparisons were unadjusted, stratified by sex and age and evaluated using standardised differences. Results: The rates of SARS-CoV-2 PCR testing were lower among younger age groups and higher among older adults within the social housing cohort, compared with the general population cohort. SARS-CoV-2 test positivity was higher in social housing than in the general population among individuals aged 60-79 years (7.9% vs 5.3%, respectively) and 80 years and older (12.0% vs 7.9%, respectively). Overall, 34.3% of social housing residents were fully vaccinated, compared with 29.6% of the general population cohort. However, a smaller proportion of social housing residents had received a booster vaccine (36.7%) compared with the general population (52.4%). Conclusion: Improved and targeted outreach strategies are needed to increase the uptake of COVID-19 booster vaccines among social housing residents.
Deep learning based super-resolution for large field of view imaging of the porosity network in dentin
(2026) Anderson, Lauren
Imaging dentinal porosity is a challenging topic in dental research. This porosity, consisting of microscopic tubules interconnected with sub-microscopic branches, houses odontoblast cellular processes that bathe in physiological fluids, which are believed to play a key role in mechano-sensing. The recent observation that porosity forms a dense network led to the realization that stimuli propagation could be more complex than currently thought. A 3D representation of this network is therefore key to understanding tooth function. This imposes strong constraints on required imaging resolution (∼ 100 nm) and field-of-view (FOV) to visualize porosity of an entire tooth section, currently beyond our reach. To achieve large-scale high-resolution (HR) visualization, we propose using deep learning (DL) super-resolution (SR) models trained on confocal fluorescence microscopy images, to restore HR details from low-resolution (LR) images acquired much faster by under-sampling. Four DL models (RCAN, FSRCNN, pix2pix, CycleGAN) were trained on experimentally acquired HR/LR pairs, with pixel size increase of x2, x4, and x8. Quantitative analysis was performed using standard image quality assessment metrics, which produced contradictory results compared to visual assessment. This drew the need for the development of a biology-driven evaluation based on 2D connected component and 3D graph network analysis, allowing for better interpretation of performance specific to porosity features. CycleGAN and pix2pix performed best, up to x8, which decreases scan-time by a factor of 20.3. CycleGAN was selected and improved with new training on an enriched dataset for application on large FOV LR acquisitions. Overall results showed great promise for the use of SR models to restore HR information from LR acquisitions. With this approach, including scan-time and model application, a large HR FOV could be generated 8.1x faster than standard HR acquisitions, saving over 300 hours. This introduces potential for large-scale HR visualization of dentin porosity, working towards full tooth visualization.
Effects of the Community Paramedicine at Clinic (CP@clinic) program on the health behaviours of older adults residing in social housing: secondary outcomes of a cluster-randomized trial.
(BMC Public Health, 2025) Jasdeep Brar; Leena AlShenaiber; Jasmine Dzerounian; Melissa Pirrie; Ricardo Angeles; Francine Marzanek; Christie Koester; Mikayla Plishka; Guneet Mahal; Sahar Popal; Manasvi Vanama; Gina Agarwal
Background: Community-dwelling, low-income older adults who reside in social housing are a vulnerable population with high rates of poor health behaviours that contribute to chronic health conditions and adverse health outcomes. This study investigates the impact of the Community Paramedicine at Clinic (CP@clinic), a chronic disease prevention, management, and health promotion program, on the health behaviours of this population. Methods: An open-label, pragmatic cluster-randomized controlled trial with parallel intervention and control groups was conducted for one-year within 30 social housing buildings in Ontario, Canada. Eligible buildings were required to have a postal code not shared with other addresses, a majority of tenants aged 55 years or older, at least 50 units, and a similar building available for matching. Buildings were paired and randomized to either intervention (CP@clinic program) or control (usual care) groups. The CP@clinic program was conducted in the common spaces of the intervention buildings and consisted of weekly drop-in sessions facilitated by trained community paramedics. Older adults met one-on-one with community paramedics who conducted evidence-based risk assessments, made referrals to community and healthcare resources, provided health education, and reported health assessment results back to family physicians. Pre- and post-intervention surveys were conducted. Descriptive statistics were used to describe demographic characteristics and health behaviours. Mann-Whitney U tests were conducted to compare individual-level change in health behaviours between intervention and control groups. Results: From the 15 intervention and 15 control buildings, 656 participants completed either the pre- and/or post-intervention survey; the mean age was 72.1 (SD 8.7) years, 75.6% were female, 91.6% were not married, 89% were white, 68.4% obtained a high school education or less, and 90% lived alone. After the intervention, the individual-level consumption of weekly fruit and vegetables and time spent watching TV improved significantly (p < 0.05) for the intervention group compared to the control group (z-scores = -2.467 and -2.194, respectively). The change in consumption of carbohydrate/grains increased significantly for the intervention group compared to the control group (z-score -2.023, p < 0.05). Conclusion: The CP@clinic program is an innovative wellness program that had a significant impact in changing health behaviours, especially in weekly fruit and vegetable consumption, among a vulnerable older adult population. Trial registration: ClinicalTrials.gov NCT02152891, registered June 6, 2014.
Supporting Software Maintenance in Heterogeneous Contexts with SST-Based Framework
(2026) Mahdipour, Azam
Maintaining large-scale and legacy software systems is a complex and time-consuming activity, largely because relevant information is scattered across various tools and artifacts. Practitioners need to perform manual, error-prone correlation of heterogeneous data when performing essential maintenance tasks. This thesis proposes a method to support software maintenance activities using the \emph{Universal Data Source (UDS)} framework based on the Single Source of Truth (SST) paradigm. It consists of a layer of reusable probes that extract targeted data from diverse sources (like source code, version control systems, issue trackers, and static analysis tools), integrating the collected heterogeneous data into a unified, queryable graph model managed by the SST layer, and a layer of tailored visualizations that address the specific needs of each maintenance task. The feasibility and practical value of the proposed method are demonstrated through three real-world use cases: bug triaging, change impact analysis, and code quality enhancement. In each case, carefully designed probes and customized visualizers reduce manual efforts and help smarter decision-making. The use cases show that targeted, incremental analyses are practically achievable and deliver immediate benefits for real maintenance scenarios.
ASSESSMENT OF THE DESIGN, HYDROLOGIC PERFORMANCE, AND MICROPLASTIC REMOVAL EFFICIENCY OF HIGHWAY FILTER DRAINS
(2026) Essien, Aniekan Effiong

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