Dr. Banafshe (Benita) Hosseini is a Research Scientist at the Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, and an Assistant Professor at the Department of Family and Community Medicine and the Dalla Lana School of Public Health at the University of Toronto.
Her research focuses on pandemic preparedness, incorporating adaptive platform trials to evaluate treatments for respiratory infections, implementing diagnostic tools to enhance early detection and monitoring, and applying the One Health approach to address the interconnected challenges across human, animal, and ecosystem health.
Benita’s work also explores the use of artificial intelligence (AI) and machine learning (ML) to predict health outcomes, improve healthcare system efficiency, and inform early warning systems for respiratory infections. She is committed to advancing health equity and understanding the role of social determinants of health (SDoH) in shaping health outcomes. Her research examines how individual and neighborhood-level factors contribute to health inequities and works to address barriers to care, particularly for vulnerable populations.
This research project aims to strengthen how Canada applies the One Health approach, a global strategy that recognizes the interconnectedness of human, animal, and eco...
The research aims to evaluate the utility of environmental data, not typically included in predictive models, in enhancing asthma exacerbation prediction models, and t...
TreatResp will evaluate the clinical effectiveness and cost-effectiveness of therapeutics for respiratory pathogens in non-hospitalized patients and build off lessons...
CanTreatCOVID results published: Read the New England Journal of Medicine article or the Unity Health Toronto article about the results of our clinical trial of Paxlo...
The COVID-19 pandemic has highlighted the importance of rapid and accurate viral testing at the point of care to both guide patient care and support surveillance. AIM-...
COVID-19 showed the importance of fast and effective ways to study potential treatments. Traditional randomized controlled trials (RCT), while often methodologicall...
Innovative strategies for early detection of acute respiratory infections: co-design of a tailored surveillance system with primary care providers and emergency depart...
Road to equitable recovery: Examining the impact of COVID-19 on low-income, racialized and/or individuals unable to shelter at home and assessing policy response aimed...