See below for a quick list of ground-breaking research that the Faculty of Science is conducting on the novel COVID-19 virus.
SFU EPIDEMIOLOGISTS URGE CAUTION AS COVID-19 INFECTIONS SEE RENEWED SPIKE
- The latest preprint paper co-authored by Caroline Colijn and Paul Tupper urges British Columbians to be cautious as latest COVID infections spike.
- The team provides details of a new framework designed to help guide which interventions–including physical distancing, masks and other barriers to transmission, or social bubbles–are likely to have the most impact, and in which settings.
- Using data from reported events where transmissions occurred and were well characterized, they introduce the concept of ‘event R’, the expected number of new infections due to the presence of a single infected individual at an event.
- The researchers determine a fundamental relationship between ‘event R’ and four parameters—transmission intensity, duration of exposure, the proximity of individuals and the degree of mixing—then weigh which interventions, from physical distancing to hand washing, are likely to have the most impact, and in which circumstances.
- The findings could help formulate policy for provinces gradually entering Phase 3 of reopening across Canada, as well as the potential pitfalls public health officials could avoid globally as countries try to reopen economies and lift restrictions on movement.
The research is currently in preprint and not yet peer-reviewed.
SFU, PROVIDENCE HEALTH CARE DEVELOP AI TOOL FOR QUICKER COVID-19 DIAGNOSIS
- Simon Fraser University researchers and Providence Health Care (PHC) are collaborating on a new artificial intelligence tool that will help diagnose COVID-19 quicker.
- The tool, currently in the validation phase at St. Paul’s Hospital in Vancouver, enables a clinician to feed a patient’s chest x-ray image into a computer, run a bio-image detection analysis and determine a positive pneumonia case that is consistent with COVID-19.
- MAGPIE Group researcher Vijay Naidu, a mathematician, helped refine the machine learning system using X-ray images of both COVID-19 and non-COVID-19 patients to identify the unique characteristics found in the virus.
- Instead of doctors checking each X-ray image individually, this system is trained to use algorithms and data to identify it for them.
- The technique can also be used in the detection and classification of other types of chest x-ray pneumonia images, such as bacterial, fungal and other viral pneumonia.
- Once approved, the tool will be made available at no cost with the U.N.’s support. An ongoing multinational collaboration will further improve efficacy and provide additional authentication.
SFU SPINOFF COMPANY RECEIVES FDA APPROVAL FOR USE ON COVID-19 PATIENTS
- Lungpacer Medical Inc. has received Emergency Use Authorization (EUA) clearance by the U.S. Food and Drug Administration, paving the way for immediate use of its Diaphragmatic Pacing Therapy System (DPTS).
- The system has been authorized for use among patients at a high risk of weaning failure from ventilators. Ventilators are used in intensive care units (ICU) to provide breathing support during treatment or as the patient’s body overcomes disease.
- About 30 per cent of ventilated patients typically fail to wean and die in hospitals, but the death rate appears to be much higher for ventilated COVID-19 patients in the U.S.
- Lungpacer has developed a temporary, non-surgical, minimally invasive technology to make mechanical ventilation more effective and safer.
- Hoffer, a professor in SFU’s Biomedical Physiology and Kinesiology (BPK) department and Lungpacer’s founder and lead inventor, says: “A big problem with inflating the lungs using positive pressure to deliver oxygen is that high pressure causes ventilator-induced lung injury, and in COVID-19 patients this may compound the lung damage caused by the virus.
- The system’s goal is to enable and accelerate the recovery of ventilated patients, reduce the hospital care cost of critically ill patients, improve the lifespan and quality of life of survivors of mechanical ventilation and save ICU patients’ lives.
Contribute to SFU`s COVID-19 Research Campaign.
PETER UNRAU COVID-19 MANGO TESTING KITS
- Simon Fraser University researchers will use their pioneering imaging technology—called Mango, for its bright colour— to develop coronavirus testing kits.
- They’re among a small set of Canadian researchers who responded to the rapid funding opportunity recently announced by the Canadian Institutes of Health Research (CIHR) to help address COVID-19.
- The latest research, led by Unrau, a professor of molecular biology and biochemistry involves using Mango to detect individual molecules of RNA within a living cell.
- This helps improve viral screening for viruses such as the coronavirus while enabling basic discoveries into the functioning of cells.
- The Mango NABSA kits can be used to test for the coronavirus, which is a positive strand RNA virus.
- Mango technology is state of the art and can also be used as effective cures for cancer and other diseases.
SFU EPIDEMIOLOGIST’S RESEARCH INFORMS B.C. HEALTH POLICY ON COVID-19
- SFU professor Caroline Colijn’s research and modelling methods have been helping to inform B.C.’s health policy on COVID-19 since the pandemic’s start.
- New Funding from Genome B.C., a non-profit research organization that leads genomics innovation on Canada’s West Coast, will also be used to develop models estimating the strength of control measures, projecting the effects of new control measures, and determining the effectiveness of existing measures based on comparisons between locations.
- The test could be used beyond short-term forecasting for B.C. and applied to Canadian and international data.
- Read the full story here.
CAROLINE COLIJN COVID-19 MATHEMATICAL MODELLING
- Simon Fraser University researcher, Caroline Colijn, an infectious disease modeller and mathematics professor, is using data to project arcs of the COVID-19 pandemic.
- Colijn’s work examines several different scenarios based on more or less stringent responses.
- The role of mathematical modelling in infectious disease epidemiology is to think about the data we have at the population level, groups of people, links between the groups, rates of infection and case counts, and thinking about what that means for the dynamics of this thing going forward.
- The inescapable takeaway of the study is that flattening the surging curve of infections requires drastic measures to keep people isolated from each other as much as possible.