Nominated Principal Applicant
Robert Wu, University Health Network
Eyal de Lara, University of Toronto
Andrea Gershon, Sunnybrook Research Institute
Nisha Andany, Sunnybrook Research Institute
Adrienne Chan, Sunnybrook Research Institute
Vikram Comondore, William Osler Health Center
Nick Daneman, Sunnybrook Research Institute
Tiago Falk, INRS – Énergie, Matériaux et Télécommunications
Christopher Graham, Trillium Health Network
Sameer Masood, University Health Network
Frank Rudzicz, University of Toronto
Teresa To, Hospital for Sick Children
Over a million Canadians have been infected with COVID-19, with the majority managing their infection at home. Experts predict that COVID-19 will become a seasonal disease like influenza. This means ongoing waves, the continued hospitalization of infected patients, a greater number of Variants of Concern (VOCs), and a growing population with Post-Acute Sequelae of SARS-CoV-2 (PASC, also known as long COVID). As the pandemic has urgently highlighted, social determinants of health, including being part of a marginalized group, being a frontline worker, and being of lower socioeconomic status, are key contributors to COVID-19 outcomes.
We are a team of healthcare workers, patients, researchers, and computer scientists with six years of experience developing and using remote monitoring systems for respiratory disease. With one year of funding from the Canadian Institutes of Health Research (CIHR) and the PSI Foundation, our group quickly designed and implemented a smartphone/smartwatch application to monitor people with COVID-19 who are managing the disease at home. Their data is uploaded and displayed on an internet-based dashboard which healthcare providers are currently using to manage patients.
This platform has the potential to become an ongoing, permanent means of caring for people with COVID-19, as well as a way to continue to learn about COVID-19, VOCs and long COVID. Specifically, it can be used to:
- Predict who will require escalation of care;
- Determine clinical characteristics of VOCs;
- Characterize the physical outcomes (phenotypes) of long COVID; and
- Understand how long COVID evolves.
The additional funding from CoVaRR-Net will help our study, officially called Home monitoring of SARS CoV2 variants: clinical characterization to improve management of patients with acute infection and post-acute sequelae of SARS-CoV-2, get closer to our overall goal of using real-time, continuous remote monitoring using smartphones and smartwatches for patients with acute COVID-19 infection isolating at home to predict who will deteriorate and need escalation of care, determine features that distinguish COVID variants that can be used for variant surveillance; and determine prevalence, functional impact and predictors of long COVID.
CoVaRR-Net is funding this research, which was first proposed to the Canadian Institutes of Health Research’s (CIHR) Emerging COVID-19 Research Gaps and Priorities – Variants funding call, with a $412,996 cash contribution.