Project Background 

All viruses naturally mutate over time, creating new versions of the virus called variants. This is also true for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19. When a variant of SARS-CoV-2 detected shows signals of the variant spreading more easily, causing more serious illness, or decreasing the effectiveness of available diagnostics, treatment, or vaccines, these variants are designated as Variants of Concern (VoC). Early data suggests that some of these VoCs may cause more severe disease or lessens the effectiveness of currently available vaccines compared to the original virus. However, these data may not fully account for potential biases such as differences in public health measures and advice, inability to account for chronic health conditions, and other socioeconomic factors which may influence health outcomes. This project leverages BCC19C data such as genomic data, population-level clinical data, and socioeconomic data.  


This project seeks to understand the effect on health outcomes and diseases severity that can be attributed to VoCs while accounting for factors that may distort the true effect (also called confounding factors) by: 

  1. Establishing risk estimates of severe health outcomes that can be attributed to VoC by:
    • Assessing disease severity (hospitalization, length of stay in hospital, ICU admission, mortality) by VoC 
    • Assessing disease severity (hospitalization, length of stay in hospital, ICU admission, mortality) by COVID-19 infection status 
  2. Assessing impact of VoC on the impact of population-level transmission and health outcomes in the context of different social determinants of health 
  3. Examining the impact of mutations common to variants under investigation and disease severity through machine learning approaches 

Funded by: Canadian Institutes for Health Research

Principal Investigator: Dr. Hind Sbihi, Dr. Naveed Janjua

Collaborators: Dr. Sharmistha Mishra, Dr. Jeff Kwong, Dr. Beate Sander