Assessing the value of blood donor data for public health surveillance 

Principal Investigator: Dr. Alton Russell

Affiliation: McGill University

Start Year: 2023

This project is being led by Yuan Yan, a postdoctoral researcher at McGill University.

Information on population immunity to COVID-19 comes from different types of studies. Some, like CanPath, invite randomly selected individuals to participate. Other studies use populations who are already having blood drawn, such as blood donors. While monitoring immunity levels with a convenient population like blood donors can be implemented quickly and inexpensively, some subgroups of the population may be underrepresented or missing, leading to ‘blind spots’. At the same time, response rates to surveys with randomly-invited participants during COVID-19 were low, which could also threaten the representativeness of those studies. In this study, we will compare COVID-19 antibody data from blood donors to CanPath and other studies with randomly sampled participants to assess differences in which sociodemographic and geographic subgroups are represented. We will also analyze the extent to which different methods of statistical adjustment can correct for underrepresentation of certain groups and improve the accuracy of population measures of COVID-19 immunity derived from both blood donor data and studies like CanPath.