Plan from Hamilton researchers aims to help province test 8 times more COVID samples
Knowing most samples are negative, the team will group samples and only re-test groups that come back positive
While Ontario has failed to reach its goal of testing 20,000 individual COVID-19 samples a day, Dr. David Bulir has had one question in the back of his mind — why isn't the province combining samples and testing them at once?
The dermatology resident who is a part-time faculty member in pathology and molecular medicine at McMaster University and a scientist at St. Joseph's Healthcare Hamilton's Research Institute said it's a simple proposition.
By combining samples using specially made equipment, Bulir thinks they can increase the number of samples tested by up to eight fold.
"If you put two samples together, you automatically double the capacity for testing in Ontario in no time," he told CBC News.
How does the test work?
The idea relies on the assumption that most results come back negative. If a batch comes back positive, the team would test all of those individual samples to determine which sample or samples are positive.
"If we know there were 100 samples and four are positive, out of the 25 pools, only four of those 25 positive should have been positive, so then we would go back and test those 16 samples. So you'd only have 41 tests instead of 100."
But he noted combining samples isn't ideal in all circumstances.
"If a ward is on an outbreak right now you might actually just want to test everyone because there's a good chance if you combine three samples, every one in three would be positive," he explained.
"But if you have a nursing home that's already been screened negative, you have a very low risk that someone is going to be positive in there so for ongoing testing you could maybe combine four or five."
Team to start using real samples
The team sent out 25,000 of their test tubes with their swabs and special liquid. Toronto hospital networks and others will begin using those materials and sending samples to the team for testing.
The group will first test them the standard way, one at a time, and then try the grouped testing to determine what the ideal number of combined samples is. When the samples are grouped, they'll be randomized by their machine.