Research carried out by a scientist from a Scottish university has found a screening method could make coronavirus testing around 20 times cheaper, as well as help to identify outbreaks earlier.

A team of researchers, including the University of Edinburgh’s Professor Neil Turok, have developed a new mathematical approach to screen large groups for Covid-19.

When applied, the method could help enable scientists to test multiple samples simultaneously and reduce the total number of tests needed - lowering the cost of screening large populations for Covid-19.

It’s called the ‘hypercube algorithm’, and the first field trials have already been conducted in Africa.

Professor Turok said: “We hope our method will enable regular, cost-effective screening in multiple contexts.

“By doing so, it could be a game changer in helping us to overcome the Covid-19 pandemic.”

According to researchers, this novel approach will make it easier to spot outbreaks early on and appears to be highly effective at identifying positive cases when most of the population is negative.

The team showed that a single positive case could still be detected even when mixed with 99 negative swab results.

If the initial test highlighted that the mixed sample contained positive cases, then researchers used the algorithm to design a further series of tests, enabling them to pinpoint individual positive swab results within the combined sample, and making it easy to identify people who are infected.

If the initial test results indicated that there were no positive cases in the mixed sample, then no follow-up action was needed.

Scientists say the new method is best suited to regular screening of a population – rather than testing individual patients – and could help to significantly lower testing costs.

So far, the method has been trialled in Rwanda, where it is being used to screen air passengers, and in South Africa, where it is regularly used to test a leading rugby team. 

The study, which also involved researchers from the African Institute for Mathematical Sciences (AIMS) and the University of Rwanda, is available here.