  Suppressing SARS-CoV-2 will likely require the rapid identification and
isolation of infected individuals, on an ongoing basis. RT-PCR (reverse
transcription polymerase chain reaction) tests are accurate but costly, making
regular testing of every individual expensive. The costs are a challenge for
all countries and particularly for developing countries. Cost reductions can be
achieved by combining samples and testing them in groups. We propose an
algorithm for grouping subsamples, prior to testing, based on the geometry of a
hypercube. At low prevalence, this testing procedure uniquely identifies
infected individuals in a small number of tests. We discuss the optimal group
size and explain why, given the highly infectious nature of the disease,
parallel searches are preferred. We report proof of concept experiments in
which a positive sample was detected even when diluted a hundred-fold with
negative samples. Using these methods, the costs of mass testing could be
reduced by a factor of ten to a hundred or more. If infected individuals are
quickly and effectively quarantined, the prevalence will fall and so will the
costs of regularly testing everyone. Such a strategy provides a possible
pathway to the longterm elimination of SARS-CoV-2. Field trials of our approach
are now under way in Rwanda and initial data from these are reported here.
