Pooled SARS-CoV-2 Testing
Noam Shental et al. (via Ben Adida):
Recent reports suggest that 10-30% of SARS-CoV-2 infected patients are asymptomatic and that significant viral shedding may occur prior to symptom onset. Therefore, there is an urgent need to increase diagnostic testing capabilities to prevent disease spread. We developed P-BEST - a method for Pooling-Based Efficient SARS-CoV-2 Testing which identifies all positive subjects within a large set of samples using a single round of testing. Each sample is assigned into multiple pools using a combinatorial pooling strategy based on compressed sensing designed for maximizing carrier detection. In our current study we pooled sets of 384 samples into 48 pools providing both an 8-fold increase in testing efficiency, as well as an 8-fold reduction in test costs.
It’s kind of like error correction codes and has similar limitations based on the frequency of errors/infections:
Our current implementation of P-BEST was designed for a carrier rate of ~1%. To allow higher testing efficiency, i.e., to minimize the number of pools required to screen a given population, designs should vary according to the carrier rate. Pooling designs can differ by the number of pools, and by the number of samples per pool. Specifically, as the carrier rate in the population rises more pools are required to correctly identify all positive carriers in a single testing round. Moreover, the required number of samples per pool decreases with increasing the carrier rate. Conversely, when carrier rates are low, more efficient pooling designs can be used, i.e., less pools are required to test the same number of individuals, while the number of samples per pool should be increased.
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Ghana, Rwanda, probably other African countries have been doing pooled testing for a while. https://www.theguardian.com/commentisfree/2020/may/21/africa-coronavirus-successes-innovation-europe-us
