Efficient sample pooling strategies for COVID-19 data gathering

Sample pooling of CoViD-19 PCR tests has been recently proposed as a low cost alternative to individual tests. We show that sample pooling is efficient as long as the fraction of the population infected is relatively small. Fisher information theory suggests a rule of thumb that for low infection rates p , pooling 2 /p samples is close to optimal. We present a simple strategy for survey design when not even a ballpark estimate of the infection rate is available.