"We show that if the prevalence of positive samples is greater than 30% it is never worth pooling. From 30% down to 1% pools of size 4 are close to optimal. Below 1% substantial gains can be made by pooling, especially if the samples are pooled twice. However, with large pools the sensitivity of the test will fall correspondingly and this must be taken into consideration. We derive simple expressions for the optimal pool size and for the corresponding proportion of samples tested."
This article provides a helpful look at optimal pooling strategies: https://arxiv.org/pdf/1007.4903.pdf
"We show that if the prevalence of positive samples is greater than 30% it is never worth pooling. From 30% down to 1% pools of size 4 are close to optimal. Below 1% substantial gains can be made by pooling, especially if the samples are pooled twice. However, with large pools the sensitivity of the test will fall correspondingly and this must be taken into consideration. We derive simple expressions for the optimal pool size and for the corresponding proportion of samples tested."