Pooled Sample Testing with Clustering (For Efficient COVID-19 Screening)

Testing medical samples is expensive and pooling samples can reduce costs. But what is the optimal setup? What is the optimal pool size? We consider the simplest and most practical pooling technique and demonstrate how the correlation between samples reduces the testing cost and increases the size of the optimal pool. Then we create a simple clustering model using a Dirichlet Process that could be used as a template for multiple SIR models.