A note on optimal design for hierarchical generalized group testing
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Choosing an optimal strategy for hierarchical group testing is an important problem for practitioners who are interested in disease screening under limited resources. For example, when screening for infection diseases in large populations, it is important to use algorithms that minimize the cost of potentially expensive assays. Black et al.(2015) described this as an intractable problem unless the number of individuals to screen is small. They proposed an approximation to an optimal strategy that is difficult to implement for large population sizes. In this note, we develop an optimal design that can be obtained using a novel dynamic programming algorithm. We show that this algorithm is substantially more efficient than the approach proposed by Black et al.(2015). The resulting algorithm is simple to implement and Matlab code is presented for applied statistician.
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