Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful framework for optimal decision making under the assumption of instantaneous communication. We focus on a delayed communication setting (MPOMDP-DC), in which broadcasted information is delayed by at most one time step. In this paper, we show that computation of the MPOMDP-DC backup can be structured as a tree and we introduce two novel tree-based pruning techniques that exploit this structure in an effective way.