This paper introduces two novel measures for multilayer networks - multilayer contagion distance and multilayer contagion centrality - designed to capture the systemic importance of nodes by explicitly incorporating interdependencies across multiple layers. Unlike traditional centrality metrics that consider each layer independently or aggregate them naively, our approach leverages the full multilayer network structure to reflect both intra-layer and inter-layer connectivity and their combined effects. The measures are applied to the dynamic multiplex global trade network, where countries are nodes and trade relationships across various industries form multiple interconnected layers. By comparing our multilayer metrics with standard aggregated and layer-specific benchmarks, we demonstrate the enhanced ability of the multilayer approach to uncover hidden contagion channels and better assess systemic risk. This framework provides a more nuanced understanding of how shocks propagate through complex, interconnected systems, making it a valuable tool for policymakers and researchers analysing economic resilience and vulnerability in global trade and beyond.