Community detection is the process of grouping nodes in a network into clusters. However, real-world graphs often evolve over time, making repeated community detection on such graphs expensive. In this paper, we extend three dynamic approaches, namely, Naive-dynamic (ND), Delta-screening (DS), and Dynamic Frontier (DF), to a fast multicore implementation of the Leiden algorithm – an algorithm known for its high-quality community detection – using subset renumbering, selective refinement, and load balancing of the aggregation phase. This is, to the best of our knowledge, the first attempt at applying such dynamic approaches to the Leiden algorithm.