We present our prototype system, OMCAT, which optimizes the reevaluation of a set of pending continuous spatio-temporal queries on trajectory data, when some of the trajectories are affected by traffic abnormalities reported. The key observation that motivates OMCAT is that an abnormality in a given geographical region may cause changes to the answers of queries pertaining to future portions of affected trajectories. We investigate the sources of contextswitching costs at various levels and propose solutions that utilize the correlation of several context dimensions to orchestrate the reevaluation of the queries. OMCAT, fully implemented on top of an existing Object Relational Database Management System ? Oracle 9i, demonstrates that our techniques can substantially reduce the response time during query answer update. Categories and Subject Descriptors H.2.4 [Database Management]: Systems--query processing Keywords Moving Objects Databases, Continuous Queries, Triggers