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In this paper, we propose a graph-based method for distributed event-region detection in a wireless sensor network (WSN). The proposed method is developed by exploiting the fact that the true events at geographically neighboring sensors have a statistical dependency in an event-region detection scenario. This spatial dependence amongst the sensors is modeled using graphical models (GMs) and serves as a regularization term to enhance the detection accuracy. The method involves solving a linear system of equations, which can be readily implemented in a distributed fashion. Numerical results are presented to illustrate the performance of our proposed approach.