This paper develops scenario-based stochastic optimization model to choose optimal policies for the integrated deployment of local urban relief teams in the early aftermath of sudden-onset mass casualty incidents. The deployment of local relief teams in an urban area with several affected sites, allocation of casualties to casualty treatment centres, and assignment of medical teams to casualty treatment centres and triage groups are simultaneously determined. Seven strategies under “streaming” and “pooling” groups of treatment strategies are linked to the activity of relief teams. Based on realistic data, our model is analysed for 1750 random samples of the disaster field and 35 instances of a hypothetical earthquake. The results show the integration of SAR and on-field treatment operations can increase the number of survivors. The robust model results in a less number of survivors because it tries to maintain the optimal solution under given scenarios close to its expected value.