Disasters impact the delivery of infrastructure services and disrupt the normal functioning of communities. A primary goal of recovery is to restore patterns of activity to pre-disaster levels in the shortest time possible with minimum performance loss. Resourcing strategies (amounts and allocations) in the post-disaster period should be efficient to maximize benefits with minimum resources and effectively ensure the desired results. Limited resources force recovery planners to choose among multiple competing priorities across infrastructures and populations (e.g., tourism, transportation, workforce, businesses, public health, residents). Optimal resource sequencing, amounts, and timing to improve recovery depend on the capacities of these interdependent community sectors, which interact through multiple delayed feedback loops. Understanding how the structure of community infrastructure systems impacts recovery can improve recovery resource planning by identifying dominant causal structures and high leverage points in the community recovery process. This research combines system dynamics and design structure matrix (DSM) modeling to build, test, and apply a feedback theory of community disaster recovery. The model is used to investigate optimal resource loading and sequencing strategies using a simplified sector model. Initial results, implications, and opportunities for future research are discussed.