Recent tsunami-related studies have employed numerical simulations to estimate inundation areas and integrated these results with geospatial demographic data to determine the number of potentially affected individuals. While this methodology is useful for estimating economic losses, particularly for real estate, it often overlooks evacuation dynamics that significantly influence casualty estimations.

Evacuation modeling frequently relies on computationally intensive techniques, such as agent-based models (ABMs), to simulate human movement. In this study, we propose a simplified evacuation model that estimates a hypothetical location for population groups, defined by census blocks within the affected area. This model integrates geospatial road network data to better approximate feasible evacuation routes, improving spatial realism while drastically reducing processing time and storage requirements.

Tsunami inundation scenarios were analyzed using the TUNAMI-N2 numerical model for multiple seismic sources along the Central Peru subduction zone, obtaining maps of inundation depths and arrival times. The population was categorized into three age groups, each with differentiated displacement capacities, and assigned hypothetical shelter points based on proximity and access through the local road network.

The simplified approach enabled estimating the quantity of people affected, injured, and fatalities. Additionally, the variation of these statistics for different parameters, such as displacement velocity and response time, was analyzed. The proposed model provides an efficient and scalable tool for coastal cities, offering valuable insights to support decision-making processes in Disaster Risk Reduction (DRR).