Disaster risk management (DRM) methodologies in Latin America traditionally segregate processes into understanding, reduction, and management. This compartmentalization often leads to disjointed decision-making, diminishing the effectiveness of risk reduction and disaster responses. We propose a novel methodology for optimizing disaster response planning to address these shortcomings. By integrating damage estimation, algebraic mapping, stochastic modeling, and model integration, our approach effectively forecasts the demands of emergency and disaster services during a major earthquake and its cascading events. Our results specify the necessary scale and distribution of urban search and rescue, fire extinguishing, and hazardous materials response services in Bogotá, D.C. This comprehensive approach enables local fire departments and disaster management entities to make science-based decisions for strategic planning, potentially including strengthening, improving, relocating, or creating new emergency service stations, and enhancing community empowerment for a swift, integrated response. Our methodology enhances disaster response capabilities in Latin American countries with similar conditions by providing a scientific basis for these decisions. It bridges the gap in DRM by emphasizing the critical roles of science and community engagement. This study sets a precedent for future advancements where integrated approaches are pivotal.