As cities grapple with converging challenges—from pandemics and urban density to escalating climate risks—wastewater-based epidemiology (WBE) has emerged as a vital early-warning mechanism. Yet, its integration into infrastructure and urban policy remains fragmented, reactive, and underleveraged. This paper introduces a forward-thinking framework grounded in the VMOSA planning model (Vision, Mission, Objectives, Strategies, Action Plan) to bridge epidemic intelligence, wastewater systems, and climate-resilient governance. The methodology aligns spatial planning with public health surveillance by mapping biosignatures—such as SARS-CoV-2 RNA and antimicrobial resistance genes—within sewer networks. Targeted sampling at wastewater treatment plants (WWTPs) and sludge processing lines enhances the spatial resolution of health signals, supported by advanced tools such as membrane bioreactors (MBRs), ion-exchange modules, and AI-enabled biosensors for diagnostic precision. The framework unfolds across four tiers: (1) establishing long-term urban health targets, (2) identifying infrastructural and demographic vulnerabilities, (3) deploying real-time detection technologies, and (4) implementing scenario-driven municipal action plans. Unlike conventional WBE approaches, this model fosters anticipatory, participatory, and replicable epidemic preparedness. Initially piloted in Middle Eastern urban labs, it is adaptable to dense, aging cities worldwide—particularly in Japan, where health innovation and compact urbanism intersect. This research bridges the technical and strategic domains, contributing to SDGs 3 (Good Health), 6 (Clean Water), 11 (Sustainable Cities), and 13 (Climate Action). By reframing wastewater as a diagnostic mirror of urban vitality rather than a byproduct, the study empowers cities to sense, strategize, and respond—before health crises escalate.