Building condition assessment methodology to support public finance and disaster risk management

Natural disasters can severely damage a country’s public buildings and infrastructure, often resulting in substantial increases in public debt. To develop cost-effective mitigation strategies, governments need information of their public buildings’ current physical condition—yet such data is often unavailable, and surveying numerous buildings is impractical. While several analytical models exist to characterize structural condition, a more granular modeling approach would better support the design and evaluation of targeted fiscal interventions. This paper introduces a probabilistic systems-aggregated condition assessment methodology that reflects how overall building condition emerges from localized deterioration processes. The methodology disaggregates a building into the levels at which deterioration naturally occurs — components, systems, and critical load paths — and models it using techniques tailored to each. Condition estimates are then coherently aggregated to characterize the compound effect on the entire structure. This structured approach affords modelers significant flexibility to represent diverse structural configurations and materials. Case study results align with expected service lifespans from the literature and resemble Weibull-type deterioration functions. The model offers a valuable tool for public agencies’ work in public finance management, risk management, and preventive maintenance planning.