Fig. 3: Spatial distribution of model errors or biases relative to socially vulnerable populations.

a Schematic example of data and model inequities in a transportation network exposure model. Data quality for roads and bridges depicts a high correlation with the geographical location, subsequently with income level (used to depict a social vulnerability metric). Model fidelity for road models seems to be fair everywhere, but individual bridges show a lack of fidelity in their model definition, which may occur given poor modeling choices (e.g., not considering aging conditions in certain locales). b Schematic example of data and model inequities in a building’s portfolio model. Damage data collected depicts a bias in data availability or quality, with the potential to exacerbate inequities in census tracts (or other social units) with limited capacity to cope with disasters. Fragility modeling availability appears adequate for most of the region, however the performance on some structures in a few census tracts may be over- or under-represented, typically observed when common behavior is assumed in systems that do not necessarily share the same performance under similar hazard conditions.