Portfolio of works across domains

Population displacement following environmental shocks reshapes the spatial organization of social interactions, often fragmenting existing ties and weakening community cohesion. Although social capital is widely recognized as a key determinant of resilience, its dynamic restructuring after disruption remains poorly quantified. Here, we develop a spatially embedded, dynamic network framework that operationalizes social capital as a network of repeated encounter opportunities inferred from large-scale mobility data. We find that disaster-induced displacement leads to substantial contraction of socio-spatial networks. To isolate underlying mechanisms, we develop two counterfactual models: a random node removal model and a behaviour-informed model. Both counterfactuals predict substantially lower connectivity than observed, indicating that post-disaster connectivity remains systematically higher than expected based on displacement behavior alone. Structural analysis of the network reveals that this residual connectivity is disproportionately concentrated among bonding ties, while bridging ties are comparatively fragile. Furthermore, interaction becomes increasingly located around third places, suggesting that these places act as spatial anchors for the persistence of social ties under disruption.

Rapid urbanization and climate change have contributed to a significant rise in the frequency and intensity of disasters, which have resulted in three million adults being displaced from their homes in the United States during 2023, according to the Census Bureau. Motivated by the recent literature showing strong associations between social homophily and mobility behavior, we use large-scale data of anonymized GPS traces and online social connections from the Marshall Fires in Colorado, USA, to unravel the associations between social and behavioral factors and evacuation destinations and long-term displacement decisions.

We find that behavioral characteristics and social homophily play a significant role in post-disaster mobility decisions. The social homophily effect is stronger among White and educated populations than low income, and Black and Asian populations. This effect has significant implications for long-term disaster impacts and policymaking, as it is a significant predictor of displacement and return decisions. Our findings highlight the importance of incorporating the social, behavioral, and economic characteristics to better understand and predict evacuation and displacement dynamics after disasters.

Affordable housing is an integral aspect that determines the level of equity, for it to function sustainably, it is important to ensure that these units are placed in high-opportunity neighborhoods, that provide good proximity and accessibility to essential social determinants.

This research leverages spatial analysis approach to assess the fairness of accessibility with public transit for the affordable housing stock of New York City. In particular, transit-based accessibility statistics are calculated by developing catchment analyses from each grid cell representing housing and affordable housing.

These results are used to devise a set of indicators to measure the potential to reach important social determinants, such as health and education facilities, and the number of available jobs. We observe variability in access scores across five boroughs.

This methodology presented here can prove very useful for conducting the feasibility analysis while planning the location of affordable housing in the city, as choosing a neighborhood with a high Access Score for social determinants will ensure that the affordable housing units are located in high opportunity neighborhoods.