Quantification of Resilience Considering Different Migration Biographies: A Case Study of Pune, India

Urbanization proceeds globally and is often driven by migration. Simultaneously, cities face severe exposure to environmental hazards such as floods heatwaves posing threats millions of urban households. Consequently, fostering households’ resilience imperative, yet impeded the lack its accurate assessment. We developed a structural equation model quantify resilience, considering their assets, housing, health properties. Based on household survey (n = 1872), we calculate households in Pune, India with without migration biography compare different sub-groups. further analyze how are exposed affected heatwaves. Our results show that not but type migration, particularly, residence zone at destination (formal or slum) origin (urban rural) provide insights into affectedness extreme weather events. While average, migrants our study have higher than non-migrants, sub-group rural living slums score significantly lower respective non-migrant cohort. Further characteristics distance, time since arrival destination, reasons for contribute resilience. opposing generalized notions literature either least resilient group high performers, need be overcome shows within one city, found both top bottom range. Thus, recommend policymakers include migrants’ biographies when assessing designing improvement interventions help migrant groups more effectively.