We’ll discuss how we can use a multi-scale socio-behavioral disease modeling approach to integrate interacting elements of health, physical and socially-constructed environments, and community and individual behavior to predict social and spatial heterogeneities in respiratory disease burden. In particular, we leverage opportunistic datasets to characterize behavior and disease across geography and time to resolve questions that have eluded explanation without socio-behavioral data; and we develop generative and inferential models for a systematic understanding of the constant, compounding socio-behavioral processes that give rise to disease heterogeneities across individuals, communities, and systems.