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Objectives. To examine the relationships among environmental characteristics, temperature, and health outcomes during heat advisories at the geographic scale of street segments. Methods. We combined multiple data sets from Boston, Massachusetts, including remotely sensed measures of temperature and associated environmental characteristics (e.g., canopy cover), 911 dispatches for medical emergencies, daily weather conditions, and demographic and physical context from the American Community Survey and City of Boston Property Assessments. We used multilevel models to analyze the distribution of land surface temperature and elevated vulnerability during heat advisories across streets and neighborhoods. Results. A substantial proportion of variation in land surface temperature existed between streets within census tracts (38%), explained by canopy, impervious surface, and albedo. Streets with higher land surface temperature had a greater likelihood of medical emergencies during heat advisories relative to the frequency of medical emergencies during non–heat advisory periods. There was no independent effect of the average land surface temperature of the census tract. Conclusions. The relationships among environmental characteristics, temperature, and health outcomes operate at the spatial scale of the street segment, calling for more geographically precise analysis and intervention. 

The social integration of a city depends on the extent to which people from different neighborhoods have the opportunity to interact with one another, but most prior work has not developed formal ways of conceptualizing and measuring this kind of connectedness. In this article, we develop original, network-based measures of what we call “structural connectedness” based on the everyday travel of people across neighborhoods. Our principal index captures the extent to which residents in each neighborhood of a city travel to all other neighborhoods in equal proportion. Our secondary index captures the extent to which travels within a city are concentrated in a handful of receiving neighborhoods. We illustrate the value of our indices for the 50 largest American cities based on hundreds of millions of geotagged tweets over 18 months. We uncover important features of major American cities, including the extent to which their connectedness depends on a few neighborhood hubs, and the fact that in several cities, contact between some neighborhoods is all but nonexistent. We also show that cities with greater population densities, more cosmopolitanism, and less racial segregation have higher levels of structural connectedness. Our indices can be applied to data at any spatial scale, and our measures pave the way for more powerful and precise analyses of structural connectedness and its effects across a broad array of social phenomena.