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Big Data and Urban Health  

Mark Stevenson, Jason Thompson, and Thanh Ho

Understanding the varied effects of urban environments on our health have arisen through centuries of observation and analysis. Various units of observation, when compiled spatially or linearly, have provided considerable understanding of the causal pathways between environmental exposures in cities and associated mortality and morbidity. With growing urban agglomerations and a digital age providing timely and standardized data, unique insights are being provided that further enhance the understanding of urban health. No longer is there a potential lack of urban data; over the 2010–2020 decade alone, the resolution and standardization of satellite and street imagery, for example, alongside methods of artificial intelligence such as self-supervision methods, have meant that technology and its capacity have surpassed the accuracy and resolution of many administrative data collections typically used for urban health research. From Bills of Mortality in 1665 to 20th century surveillance systems to the innovation and global reach in the period of “big data,” data has been the mainstay of decision support systems over the centuries. This new world of big data characterized by volume, velocity, variety, veracity, variability, volatility, and value is paramount to answering the significant urban health challenges of the 21st century.