title: Integrative Spatial Data Analytics for Public Health Studies of New York State.
abstract: Increased accessibility of health data made available by the government provides unique opportunity for spatial analytics with much higher resolution to discover patterns of diseases, and their correlation with spatial impact indicators. This paper demonstrated our vision of integrative spatial analytics for public health by linking the New York Cancer Mapping Dataset with datasets containing potential spatial impact indicators. We performed spatial based discovery of disease patterns and variations across New York State, and identify potential correlations between diseases and demographic, socio-economic and environmental indicators. Our methods were validated by three correlation studies: the correlation between stomach cancer and Asian race, the correlation between breast cancer and high education population, and the correlation between lung cancer and air toxics. Our work will allow public health researchers, government officials or other practitioners to adequately identify, analyze, and monitor health problems at the community or neighborhood level for New York State.
authors.affiliation: Stony Brook University, Stony Brook, NY.
authors.forename: Xin
authors.initials: X
authors.lastname: Chen
authors.affiliation: Stony Brook University, Stony Brook, NY.
authors.forename: Fusheng
authors.initials: F
authors.lastname: Wang
mesh_terms: D001943:Breast Neoplasms / Q000453:epidemiology; D066264:Datasets as Topic; D004813:Epidemiology; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000139:chemically induced / Q000453:epidemiology; D009369:Neoplasms / Q000453:epidemiology*; D009518:New York / Q000453:epidemiology; D011634:Public Health / Q000706:statistics & numerical data*; D044469:Racial Groups; D012959:Socioeconomic Factors; D062206:Spatial Analysis; D013274:Stomach Neoplasms / Q000208:ethnology