Open AccessUsing Integrated City Data and Machine Learning to Identify and Intervene Early on Housing-Related Public Health Problems
Author(s) -
Katharine Robb,
Nicolas Diaz Amigo,
Ashley Marcoux,
Mike McAteer,
J. de Jong
Publication year - 2021
Publication title -
journal of public health management and practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.771
H-Index - 50
eISSN - 1550-5022
pISSN - 1078-4659
DOI - 10.1097/phh.0000000000001343
Subject(s) - overcrowding , public housing , public health , context (archaeology) , stock (firearms) , actuarial science , built environment , code (set theory) , business , computer science , machine learning , environmental health , set (abstract data type) , engineering , medicine , geography , economics , economic growth , nursing , civil engineering , mechanical engineering , archaeology , programming language
Housing is more than a physical structure-it has a profound impact on health. Enforcing housing codes is a primary strategy for breaking the link between poor housing and poor health.