Yale University will develop a “microbial health score” for a cohort of single-family homes, focusing on the respiratory health of the home’s occupants. The team will use classical statistical models, machine learning, and deep learning methods to train, test, and validate an adaptable index that links microbial features to building health and quantifies the relationship between non-biological building (environmental) variables with important microbial features. This index will help predict how indoor microbes impact human health, guiding building design and operations to foster beneficial microbial communities and prevent the spread of harmful ones.