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Presentations by:

• Rodrigo Puentes - Associations of dry bulb and wet bulb globe temperatures with acute cause-specific cardiovascular hospitalizations: A time-series analysis across 12 U.S. states.

• Wyatt Madden - Bayesian ensemble with spatially varying covariate-dependent weights for PM2.5 estimation.

• Martine Mathieu-Campbell - Bias-correcting the high-resolution urban meteorology for impacts dataset (HUMID) temperature data using the personal weather stations (PWS) network and a spatial temporal Bayesian regression coupled with random forest.

• Haisu Zhang - Characterizing cold temperature-cardiovascular disease associations across U.S. metropolitan areas.

• Xiaping Zheng - Estimating short-term health effects of rare exposures and rare outcomes with Firth’s correction to reduce bias.

• Fred Huang - Time-series analysis of population exposure distribution to ambient temperature and heat-related emergency department visits in Atlanta.