Assessment of extreme heat and hospitalizations to inform early warning systems Proceedings of the National Academy of Science of the United States

Heat early warning systems and action plans use temperature thresholds to trigger warnings and risk communication. In this study, we conduct multistate analyses, exploring associations between heat and all-cause and cause-specific hospitalizations, to inform the design and development of heat–health early warning systems. We used a two-stage analysis to estimate heat–health risk relationships between heat index and hospitalizations in 1,617 counties in the United States for 2003–2012. The first stage involved a county-level time series quasi-Poisson regression, using a distributed lag nonlinear model, to estimate heat–health associations. The second stage involved a multivariate random-effects meta-analysis to pool county-specific exposure–response associations across larger geographic scales, such as by state or climate region. Using results from this two-stage analysis, we identified heat index ranges that correspond with significant heat-attributable burden. We then compared those with the National Oceanic and Atmospheric Administration National Weather Service (NWS) heat alert criteria used during the same time period. Associations between heat index and cause-specific hospitalizations vary widely by geography and health outcome. Heat-attributable burden starts to occur at moderately hot heat index values, which in some regions are below the alert ranges used by the NWS during the study time period. Locally specific health evidence can beneficially inform and calibrate heat alert criteria. A synchronization of health findings with traditional weather forecasting efforts could be critical in the development of effective heat–health early warning systems. 2019 PMC6431221 NWS (National Weather Service) Submitted https://doi.org/10.1073/pnas.1806393116 Other 1948