The ability to estimate and characterize the burden of disease on a population is important for all public health events, including extreme heat events. Preparing for such events is critical to minimize the associated morbidity and mortality [1, 2]. Since there are delays in obtaining hospital discharge or death records, monitoring of ED visits is the timeliest and an inexpensive method for surveillance of HRI . Aside from air temperature, other environmental variables are used to issue heat advisories based on the heat index, including humidity and wind . The purpose of this study was to evaluate the relationship between HRI ED visits and weather variables as predictors, in Ohio.
Correlation and linear regression analyses were completed to evaluate the relationship between a heat-related illness (HRI) classifier using emergency department (ED) chief complaint data and specific weather variables as predictors, in Ohio.