Heat-health warning systems: a comparison of the predictive capacity of different approaches to identifying dangerously hot days.

Abstract

We compared the ability of several heat-health warning systems to predict days of heat-associated mortality using common data sets. Heat-health warning systems initiate emergency public health interventions once forecasts have identified weather conditions to breach predetermined trigger levels. We examined 4 commonly used trigger-setting approaches: (1) synoptic classification, (2) epidemiologic assessment of the temperature-mortality relationship, (3) temperature-humidity index, and (4) physiologic classification. We applied each approach in Chicago, Illinois; London, United Kingdom; Madrid, Spain; and Montreal, Canada, to identify days expected to be associated with the highest heat-related mortality. We found little agreement across the approaches in which days were identified as most dangerous. In general, days identified by temperature-mortality assessment were associated with the highest excess mortality. Triggering of alert days and ultimately the initiation of emergency responses by a heat-health warning system varies significantly across approaches adopted to establish triggers.