Introduction

The French warning system for heat waves is based on meteorological forecasts. Near real-time health indicators are used to support decision-making, e.g. to extend the warning period, or to choose the most appropriate preventive measures. They must be analysed rapidly to provide decision-makers useful and in-time information. The objective of the study was to evaluate such health indicators.

Methods

A literature review identified a range of possible mortality and morbidity indicators. A reduced number were selected, based on several criteria including sensitivity to heat, reactivity, representativity and data quality. Two methods were proposed to identify indicator-based statistical alarms: historical limits or control charts, depending on data availability. The use of the indicators was examined using the 2006 and 2009 heat waves.

Results

Out of 25 possible indicators, 5 were selected: total mortality, total emergency calls, total emergency visits, emergency visits for people aged 75 and over and emergency visits for causes linked to heat. In 2006 and 2009, no clear increases were observed during the heat waves. The analyses of real-time health indicators showed there was no need to modify warning proposals based on meteorological parameters.

Discussion

These findings suggest that forecasted temperatures can be used to anticipate heat waves and promote preventive actions. Health indicators may not be needed to issue a heat wave alert, but daily surveillance of health indicators may be useful for decision-makers to adapt prevention measures.

Background: July 2006 was the first major heat wave in France after the creation of a heat prevention plan. Understanding its impacts on health will help improving the efficiency of this plan. We assessed the mortality impact of the heat wave, and investigated the influence of the heat prevention plan.

Methods: The study focused on nine French cities. A Poisson regression model was used to analyze the correlation between temperature, air quality and mortality. An additional spline of time was introduced to capture an additional heat wave effect. Heat-action days defined by the prevention plan were introduced as a dummy variable.

Results: 411 extra deaths were observed in the nine cities during the 2006 heat wave. Unlike the 2003 heat wave, no additional heat wave effect was observed in 2006. The maximum daily relative risk of mortality varied from 1.45 in Strasbourg (IC 95% [1.01-2.08]) to 1.04 in Lille (IC 95% [0.92-1.18]). The impact on mortality of the implementation of heat-action days was non-significant and highly variable depending on the cities, with a combined excess of relative risk of -3.3% (IC 95% [-10.3%; 4.4%]).

Conclusions: Although no specific heat wave effect was observed, warm temperatures and air pollution were still responsible for a significant excess mortality in France. The absence of a specific heat wave effect may be partly explained by the prevention plan. It may also indicate that higher temperatures are required to observe a mortality outburst.