P-502 Objectives: Following the heat wave in August 2003, a heat health watch warning system (HHWWS) was developed, essentially based on a biometeorological indicator and integrated into a national action plan. This study's objective was to evaluate that system in 2004 and 2005 in order to pinpoint the strengths and to propose some scientific and organisational improvements. Methods: The evaluation was carried out in the Institute running the system and with external partners (working group associating the National Weather Bureau and a research laboratory in Climate and Health, consultants, international workshop). This evaluation took into account the following areas: scientific aspects, efficiency of the system and its cost, organisation, cooperation between the different partners, simplicity, flexibility, traceability, adaptability. Results: The evaluation demonstrated it was necessary to revise the alert thresholds, to take into account the uncertainties due to the meteorological forecasts, to integrate qualitative criteria such as atmospheric pollution and to change some meteorological stations which were not very representative. Despite the difficulty for the partners to well understand the biometeorological indicator, the system proved to be quite simple, adaptable even during the working period, well traceable (data, information) and based on good relations between the different partners. The use of health data proved to be heavy, needing a better automation. Concerning the efficiency, the number of alert propositions was high (74) compared to the real over thresholds (25), because of the meteorological forecasts uncertainties and also because of the qualitative criteria taken into account besides the main indicator: this is an indication of quite a protective system. Conclusion: This evaluation allowed to improve the system at a scientific and organisational level. Further improvements should be done, in particular using air masses as possible indicators. But the evaluation has still shown that each country is specific in terms of available data, human resources, financial resources, objectives, and that it might not be useful to try to define a single system adaptable everywhere.
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