Application of the Spatial Synoptic Classification in Evaluating Links between Heat Stress and Cardiovascular Mortality and Morbidity in Prague, Czech Republic

Severe and sustained summer heat waves are associated with increased morbidity and mortality, particularly in mid-latitudinal cities. Reductions of the heat-related mortality following implementation of heat warning systems based on a synoptic approach have been documented in many locations around the world. The weather types (air masses) classification methods consist in identifying oppressive air masses, i.e. those associated with increased mortality, and in the next step, relationships of meteorological (e.g. air temperature, heat index), environmental (PM10, O3) as well as non-meteorological variables (day in sequence, time of season, year) to excess mortality are evaluated within the oppressive air masses. In this study, the widely used ‘Spatial Synoptic Classification' (SSC) method is employed for the first time in heat-related mortality assessment in Central Europe (Prague, Czech Republic) where excess mortality during heat waves represents an important public health issue. The classification is applied into examining links between weather patterns and excess cardiovascular mortality (number of deaths) and morbidity (hospital admissions) in extended summer season (May-September) over 16-year period of 1994-2009. Characteristics of different oppressive air mass spells (Dry Tropical vs. Moist Tropical) and their impacts on cardiovascular mortality and morbidity are compared. Step-wise regression models are identified within the oppressive air masses, and their application in a possible heat warning system in Prague is evaluated by testing on independent data. The results of the SSC approach are compared with a common epidemiological approach based on time-series analysis (Poisson regression, generalized additive models) of daily temperature and mortality data.