Weather conditions influence the health of humans. Changing weather patterns may also cause considerable increase or decrease in the number of deaths. In this paper, we use daily data for Prague, Czech Republic, and the maximum overlap discrete wavelet transform to explore the time scale patterns in the relationship between the average ambient temperature and the number of deaths due to cardiovascular diseases. We summarize several well-known facts, give a short introduction to the maximum

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... ap discrete wavelet transform and study the relationship between several pairs of waveletcoefficients of various levels for the temperature time series and the number of deaths. The results are suggestive of a positive linear relationship between respective wavelet coefficients of the 4th level during summer. More specifically, we have estimated thata one-degree-Celsius increase in the weekly average temperature during summer is accompanied by an increase in the weekly average number of deaths by 0.37 on average.The odds in favor of an increase in the weekly average number of deaths during summerhave been estimated to be 4.22 times higher if an increase in the weekly average temperatureoccurs when compared to the situation when a decrease in the weekly averagetemperature occurs. Further research might be desirable to verify and interpret the results.