Heat waves in Budapest A Páldy *, J Bobvos **, A Vámos ** * - “Fodor József” National Center for Public Health, National Institute of Environmental Health, Budapest ** - Capital Institute of the National Public Health Service, Budapest ** - Capital Institute of the National Public Health Service, Budapest

Background Analysis of effect of TEMP by time series method,, Budapest,

WinterSummer Association of temperature and mortality in Budapest,

Effect of 5 o C increase of daily mean temperature on mortality in winter and summer, Budapest,

Estimation of the effect of extreme hot days, 2003 Risk estimate based on the time-series analysis of Risk estimate based on the time-series analysis of

Risk estimate based on the time-series analysis of RR / 1 o C = 1,025 95% CI 1.023; increase of mortality by 1 o C (β) = 1,795% CI 1.569; increase of mortality by 1 o C increase of mean TEMP (β) = 1,795% CI 1.569; days ∑heat °C excess death CI min CI max heat wave ,6108,3126,9 above mean temperature ,2297,9

Excess mortality on extreme hot days and on days in 2003 [Mean No of deaths on days 26,6 o C] * No of days TEMP>26,6 o C

Excess mortality on extreme hot days and on days when mean TEMP was higher than the average, Budapest – Excess mortality on extreme hot days and on days when mean TEMP was higher than the average, Budapest – temperaturedayscasemeandiff. excess mortality > 22,4 °C ,3 4,9 397,1 < 22,4 °C ,3 > 26,6 °C ,2 7,9 167,5 < 26,6 °C ,2

Methods and data of analysis of heatwaves,

We investigated the health impact of exterme temperature episodes between by applying the modified methodology of ENHIS1 House_E1 indicator and by own method.  Cumulated daily mortality following the onset of the period of extreme heat with a 3-day delay was extracted from the average of the cumulated daily mortality calculated from the previous 3 years for the same period (WHO).  Cumulated daily mortality for the identical period of extreme heat was extracted from the average of the cumulated daily mortality calculated from the previous 3 years for the same period (HUN).

The temperature data were retrieved from the National Meteorological Service, (Pestlörinc Station).The descriptive analysis of the data showed that the yearly mean temperature was the highest in 2002 (11,9 o C), the highest daily mean was recorded in 2003 (29,5 o C) The temperature data were retrieved from the National Meteorological Service, (Pestlörinc Station). The descriptive analysis of the data showed that the yearly mean temperature was the highest in 2002 (11,9 o C), the highest daily mean was recorded in 2003 (29,5 o C) Results

The weekly mean temperature in summer

The daily mean TEMP in years , summer period

The number of extreme hot days increased from 4 to 17 days

The “heatwave” periods were identified: 3 or more consecutive days 3 or more consecutive days when daily mean temperature was above >26,5 o C ( 97 % frequency )when daily mean temperature was above >26,5 o C ( 97 % frequency ) fromto No of days total

Mean daily mortality ∑ mean Total67,560,861,163,2 Cardiovascular32,932,532,532,6 Respiratory1,91,82,32,0 The health outcomes were all cause, cardiovascular and respiratory deaths for the permanent population of Budapest. The mortality data source was the Central Statistical Office.

Daily mean mortality by month (May-Sept),

Heatwaves in Budapest 2001

No of deathsNo of excess_1No of excess_ SUM7357 No of excess death_1= No of death of given day in 2001 – mean No of death s of the prev. 3 years ( on the same day) No of excess death_2= No of death of given day in mean No of deaths of the year 2001 (67)

Heatwawes in Budapest 2002

No of deathsNo of excess_1No of excess_ SUM SUM2612 No of excess death_1= No of death of given day in 2002 – mean No of death s of the prev. 3 years ( on the same day) No of excess death_2= No of death of given day in mean No of deaths of the year 2002 (61)

Heatwawes in Budapest 2003

No of excess death_1= No of death of given day in 2003 – mean No of death s of the prev. 3 years ( on the same day) No of excess death_2= No of death of given day in mean No of deaths of the year 2003 (61)

TM_ WHO CM_ WHO RM_ WHO TM_ HUN CM_ HUN RM_ HUN total number of excess deaths 42,3117,0 9,0 197,3174,08,3 mean excess death count/day 1,845,090,398,587,570,36 % of daily excess deaths Excess death computed by WHO and Hungarian method

CONCLUSION By comparing the two methods for evaluating the effect of heat waves it seems that in case of Budapest extreme heat has an impact on mortality on the hot days. By comparing the two methods for evaluating the effect of heat waves it seems that in case of Budapest extreme heat has an impact on mortality on the hot days. We could not state a delayed effect of extreme temperature on mortality using 3-day-lag. We could not state a delayed effect of extreme temperature on mortality using 3-day-lag. In case when 2 heatwaves occurred in one summer period, the effect of the first heatwave was much stronger than the second one. In case when 2 heatwaves occurred in one summer period, the effect of the first heatwave was much stronger than the second one. To assess the impact of heat wave the mean of 3-day death counts of the previous 3 years is not a stable reference value. To assess the impact of heat wave the mean of 3-day death counts of the previous 3 years is not a stable reference value.