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Daily numbers of deaths at a regional level were collected in 16 European countries. Summer mortality was analyzed for the reference period 1998-2002 and for 2003. More than 70,000 additional deaths occurred in Europe during the summer 2003. Major distortions occurred in the age distribution of the deaths, but no harvesting effect was observed in the months following August 2003. Global warming constitutes a new health threat in an aged Europe that may be difficult to detect at the country level, depending on its size. Centralizing the count of daily deaths on an operational geographical scale constitutes a priority for Public Health in Europe.
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C. R. Biologies 331 (2008) 171–178
Epidemiology / Épidémiologie
Death toll exceeded 70,000 in Europe during the summer of 2003
Jean-Marie Robine a,, Siu Lan K. Cheung a, Sophie Le Roy a, Herman Van Oyen b,
Clare Griffiths c, Jean-Pierre Michel d, François Richard Herrmann d
aINSERM, Démographie et santé, CRLC, centre Val-d’Aurelle, parc Euromédecine, 34298 Montpellier cedex 5, France
bUnit of Epidemiology, Scientific Institute of Public Health, J. Wytsmanstraat 14, 1050 Bruxelles, Belgium
cOffice of National Statistics, Mortality Statistics, 1 Drummond Gate, London SW1V 2QQ, London, UK
dDepartment of Rehabilitation and Geriatrics, Geneva Medical School and University Hospitals, 3, ch. Pont-Bochet,
1226 Thonex-Genève, Switzerland
Received 22 August 2007; accepted after revision 2 December 2007
Available online 31 December 2007
Presented by Alain-Jacques Valleron
Daily numbers of deaths at a regional level were collected in 16 European countries. Summer mortality was analyzed for the
reference period 1998–2002 and for 2003. More than 70,000 additional deaths occurred in Europe during the summer 2003. Major
distortions occurred in the age distribution of the deaths, but no harvesting effect was observed in the months following August
2003. Global warming constitutes a new health threat in an aged Europe that may be difficult to detect at the country level,
depending on its size. Centralizing the count of daily deaths on an operational geographical scale constitutes a priority for Public
Health in Europe. To cite this article: J.-M. Robine et al., C. R. Biologies 331 (2008).
©2007 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.
Plus de 70 000 décès en Europe au cours de l’été 2003. Nous avons collecté le nombre quotidien de décès par région dans
16 pays européens et analysé la mortalité estivale pour la période de référence (1998–2002) et pour 2003. Il s’est produit plus de
70 000 décès supplémentaires au cours de l’été 2003. On observe des distorsions importantes dans la distribution par âge des décès,
mais pas d’effet de rattrapage dans les mois suivants. Le réchauffement climatique constitue une nouvelle menace pour la santé des
personnes âgées, qui peut être difficile à détecter au niveau d’un pays, en fonction de la taille de ce dernier. Le décompte centralisé
des décès journaliers à une échelle géographique opérationnelle constitue une priorité de santé publique en Europe. Pour citer cet
article :J.-M. Robine et al., C. R. Biologies 331 (2008).
©2007 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.
Keywords: Human; Elderly; Daily mortality; Europe; Heat wave; Global warming
Mots-clés : Humain ; Personnes âgées ; Mortalité quotidienne; Europe ; Vague de chaleur ; Réchauffement climatique
*Corresponding author.
E-mail address: (J.-M. Robine).
1. Background
Everyone remembers the 15,000 additional deaths
caused by the heat wave of August 2003 in France [1].
1631-0691/$ – see front matter ©2007 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.
172 J.-M. Robine et al. / C. R. Biologies 331 (2008) 171–178
However, four years later, no one knows precisely the
cumulative number of European victims, although more
than 70 scientific reports related to this event have al-
ready been published [2]. A first assessment, made in
March 2004 by the United Nations Environment Pro-
gramme (UNEP), estimated the death toll on a Euro-
pean scale to exceed 30,000 [3]. A similar estimation
was published two years later, although the available
studies pertain to different periods of the summer [4].
A range between 27,000 and 40,000 excess deaths has
been proposed, depending on data sources, methodol-
ogy and reference period [5]. A total higher than 38,000
excess deaths during August 2003 has been declared in
seven European countries [6]. These divergent figures
indicate that a global assessment of excess mortality is
difficult, if not impossible, because no standardized esti-
mates across European countries have been made for the
2003 heat wave [7]. Press releases issued by statistical
institutes referred to major excess mortality, potentially
reaching 13,000 deaths in Spain and 20,000 deaths in
Italy. This situation, in combination with current con-
cerns about global warming [8], led the European Union
to instigate a global study on the excess mortality in Eu-
rope during the summer of 2003.
2. Methods
Mortality in the summer 2003 is compared to the
period 1998–2002. This five-year reference period is a
compromise between the necessity of gathering enough
years to get an average reference and the need of not
being influenced by too far values, which may be due
to higher past mortality level. Daily numbers of deaths
were collected at regional level (NUTS 2 – http://en.
_for_Statistics), from 1 January 1998 onwards, by gen-
der and age, in France and nine neighbouring coun-
tries (Belgium, England, Germany, Italy, Luxemburg,
the Netherlands, Portugal, Spain, and Switzerland) for
which prior information on their involvement in the heat
wave of August 2003 was available [9–16], as well as in
six surrounding countries (Austria, Croatia, the Czech
Republic, Denmark, Poland, and Slovenia), for which
no information was available. The aim of this selec-
tion was to delimit better the area affected by the Au-
gust heat wave. Indeed, it turns out that two countries,
Croatia and Slovenia, were partially affected. The four
remaining unaffected countries were kept as potential
controls for the study. Altogether 19,098,574 daily mor-
tality counts were collected for 177 NUTS belonging to
these 16 European countries. Daily death frequencies
were calculated by dividing, for each year, the daily
number of deaths by the annual total to compare coun-
tries and regions. Assuming no seasonal variations or
daily fluctuations, 0.27% (1/365 ×100)of all annual
deaths should be observed on any given day. Computa-
tions were performed by gender, single age, and NUTS,
and then aggregated for analysis at the requested level.
Seasonality of deaths and the characteristics of the
summer mortality in Europe during the reference pe-
riod of 1998–2002 were analysed to set thresholds for
extreme values. Robust polynomial regression models
(1 to 4 degrees), weighted by the numbers of deaths
in each country, were applied to the mortality profiles
(summer and non-summer) to determine the propor-
tion of variance in the daily death frequency explained
by the days of the year. The multivariate models were
adjusted for year and country by introducing dummy
variables. Such models (in the form: m(d, i, j ) =a0+
a1d1+a2d2+a3d3+a4d4+a5y(i) +a6c(j), where
mis the daily mortality, anare constants, dis the day
of the year at the power 1 to 4, y(i) each year and
c(j) each country) assess the relative contribution of a
specific day within two broad seasons, summer or not
summer, controlling for years and countries. The vari-
ables ‘year’ and ‘country’ allow the secular trend in
mortality decline as well as the geographical variation
to be taken into account. The four selected polynomial
degrees let the principal shapes of the potential rela-
tionship between mortality and days to be appraised
within the two broad seasons. A horizontal linear fit
(a1=0, a2=0, a3=0, a4=0) would mean that mor-
tality is independent of days. A quadratic fit (a2= 0,
a3=0, a4=0) would indicate a single mortality peak
or hollow, whereas higher-degree polynomials would fit
a more complex shape.
The first and third quartiles (Q1and Q3), in combi-
nation with the inter-quartile range (IQR), allow identi-
fication of minor outliers (Q11.5×IQR; Q3+1.5×
IQR) and exceptionally extreme values (Q13×IQR;
Q3+3×IQR) [17].
Variations in daily mortality in combined data of all
the 16 countries were examined by calculating the delta
between the number of daily deaths recorded during
the summer of 2003 and the average number of deaths
recorded on the same day during the reference period.
A positive delta means that the number of deaths in 2003
is higher than the 1998–2002 average, while a negative
delta indicates a lower number. Daily death frequencies
were divided by the value of the median frequency ex-
perienced during the summers of 1998–2002 to estimate
the magnitude of the excess mortality. This conversion
rescales all the frequencies around the unit. It is there-
J.-M. Robine et al. / C. R. Biologies 331 (2008) 171–178 173
fore immediately possible to interpret the daily mortal-
ity on any given day as a multiple of the median value.
Next, daily excess mortality in 2003 was calculated
for each country. Results were grouped per month and
mortality profile. Special attention was devoted to the
mortality peak of August 2003. Maps at NUTS 2 level
allow the geographical boundaries of this mortality cri-
sis to be specified better. In order to identify shifts in
the age of death, we estimated the ratio of 65+as the
proportion of deaths above the age of 65 years on a
given day divided by the average share of the 65+ob-
served over the summer of 2003. A series of such ratios
(by age: 65+,75+,85+and 95+and by gender) were
plotted on the calendar time scale to examine the co-
occurrence in the distortions in the proportion of deaths
involving older people and women. More detailed infor-
mation on the methods used is available on request [18].
3. Results
The distribution of daily deaths between 1998 and
2002 reveals an identical seasonality in the 16 European
countries, with (i) a low summer mortality from June to
September, where the daily mortality appears to be con-
stant, and (ii) non-summer conditions from October to
May, with a rise in mortality from October to Decem-
ber, a winter peak in January and February, followed by
a drop in mortality from March to May. The regression
models with a degree higher than 1 do not improve the
prediction quality for the summer period. In all mod-
els, the summer days explain only between 2% and 3%
of the variance, whereas the year and the country ex-
plain each between 5% and 6%. As this is negligible,
the summer mortality was analysed as a single block.
By contrast, outside of the summer period, the day ex-
plains around 40% of the variance of the daily death
frequency in all models with a degree higher than 1.
The 9760 daily summer death frequencies (122 sum-
mer days ×16 countries ×5 years) experienced in Eu-
rope between 1998 and 2002 are distributed symmet-
rically around a median frequency of 0.2506 (average
0.2525). The distribution seems very concentrated com-
pared to a normal distribution; 50% of observations are
between 0.2377 (25th percentile) and 0.2655 (75th per-
centile). The boundaries defining the extreme values are
0.1961 and 0.3072 for the minor outliers, and 0.1544
and 0.3489 for the exceptional values. 554 days (5.68%)
are outliers of which 174 days (1.78%) are exceptional
Using the delta between the numbers of daily deaths
recorded during the summer of 2003 and the average
number recorded on the same day during years 1998–
Fig. 1. Delta between the number of daily deaths recorded in the sum-
mer of 2003 and the average number of deaths recorded on the same
day during the 1998–2002 reference period for the 16 European coun-
tries studied. DOY 152, the 152nd day of the year corresponds to 1
June, DOY 181 to 30 June, DOY 212 to 31 July, DOY 243 to 31 Au-
gust and DOY 273 to 30 September.
2002, Fig. 1 represents the variations in daily mortality
during the summer of 2003 for the 16 European coun-
tries together. Out of the 122 days, 27 days presented
a delta lower than zero, inducing a total deficit of 5045
deaths compared to 95 days, with a delta higher than
zero, creating a total excess mortality of 74,483 deaths.
Both gaps do not balance each other. Excess mortality
was a characteristic of the summer of 2003 affecting a
major part of Europe. In particular, three main peaks ex-
ceeding 1000 additional daily deaths were observed on
13 June, between 16 and 21 July and on 12 and 13 Au-
gust, days in which the mortality peak was exceptional.
Excess mortality was also observed at the end of June
and persisted during the month of September.
In 2003, out of a total of 1952 summer days in the
16 countries, 145 days (7.5%) are outliers beyond the
boundary of [Q3+1.5×IQR], marking high extreme
values. Fifty days (2.6%) are extreme outliers. This is
more than three times the figures observed during the
1998–2002 period. The countries most affected by these
exceptionally high death frequencies are Luxemburg
(20 days), Portugal (eleven days), France (nine days)
and Italy (four days). The first peak in mid-June is found
mainly in Italy and Croatia and, to a lesser degree, in
Spain. The peak seems to be delayed a few days in Por-
tugal where it occurred on 20 June. All these days cre-
ated a considerable number of excess deaths at the start
of the summer, limited to southern countries. This pe-
riod of excess mortality remained almost unnoticed. The
second peak is centred on 16–21 July and involves the
Netherlands, England and Wales, Belgium, Luxemburg,
France, Germany, Switzerland and, to a lesser degree,
174 J.-M. Robine et al. / C. R. Biologies 331 (2008) 171–178
Spain. Although excess mortality occurred simultane-
ously in all of these countries, it remained unnoticed,
with the exception of the Netherlands [19]. The third
peak, centred on 12 and 13 August is first observed
in France, Italy, Portugal, and Luxemburg. It is clearly
visible in Germany, England and Wales, Belgium and
Switzerland. It also appears, although less sharply, in
the Netherlands and in Spain.
The cumulative daily death frequencies over the
summer of 2003 show a contrast between (i) countries
such as France and Germany, which deviate abruptly
from the anticipated trend during the first two weeks of
August, by cumulating excess mortality, which will not
be compensated later on in the summer, (ii) countries
like Spain and Italy that move far more gradually away
from the trend in several waves covering the beginning
of the summer until the August peak, (iii) countries like
Portugal, which tend towards a deficit of mortality prior
to the August peak and which recover excess mortality
before the end of the summer, and lastly (iv) countries
like England and Wales, which ultimately drift away
only slightly from the anticipated trend, just like the
control countries not affected by the heat wave.
Table 1 presents the excess mortality, both as the
absolute and the percentage difference between the ob-
served daily number of deaths and the average number
of deaths on the same day during the reference period.
The absolute numbers and percentages of the excess
mortality are given by country for the period before,
during and after the summer of 2003 and by month
for the summer period. Overall, more than 80,000 ad-
ditional deaths were recorded in 2003 in the 12 coun-
tries affected by excess mortality, i.e. an excess of 2.5%
compared to 1998–2002. Although about 70,000 out
of these additional deaths occurred during the summer,
over 3000 additional deaths occurred before and there
were more than 8000 deaths in excess afterwards. The
countries most affected by this excess summer mortality
were Luxemburg, Spain, France, and Italy, where mor-
tality increased by 14.3%, 13.7%, 11.8% and 11.6%,
respectively. The female deaths represent 65% of the to-
tal number of the excess deaths during this period.
In August 2003 alone, nearly 45,000 additional
deaths were recorded in the 12 countries, including
15,251 in France (+37%), 9713 in Italy (+21.8%),
7295 in Germany (+11%), 6461 in Spain (+22.9%) and
1987 in England and Wales (+4.9%). In less-populated
countries, the numbers are lower, but excess mortal-
ity can be relatively very significant, as in Luxemburg,
where 73 additional deaths increased mortality by 25%.
Belgium, the Netherlands, and Switzerland each num-
bered about five hundred additional deaths, respectively
+5.3%, +5.2%, and +9.8%. Excess mortality reached
9.9% in Slovenia, with 144 additional deaths, and 6.8%
in Croatia with 269 additional deaths, while mortality
dropped by more than 1% during August 2003 in the
control countries.
August aside, 11,000 additional deaths were recorded
in June (including 5274 in Italy and 4268 in Spain),
over 10,000 in July (including 4318 in Italy and 2751
in Spain), and nearly 5000 in September. Therefore,
France and Italy totalized the same excess mortality
from 1 June to 30 September 2003, of 19,490 and
20,089 excess deaths, respectively, with very different
cumulative profiles during the summer.
4. The mortality crisis of August 2003
The mortality crisis of August extended over the two
weeks between 3 and 16 August. In the 12 countries,
15,000 additional deaths were recorded during the first
week and nearly 24,000 during the second. The ex-
cess mortality ratio reached the exceptional value of
96.5% during the second week in France and very high
values in Portugal (+48.9%), Italy (+45.4%), Spain
(+41.2%), and Luxemburg (+40.8%). Excess mortality
reached 28.9%, 26.7%, and 21.6% in Germany, Switzer-
land, and Belgium, respectively. It exceeded 10% in all
countries, except Denmark, Poland, and the Czech Re-
public. Even in Austria, mortality increased by 12.6%
during this week. Beyond a return to normal, no overall
harvesting effect was observed in the weeks and months
following the mortality crisis of August. Mortality re-
mained high just about everywhere until the end of the
summer. Only in Germany, Italy and Switzerland, slight
drops in deaths after the summer were recorded (see Ta-
ble 1).
The regions most affected by the mortality crisis of
August lie in a southwest–northeast axis (see Fig. 2),
from the Algarve in southern Portugal to Westphalia in
Germany. A secondary axis starts in southern England
and continues towards Latium in central Italy and Croa-
tia. The most significant mortality focal spots are in Île-
de-France and the neighbouring region of Centre, where
mortality recorded between 3 and 16 August is twice
what was expected. Six regions – two in southern Por-
tugal (Algarve and Alentejo) and four in France (Pays
de la Loire, Poitou-Charentes, Burgundy, and Franche-
Comté) recorded a very high excess mortality during
these two weeks (between 65% and 125%). Switzerland
as well as some coastal regions (among others, Brittany
in France and Galicia, Murcia and Valencia in Spain)
seems to have been relatively spared. The southeastern
limits of the mortality crisis are poorly defined due to
J.-M. Robine et al. / C. R. Biologies 331 (2008) 171–178 175
Tab le 1
Delta between the number of deaths recorded in 2003 and the average number of deaths recorded during the 1998–2002 reference period and excess mortality ratio (expressed as a percentage) for
various periods in 2003 (before the summer, during the summer and after the summer) and for various countries
Before summer Summer After summer Total of the year
Nb Ratio June July August September Total Nb Ratio Nb Ratio
Nb Ratio Nb Ratio Nb Ratio Nb Ratio Nb Ratio
Countries affected by the August 2003 heat wave
Belgium 40.01 139 1.72 162 1.97 438 5.31 436 5.57 1175 3.62 1356 5.11 2528 2.41
Switzerland 92 0.34 253 5.30 187 3.89 469 9.81 130 2.75 1039 5.45 148 0.93 984 1.58
Germany 9290 2.55 642 0.98 1159 1.73 7295 10.97 259 0.40 9355 3.56 5760 2.69 12885 1.53
Spain 1464 0.90 4268 15.49 2751 9.64 6461 22.86 1611 6.21 15090 13.68 7249 7.95 20875 5.74
France 3977 1.70 1482 3.60 1706 4.06 15251 36.93 1051 2.62 19490 11.84 3415 2.53 18928 3.55
Croatia 882 3.95 193 4.85 157 3.98 269 6.83 169 4.49 788 5.04 5 0.04 1675 3.29
Italy 5575 2.24 5274 12.12 4318 9.72 9713 21.81 783 1.94 20089 11.63 2487 1.76 23177 4.12
Luxemburg 69 3.47 33 10.81 27 9.29 75 25.00 34 12.22 170 14.34 79 7.85 318 7.95
Netherlands 304 0.50 78 0.71 11 0.10 578 5.24 297 2.79 965 2.20 503 1.42 1771 1.26
Portugal 2068 4.26 220 2.83 100 1.28 2196 27.75 179 2.44 2696 8.73 2072 7.76 2699 2.54
Slovenia 351 4.30 13 0.87 62 4.21 144 9.93 70 4.86 289 4.96 74 1.55 714 3.81
England & Wales 5695 2.41 1080 2.64 504 1.21 1987 4.90 103 0.26 301 0.18 2025 1.44 3369 0.62
Tot a l 3355 0.23 11516 4.50 10137 3.88 44878 17.34 4917 1.99 71449 6.99 8382 0.99 83186 2.50
Countries used as controls
Austria 708 2.12 42 0.71 172 2.86 159 2.63 57 0.99 345 1.45 645 3.30 408 0.53
Czech Republic 2408 5.17 207 2.43 190 2.18 58 0.67 37 0.43 418 1.22 335 1.20 2491 2.29
Poland 1916 1.21 487 1.71 543 1.85 918 3.21 652 2.29 2600 2.26 3436 3.60 4119 1.12
Denmark 113 0.44 43 0.95 92 1.95 49 1.04 14 0.31 170 0.92 92 0.61 191 0.32
Tot a l 4920 1.86 365 0.77 273 0.56 750 1.56 618 1.31 2006 1.05 4325 2.74 1411 0.23
176 J.-M. Robine et al. / C. R. Biologies 331 (2008) 171–178
Fig. 2. Standardized daily death frequencies (1 means equal to the me-
dian death number, 2 means twice the median death number) between
3 and 16 August 2003, in 16 European countries, for 177 NUTS.
the absence of data for Bosnia-Herzegovina and Serbia.
On the most lethal day – 12 August – mortality recorded
in Île-de-France was over five times more than expected.
It was over four times the expected mortality in the Cen-
tre region (France) and twice the expected mortality in
Algarve in Portugal, in six other French regions, in three
Belgian regions, in Piedmont in Italy and in the Greater
London Area in England.
The August mortality crisis caused major distortions
in the deaths’ age and gender structure, which are il-
lustrated in Fig. 3, using France and Italy as examples.
On 12 August, the share of 65+deaths increased by
9.5% in France, the share of 75+deaths increased by
16.5%, the share of 85+deaths by 26.8% and the share
of 95+deaths by 46%. These distortions in the deaths’
age structure imply that excess mortality increased as
age rose. The structure of deaths by gender also varied
considerably during the mortality crisis. The share of fe-
male deaths increased by 21% in France on 12 August
and by 14% in Italy on 13 August.
5. Interpretation
One original aspect of our work was to begin by ana-
lyzing the seasonality of mortality at the European wide
scale. This study disclosed the existence of two broad
mortality patterns: a constant one during the four sum-
mer months from June to September and a platykurtic
pattern (flattened peak, centred on January–February)
during the remaining months. Therefore, the mortality
crisis of the summer 2003 was studied within this con-
More than three years after the 2003 heat wave, the
total number of victims was still unknown on a Euro-
pean scale. The methods used for estimating the ex-
cess mortality covered various periods (from June to
September or in August only) and different popula-
tions (countries, major cities), preventing comparisons
among countries and therefore global appraisal [7].
Fig. 3. Distortion of the death structure by age and gender in France and Italy during the summer of 2003. DOY 152, the 152nd day of the year
corresponds to 1 June, DOY 181 to 30 June, DOY 212 to 31 July, DOY 243 to 31 August and DOY 273 to 30 September.
J.-M. Robine et al. / C. R. Biologies 331 (2008) 171–178 177
Gathering data from 16 European countries, our
study disclosed that more than 70,000 additional deaths
occurred in Europe during the summer of 2003, of
which more than 20,000 before August. Excess mortal-
ity reached exceptionally high levels during the second
week of the August heat wave in France. However,
France and Italy totalized the same excess mortality,
19,490 and 20,089 excess deaths, respectively, with very
different cumulative profiles during the summer. Ob-
viously, this computed amount of excess mortality is
sensitive to the reference period. However, a compari-
son with a French study of the August heat wave using
a 3-year reference period [1] demonstrates a negligible
impact of the duration of the reference period, ranging
from 3 to 5-year, on the results.
Our study is limited to 16 European countries, ba-
sically France and its neighbouring countries, plus a
group of surrounding countries kept as controls. The
southeastern boundaries of the mortality crisis are
poorly defined, as it was not possible to obtain the
necessary data from Bosnia-Herzegovina and Serbia.
These limitations probably lead to an underestimation
of the real death toll in Europe due to the summer of
2003, as Bulgaria, Greece, Romania, and the south of
the Balkans may have been affected by excess mortal-
Although the mortality crisis caused major distor-
tions in the age and gender death structure, increasing
the share of women and oldest ones, no overall har-
vesting effect was observed in the weeks and months
following the mortality crisis. A French study proposed
a late or postponed ‘harvesting’ effect that occurred in
the first months of 2004 [20]. However, a subsequent
study showed that the French regions with excessively
low mortality in 2004 were not the most affected by the
2003 heat wave [21,22]. The most recent studies found
little evidence in favour of a compensating harvesting
effect [23].
Relating the number of death to person-years will
provide, in the next step of our study, a better descrip-
tion of the populations at risk (gender, age groups...).
Nevertheless, the current results, analyzed at the NUTS
2 level, strongly suggest that the excess mortality is not
limited to urban areas.
Our observations showed that during the summer
of 2003, a series of minor mortality crises throughout
Europe, occurring almost unnoticed, led to a signifi-
cant cumulative number of victims in comparison to the
huge number of victims due to the August heat wave.
Global warming may constitute a new threat to health
in an aged Europe [8,24] that may be difficult to mon-
itor at the level of a country or of a major city only.
Centralising the count of daily deaths on a sufficiently
large scale, like grouping neighbouring regions across
the border and countries with small populations, should
improve detecting early excess mortality due to various
causes. Anticipation of excess summer mortality poten-
tially due to global warming [25,26], through daily mor-
tality monitoring alongside meteorological and pollu-
tion warning, may constitute a priority for Public Health
in Europe.
Barbara Leitner, Statistik Österreich, Austria, Her-
man van Oyen and Bianca Cox, Scientific Institute
of Public Health, Belgium, Robert Jurak and Maga
Francic, Croatian Central Bureau of Statistics, Croatia,
Terezie Kretschmerova, Czech Statistical Office, Czech
Republic, Jesper Marcussen, National Board of Health,
Denmark, Eric Jougla, INSERM–CépiDc, France, Ste-
fan Rübenach, Federal Statistical Office, Germany, Sil-
via Bruzzone, ISTAT, Italy, Guy Weber, direction de la
Santé, Luxembourg, Carel Harmsen, Central Bureau of
Statistics, The Netherlands; Artur Satora, Central Statis-
tical Office of Poland, Poland, Eduarda Góis, Instituto
Nacional de Estatistica, Portugal, Raquel Álvarez Es-
teban, Instituto Nacional de Estadistica, Spain, Tatjana
Rokavec, Institute of Public Health of the Republic of
Slovenia, Slovenia; Dominik Ullmann, Office Fédéral
de la Statistique, Switzerland, Clare Griffiths, Office
for National Statistics, United Kingdom are thanked,
as well as Anne Scherrer-Herrmann for editorial help.
This study was supported by the EU Community Ac-
tion Programme for Public Health (Grant Agreement
No. 2005114).
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... When maximum temperature lies between 36-38 0 C = Mild Heat Wave When maximum temperature lies between 38-40 0 C = Moderate Heat Wave When maximum temperature lies between 40-42 0 C = Severe Heat Wave When maximum temperature >43 0 C = Extreme Heat Wave Heat wave is emerging as a great threat worldwide. The 2003 European heat wave was the deadliest event in Europe causing fatalities of over 70000 people across Europe with France being the worst-hit [4]. More than 87% of all disaster deaths were due to heat related complications between 2000-2016 [5]. ...
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As a consequence of worldwide warming of atmosphere, heat waves are becoming more intense, frequent and widespread. Bangladesh, being a tropical country, is at a high risk of this extreme weather event. Heat waves have been accounted to significant rise in morbidity and mortality rates in recent years. For this reason, an attempt has been made to simulate a heat wave which occurred in the month of May, 2017 using Advanced Research WRF model. The WRF model was run for seven days on a single domain-of 10km horizontal resolution using six hourly GFS data. The model performance has been evaluated by analyzing temperature, relative humidity, wind speed and surface level pressure considering their sultriness on thermal stress. Analysis of observed human thermal stress during the heat wave event has also been made extensively for eight divisional stations spread across the country using bioclimatic index, Physiologically Equivalent Temperature (PET). Finally, a comparison between observed and model simulated PET has been made.
... In 1980, 10,000 individuals died in the United States because of a heat wave [2]. In July of 1995, it has executed more than 700 individuals in Chicago [3], and in August of 2003, more than 70,000 deaths were recorded in Europe [4]. Extreme heat has been observed to be the deadliest climate-related risk in certain areas [5]. ...
... The relative risk of cardiovascular death was 2.39 on the day with the highest number of deaths 107 . An 11% increase in hospital admissions owing to dehydration, heat stroke and heat exhaustion was observed, especially in patients with underlying CVD (such as hypertension) and diabetes 110 112 ). In July and August of 2010, a heatwave was recorded in Russia that produced tem peratures >40 °C 113 . ...
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Climate change is the greatest existential challenge to planetary and human health and is dictated by a shift in the Earth’s weather and air conditions owing to anthropogenic activity. Climate change has resulted not only in extreme temperatures, but also in an increase in the frequency of droughts, wildfires, dust storms, coastal flooding, storm surges and hurricanes, as well as multiple compound and cascading events. The interactions between climate change and health outcomes are diverse and complex and include several exposure pathways that might promote the development of non-communicable diseases such as cardiovascular disease. A collaborative approach is needed to solve this climate crisis, whereby medical professionals, scientific researchers, public health officials and policymakers should work together to mitigate and limit the consequences of global warming. In this Review, we aim to provide an overview of the consequences of climate change on cardiovascular health, which result from direct exposure pathways, such as shifts in ambient temperature, air pollution, forest fires, desert (dust and sand) storms and extreme weather events. We also describe the populations that are most susceptible to the health effects caused by climate change and propose potential mitigation strategies, with an emphasis on collaboration at the scientific, governmental and policy levels. The relationship between climate change and health outcomes is complex. In this Review, Rajagopalan and colleagues describe the environmental exposures associated with climate change and provide an overview of the consequences of climate change, including air pollution and extreme temperatures, on cardiovascular health and disease.
... International researchers Fouillet et al., 2007;Hajat et al., 2007;Ishigami et al., 2008;Kovats & Kristie, 2006;Páldy et al., 2005;Rooney et al., 1998;Vicedo-Cabrera et al., 2021) have shown a clear link between high outdoor temperatures and the risk of death. During the 2003 European heatwave, it is estimated that more than 70, 000 people lost their lives (Robine et al., 2008). In addition to health risks, heatwaves also cause direct and indirect financial losses, such as increased cooling energy and water use, increased health care costs and drought damage (Ahead, 2013;Patz et al., 2005). ...
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Extreme weather events, including heatwaves, are escalating with the changing climate. High outdoor temperatures increase morbidity and mortality. Heat vulnerability indices (HVIs) tend to neglect or only simplistically consider the impact of the building in their analyses. This research aims to implement the reliability analysis used in other fields of civil engineering to study the overheating of buildings. In this method, the internal temperatures in different building types are determined with dynamic simulations. These results are used to create fragility curves. Historical weather data has also been used to produce the hazard curve. With these two, the overheating probability of buildings in a city can be analysed. Based on the methodology, the vulnerability of a district of Budapest was investigated as a pilot area. From the results, it can be seen that precast concrete panel buildings are the most vulnerable, while the least vulnerable category is the single-family house for an average internal temperature limit of 26 °C. In a sensitivity analysis, adaptation measures such as shading and enhanced natural ventilation uniformly reduced the overheating probability of the panel building. The methodology developed here makes it possible to incorporate the overheating of buildings more objectively in heat vulnerability analysis.
... The combination of these factors has been shown to increase heat-related morbidity and mortality for those living in cities. During the 2003 European heat wave that was responsible for over 70,000 deaths throughout Europe (Robine et al. 2008), approximately 52% of the heat-related deaths in West Midlands, England were contributed to the UHI effect (Heaviside et al. 2016). Studies have shown that with greater nighttime minimum temperatures, the risk of mortality increases because it reduces the amount of time that individuals are able to recover from extreme daytime temperatures (EPA 2006;Laaidi et al. 2012;Murage et al. 2017). ...
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An urban heat island (UHI) is a phenomenon where the temperatures within cities are greater than those of surrounding rural areas due to human activity and physical properties of urban surfaces. One method that has been investigated as a way to mitigate the UHI phenomenon is to increase the surface albedo in cities, which reflects a greater amount of solar radiation away from these surfaces compared to conventional materials (e.g., dark asphalt shingles). In this study, we utilize the Weather Research and Forecasting (WRF) model to investigate the UHI under different scenarios during a July 2012 heat wave event in the Kansas City metropolitan area (KCMA). Two cool roof simulations are implemented to determine the effectiveness of this mitigation strategy on reducing temperatures within the KCMA. The first scenario represents “newly installed” cool roofs with an albedo of 0.8 and the second with “aged” cool roofs with an albedo of 0.5. Results indicate that cool roof materials were able to mitigate the UHI effect by up to 0.64 °C during the evening, causing the onset of the UHI effect to be delayed until later in the day. Cool roofs were also shown to have important impacts on the surface energy balance, affecting both sensible and ground storage heat fluxes, and the planetary boundary layer.
For both financial and environmental applications, tail distributions often correspond to extreme risks and an accurate modeling is mandatory. The peaks‐over‐threshold model is a classic way to model the exceedances over a high threshold with the generalized Pareto distribution. However, for some applications, the choice of a high threshold is challenging and the asymptotic conditions for using this model are not always satisfied. The class of extended generalized Pareto models can be used in this case. However, the existing extended model have either infinite or null density at the threshold, which is not consistent with tail modeling. In the present article, we propose new extensions of the generalized Pareto distribution for which the density at the threshold is positive and finite. The proposed extensions provide better estimate of the upper tail index for low thresholds than existing models. They are also appropriate for high thresholds because in that case, the extended models simplify to the generalize Pareto model. The performance and flexibility of the models are illustrated with the modeling of temperature exceeding a low threshold and non‐zero precipitations recorded in Montreal. For non‐zero precipitation, the very low threshold of 0 is used.
The rivers and their floodplains are integrated systems. The biodiversity of the Lower Danube River (LDR), in terms of species and habitats, is strongly linked with its hydro-geomorphic-diversity and the natural regions it passes. Human activities, directly and indirectly, are the primary cause which has induced changes in hydrologic regime, longitudinal and lateral connectivity, floodplain geomorphology and function, biodiversity of the river waters and riparian zone. During the twentieth century, particularly after World War II, the LDR has undergone alteration of physical habitat, significant landscape changes, and ecological loss as a result of hydropower damming works and their associated water reservoirs, floodplain embankment, wetlands drainage, chemical pollution, eutrophication, and invasion of exotic species. The extensive embankments and drainage work along LDR in Romania converted about 80% of the annual flooded zone of the floodplain area primarily into agricultural region, obviating its essential connection with the river. Few areas, including reed marshes, meadows, floodplain forests, large shallow lakes, fluvial islands, and the braided section of the river named “the Small Island of Brăila”, have been preserved in natural regime in order to preserve valuable samples of biodiversity, hydro-morpho dynamic processes, and particular fluvial landforms. Most of them are ecotonal areas that have an increased and extremely dynamic biodiversity. This increased turnover of species is exacerbated by anthropogenic factors, which sometimes they can negatively influence certain species of fauna, such as sturgeons, modifying their habitats for reproduction, feeding and resting. After the 1990s, due to the change of the political system in Romania and following integrated programs of the Danube Riparian States, some areas of the engineered floodplain are subject to ecological restoration and integrated management in order to provide convenient ways of reconciliation between nature and human society for a sustainable development. The currently Ramsar and Natura 2000 sites network designed along the LDR provides the national and international legal framework of protection and conservation of wildlife and its habitats. The objectives of this chapter are to present a review of: (1) human interventions from the last century that lead to alteration, degradation, and irreversible losses of habitats along the LDR valley, (2) restoration projects of former floodplain areas, and (3) biodiversity protection and conservation actions carried out over the area in the last decades.
Natural hazards, including droughts, are processes and phenomena that can trigger a negative impact on the environment, society and various economic sectors. The present chapter aims to identify spatial peculiarities of drought characteristics (frequency, duration, affected area) and to analyse drought hazard, vulnerability and risk in the Lower Danube region. The study area includes administrative regions from Romania (counties) and Bulgaria (districts) located along the Danube River, which is the common administrative border between the two countries. The northward and southward Danube territories are part of the most important agricultural areas of both countries, where natural landscapes have been significantly transformed by anthropogenic activities which contributed to the removal of the natural vegetation and its replacement with cultivated plants and urban areas. Drought characteristics and associated hazards were analysed using the Standardized Precipitation-Evapotranspiration Index (SPEI-3, 6, 12) for the period 1981–2019. Population density and land cover/land use data were taken into account in the drought vulnerability assessment. Drought hazard and vulnerability were considered in the drought risk evaluation which allowed the identification of the regional drought “hotspots”. Results show a very high level of drought risk associated to short-term drought (SPEI-3) in the central and eastern parts of the study region. In the case of long-term drought (SPEI-12), a reduction in areas showing a very high drought risk level is observed. The administrative regions located in the western part of the study area have very low and low levels of drought risk.
Deadly humid heat conditions exceeding human thermoregulatory capacity have been reported, however, whether and where the deadly humid heat events occur consecutively across the land surface are largely unknown. We calculate the maximum consecutive days of deadly humid heat, defined as daily maximum wet‐bulb temperature (TWmax) ≥ 35°C, for observations of 9278 meteorological stations and for simulations of 14 global climate models. We further define short and long deadly humid heatwaves as a period of 3‐4 and ≥ 5 consecutive days with daily TWmax ≥ 35 °C, respectively. Our analyses show that six stations in some subtropical regions have experienced deadly humid heat with daily TWmax ≥ 35 °C, but only occurs in individual days. Deadly humid heatwaves increase exponentially as the global mean temperature rising. When limiting global warming within 1.5°C, long deadly humid heatwaves will not occur across the land surface, and short deadly humid heatwaves will only emerge in some drylands but not in humid areas. Under 2°C warming, 0.09% of the global land, 0.42% of the human population, and 0.56% of the global centers of crop diversity are projected to be exposed to long deadly humid heatwaves. Meanwhile, 18% of the deadly humid heatwaves lasting ≥ 3 consecutive days will occur in humid areas; the fractions are projected to rapidly increase in humid areas as temperature rising further. At the end of the century, the percentage of land areas and human population exposed to deadly humid heatwaves lasting ≥ 3 consecutive days are expected to be 76‐times higher than that under 1.5°C warming level. Our finding suggests that keeping global warming within 1.5°C will significantly constrain the emergence of prolonged deadly humid heatwaves, and thus reduce the risk of the human population especially outdoor agricultural workers.
Public health measures need to be implemented to prevent heat-related illness and mortality in the community and in institutions that care for elderly or vulnerable people. Heat health warning systems (HHWS) link public health actions to meteorological forecasts of dangerous weather. Such systems are being implemented in Europe in the absence of strong evidence of the effectiveness of specific measures in reducing heatwave mortality or morbidity. Passive dissemination of heat avoidance advice is likely to be ineffective given the current knowledge of high-risk groups. HHWS should be linked to the active identification and care of high-risk individuals. The systems require clear lines of responsibility for the multiple agencies involved (including the weather service, and the local health and social care agencies). Other health interventions are necessary in relation to improved housing, and the care of the elderly at home and vulnerable people in institutions. European countries need to learn from each other how to prepare for and effectively cope with heatwaves in the future. Including evaluation criteria in the design of heatwave early warning systems will help ensure effective and efficient system operation.
The scientific case for global warming is overwhelming. So what next for the IPCC? Helping policymakers decide what to do now may require radical reform, reports Jim Giles.
The relative overall stability of the population of continental Europe is accounted for by population growth in western Europe alone, mainly from immigration. Central Europe has negative natural increase, with net migration being positive only in Russia. This contrasts with the United States, where natural increase and net migration are substantially positive. The total fertility rate in the 15-member EU, driven chiefly by the older members, has risen slightly since 2002 and now stands at 1.55 children per woman, 0.5 children below the United States. Fertility trends and levels present quite contrasting pictures across the whole of the continent, with TFRs ranging from 1.20 in Belarus to 2.04 in Iceland. Fertility in central and eastern Europe had fallen to very low levels, but the decline now seems to have abated in many countries. Rates have broadly stabilized in western Europe, apart from Scandinavia where they have risen significantly. Women's completed fertility is continuing to decrease almost everywhere, apart from the United States. This reduction in completed fertility is accompanied by an increase in permanent infertility. The mean length of life continues to increase in almost all European countries, although the countries of the former Soviet Union have still not returned to their 1960s levels. While female life expectancy at birth is among the highest in the world in some western European countries (Spain, Switzerland and France), it is still almost 2 years lower than in Japan.
The book represents the results of the cCASHh study that was carried out in Europe (2001-2004), co-ordinated by WHO and supported by EU Programmes. The flood events in 2002 and the heat wave of August 2003 in Europe had given evidence in a rather drastic way of our vulnerability and our non preparedness. The project has produced very important results that show that the concurrent work of different disciplines in addressing public health issues can produce innovative and useful results, providing an approach that can be followed on other public health issues. The project has shown that information on potential threats can be extremely useful in preparing the public for adverse events as well as facilitating the response when the events occur. This is a new dimension for public health which reverses the traditional thinking: from identifying and reducing specific risk factors, to taking action on the basis of prediction and early warning to prevent health consequences in large populations.
The heat wave that struck France in 2003 has been accompanied with an estimated 15 000 excess deaths. This paper stresses the difficulties of the epidemiology of such an event. The relevant clinical and biological information is incomplete or even inaccessible and many of the deaths are due to multiple factors. The data presently available indicate that the deaths occurred in persons already vulnerable, and that the heat wave caused a five- to eight-month loss of lifetime for the affected individuals. There is a noteworthy similarity between the profiles of this exceptional summer mortality surge, and those of many past winters when similar or larger excess mortalities have occurred without as yet eliciting much public attention. To cite this article: A.-J. Valleron, A. Boumendil, C. R. Biologies 327 (2004).