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Proposal for territorial distribution of the 2010 EU road safety target
Accident Analysis and Prevention 41 (2009) 1008–1015
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Proposal for territorial distribution of the 2010 EU road safety target A. Tolón-Becerra a,∗ , X. Lastra-Bravo b , F. Bienvenido-Bárcena c a
University of Almeria, Area of Engineering Projects, Ctra Sacramento s/n, La Ca˜ nada de San Urbano, 04120 Almeria, Spain University of Almeria, Area of Engineering Projects, Junta de Andalucía Scolarship, Spain c University of Almeria, Dept. of Computer Science, Spain b
a r t i c l e
i n f o
Article history: Received 18 November 2008 Received in revised form 19 May 2009 Accepted 8 June 2009 Keywords: Road mortality Quantitative road safety target EU transport policy International comparisons Europe Spain
a b s t r a c t European Union (EU) road safety policies include reduction in road fatalities by 50% during 2000–2010. The original territorial distribution of this target is uniform, as all the territories have to halve the number of fatalities regardless of their previous record. We propose a simple method of distributing the total effort required to reach the EU target of halving fatalities in a territory in such a way that those areas with a higher proportion of fatalities (relative to their populations) have the highest targets and the sum of all of the areas is the 50% reduction. The distribution function we use here is based on an inverse logarithmic function selected from among several alternative functions analyzed in an initial study. This use of weighted distribution functions has been applied since 2000 by the EU in other policies, such as the use of renewable energies. We applied the proposed distribution function to two territorial aggregation levels in the EUROSTAT Nomenclature of Territorial Units for Statistics (NUTS): NUTS0 for EU-15 and EU-25 Member States, and NUTS3 for the 50 Spanish provinces, comparing the new and old targets with the real achievements for the 2000–2006 period, and new and old targets for the 2000–2010 period. This is a simple proposal for modification of target distribution that can be further improved using other parameters, such as road or weather conditions. © 2009 Elsevier Ltd. All rights reserved.
1. Introduction 1.1. Road mortality Road accidents constitute a major public health problem worldwide, causing around 1.2 million deaths and over 50 million injuries each year. Around 16 000 people die every day as a result of injuries caused by accidents, representing 12% of mobility worldwide, which represent the third cause of overall mortality and the main cause of death in the age group 1–40 (WHO, 2004). In the 25 Member States of the European Union (EU-25),1 52 536 people died in road accidents in 2000, and over 1 900 000 were injured, and the fatalities was 33 519 in 2006. It is the first cause of mortality in the population aged 14–25, and an estimated one in three people will be injured in a road accident in the course of their lives.
∗ Corresponding author. Tel.: +34 950015902; fax: +34 950015491. E-mail addresses: [email protected] (A. Tolón-Becerra), [email protected] (X. Lastra-Bravo), [email protected] (F. Bienvenido-Bárcena). 1 The member states of the European Union 25 (EU-25) are: Austria, Belgium, Cyprus, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, and the United Kingdom. 0001-4575/$ – see front matter © 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.aap.2009.06.005
From 2003 to 2006 in Spain over 14 000 people died in road accidents while around 565 000 suffered injuries. The approximate cost per death was 1 000 000 Euros, and twice that amount for people suffering long-term injuries (DGT, 2007; AEC, 2007). The vast majority of road accidents involve private traffic. This situation is not helped by the popular misconception that road accidents are isolated facts, rather than a social problem involving other economic, environmental, professional and emotional aspects (AEC, 2006). Trawen et al. (2002) reported an increase of 6% per annum in the average cost per fatality in 11 developed countries, from US$ 0.9 million in 1990 to US$ 1.56 million in 1999. The EU estimated the direct cost of road accidents in 2000 at 45 000 million Euros. The indirect costs were three to four times higher, reaching a total of 160 000 million Euros, equivalent to 2% of the GNP of the 15member European Union2 (EU-15) (EC, 2001). In short, road accidents constitute a serious public health problem requiring the political involvement of policy makers at regional and national levels, as well as of all the agents in the field of road safety (EC, 2001; WHO, 2004). The policies implemented must be
2 The member states of the former European Union 15 (EU-15) were Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom.
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effective, coordinated and sustainable measures, capable of achieving positive results in the reduction of road accidents and all the other aspects related to transport. Their performance and effectiveness should be assessed by comparisons between countries (Achterberg, 2006; Page, 2001; Richardson, 2005). Despite the above, it is true that since the 1990s there has been a downturn in the number of accidents, fatalities and injuries on the road in Europe (CARE, 2008; EC, 2001). But further reduction is one of the biggest challenges in the field of the road safety. Important progress has been made in this field over the past 30–35 years, allowing us to develop and detect effective strategies to prevent collisions and injuries or reduce their number (Elvik, 2008a,b; WHO, 2004). Road safety figures vary in both time and space. Variations in time have been the object of considerable study and analysis by researchers and policy makers. Despite the fact that most of the factors involved in road safety are linked to space, reducing the geographic scale in the spatial analysis of road accidents is an important tool for understanding regional differences and enabling us to focus on the measures to be implemented (Deboosere and Gadeyne, 2002; Eksler et al., 2008; Eksler and Lassarre, 2008; Hakim et al., 1991; Lassarre and Thomas, 2005). 1.2. Road mortality in Europe and in Spain in 2000 The analysis of road mortality in 2000 shows that the basic indicators are very heterogeneous, varying considerably among EU Member States, and even more so among Spanish provinces. Of the 25 EU Member States, seven presented lower road mortality rates than the EU-25 mean. Malta, the United Kingdom, Sweden and the Netherlands stand out, with rates of 3.9, 6.1, 6.7 and 6.8 fatalities per 100 000 inhabitants, respectively. Analysing absolute values, countries with higher population and surface area (Germany, France, the United Kingdom, Italy, Spain and Poland) presented the highest numbers of fatalities. However, Page (2001) established the elasticity of the population of these countries at 0.96, meaning that a 10% increase in population produces a 9.6% increase in the number of fatalities, as long as the remaining variables remain constant. Eksler et al. (2008) estimated the elasticity of the population density as −0.32, that is to say a 10% increase in density means a 3.2% reduction in the number of fatalities. Of the 50 Spanish provinces, Soria had by far the highest road mortality rate, with 84.7 deaths per 100 000 inhabitants. This is six times higher than the Spanish mean (14.4), while the remaining provinces varied between 7.5 and 37.3 fatalities. The effect of population can be observed in provinces with a low population such as Soria, Cuenca, Huesca, Burgos, Teruel and Zamora, which have a low absolute number of fatalities and a relatively high mortality rate. The opposite proves true for the most populated provinces like Madrid, Barcelona, Valencia, Sevilla or Vizcaya. In the statistical analysis of the data, the mean and the standard deviation are the parameters that describe best and in the simplest way the variations of spatial data (Lassarre and Thomas, 2005). The differences between the means for the EU-15 and the EU-25 areas are not great, but they differ significantly in comparison to the average value for Spanish provinces. The standard deviation is greater when the number of regions (n) increases, and when the geographic scope is smaller, as in the Spanish provinces (Table 1). 1.3. Evolution of road mortality 2000–2006 in Europe and in Spain Although the overall evolution of road mortality in the period 2000–2006 is quite irregular, the number of fatalities in most EU Member States follows a downward trend (Table 2). By 2006 the EU-
1009
Table 1 Mean, standard deviation, minimum and maximum values of the mortality rate for NUTSa regions in 2000. Level
EU-25 states EU-15 states Spanish provinces
n
25 15 50
Population (hundred thousands)
Road fatalities
Avg.
Min.
Max.
Avg.
Min.
Max.
180.85 251.49 8.07
3.80 4.34 0.91
821.64 821.64 52.05
2101.44 2733.93 115.42
15 76 39
8079 8079 443
a This analysis covers 25 and 15 EU Member States (NUTS0) and 50 Spanish provinces (NUTS3), and is geographically based on the EUROSTAT’s NUTS 2003 regional classification (EUROSTAT, 2005).
25 Member States had achieved a reduction of 24.9% in the number of fatalities in comparison with 2000, with an average reduction per country of 22.3 ± 15.95%. The EU-15 Member States had been more successful, achieving a reduction of 28.0% and a mean of 28.1 ± 13.2%. While more than a third of the countries of the EU25 had made significant progress, it should be noted that in some countries road mortality actually increased over this period. The results for Spanish provinces over the period 2000–2006, shown in Table 3, present a more irregular evolution. Comparison of the road mortality data for 2000 and 2006 reveals heterogeneous results, ranging from a 68.8% decrease in Soria to a 13.8% increase in Huelva. The provinces of Huelva, Salamanca, Malaga, Almería and Cuenca increased or maintained their values of road mortality. The remaining provinces have made varying degrees of progress: in 9 provinces road mortality fell by less than 15%, in 15 provinces it fell by between 15% and 30%, in 14 provinces by 30–45%, and in 7 it fell by over 45%. 2. Desirable threshold and dynamic target values for the reduction of road mortality In the field of road safety, quantitative targets represent the results that policy makers wish to achieve for a certain geographic area (group of countries, country, region, etc.) in a certain period Table 2 Road mortality in the Member States of the EU-25 in the period 2000–2006. Index = 100 for year 2000. 2001
2002
2003
2004
2005
2006
EU-25 EU-15
2000 100 100
96.0 97.2
94.7 94.1
88.8 87.4
82.8 79.6
79.4 76.5
75.1 72.0
Lithuania Hungary Estonia Slovakia United Kingdom Ireland Italy Finland Slovenia Poland Greece Cyprus Sweden Austria Belgium Czech Republic Spain Germany Netherlands Malta Latvia Denmark France Portugal Luxembourg
100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
110.1 103.3 97.6 97.8 100.5 98.6 100.6 109.3 88.8 87.9 92.3 88.3 98.7 98.2 101.1 89.8 95.5 93.0 91.8 106.7 87.9 86.6 101.0 89.0 92.1
108.7 119.1 109.3 97.1 100.0 90.0 101.4 104.8 85.9 92.6 80.2 84.7 94.8 98.0 88.8 96.3 92.6 91.2 91.2 106.7 88.0 93.0 94.8 88.2 81.6
110.6 110.5 80.4 102.7 102.2 80.6 91.2 95.7 77.3 89.6 78.8 87.4 89.5 95.4 82.6 97.4 93.5 88.1 95.0 106.7 83.8 86.8 75.0 82.2 69.7
117.3 108.0 83.3 96.0 94.1 89.5 85.6 94.7 87.5 90.8 82.0 105.4 81.2 90.0 79.1 93.0 82.2 77.9 74.3 86.7 81.3 74.1 68.5 68.9 64.5
118.6 106.5 82.8 89.2 93.2 95.5 87.5 95.7 82.4 86.5 81.4 91.9 74.5 78.7 74.1 86.5 76.9 71.5 69.3 113.3 69.6 66.5 65.8 66.4 60.5
118.4 108.8 100.0 92.2 92.1 88.0 85.3 84.9 83.7 83.3 81.4 77.5 75.3 74.8 72.7 71.5 71.0 67.9 67.5 66.7 64.1 61.5 58.3 51.6 47.4
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Table 3 Road mortality in Spanish provinces over the period 2000–2006. Index = 100 for year 2000.
Huelva Salamanca Málaga Almería Cuenca Cádiz Huesca Albacete Lugo Cáceres Córdoba Murcia Ciudad Real Ávila Toledo Valladolid Guadalajara Ourense Jaén Segovia León Cantabria Granada Sevilla Tarragona
2000
2001
2002
2003
2004
2005
2006
100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
129.3 125.0 111.2 105.5 82.6 118.6 100.0 113.4 102.1 118.2 89.2 114.7 107.1 112.8 82.0 112.7 125.6 87.1 105.6 123.1 101.9 82.5 92.7 101.8 83.0
137.9 143.8 111.2 96.3 87.0 105.2 109.0 101.5 110.6 109.1 97.3 96.9 110.6 123.1 77.4 122.8 102.6 109.7 88.7 130.8 94.3 109.5 84.7 92.1 87.3
110.3 122.9 128.5 82.6 118.8 121.7 117.9 88.1 103.2 92.4 110.8 106.1 98.8 120.5 102.3 86.1 102.6 103.2 94.4 100.0 81.9 87.3 78.1 111.0 88.5
86.2 131.3 124.1 99.1 81.2 122.7 94.0 82.1 85.1 112.1 82.4 103.1 76.5 87.2 72.9 70.9 66.7 87.1 93.0 128.2 83.8 68.3 76.6 107.9 83.6
113.8 93.8 113.8 97.3 85.5 97.9 100.0 80.6 72.3 69.7 100.0 101.8 77.7 102.6 98.5 76.0 112.8 71.0 74.7 87.2 63.8 50.8 73.7 80.5 73.9
113.8 108.3 106.0 100.0 100.0 95.9 94.0 91.0 90.4 89.4 86.5 85.9 84.7 84.6 82.0 79.8 79.5 79.0 78.9 76.9 76.2 76.2 75.2 75.0 74.6
of time (European Road Safety Observatory, 2006). The establishment of threshold values and quantitative targets is a catalyst for the efforts of the different agents involved in road safety, aware that individually they would not have a direct bearing on the outcome of road safety programmes (Loo et al., 2005; Wong et al., 2006; Yannis et al., 2008). It has been found that the most ambitious quantitative targets generate a greater impact on the policy makers and on the implementation of safety programmes (Elvik, 1993). Countries that set out to improve road safety by implementing specific policies and defining clear targets were successful in reducing road mortality, e.g. the UK in 1983, Spain in 1991 and the Netherlands in 1972 (Lassarre, 2001). For Elvik (2008a,b), setting targets of road safety is an attractive idea which requires strong political commitment, although this was not the case in Norway. Given this scenario, the European Union set itself the target of halving the number of fatalities between 2000 and 2010. This goal was reflected in the White Paper “European transport policy for 2010: time to decide”. In this document are designated the national or local authorities as being responsible for achieving the proposed goals in each country. The Commission also reserved the right to propose regulatory measures in the report of 2005 if the number of fatalities were not reduced, mainly in the candidate countries (EC, 2001, 2003, 2006). The White Paper does not specify how this target should be achieved, so each Member State could consider that its aim is to halve its own number of road fatalities. We believe that our goal of reducing road mortality, which effectively shapes a country’s road safety policies, should differ for each geographic area (Lassarre and Thomas, 2005). The higher the mortality rate in a given area, the more ambitious that area target should be, considering that geographic areas with highly ambitious quantified road safety targets have been more successful than areas with less ambitious or nonquantified targets (Elvik, 1993, 2003; European Road Safety Observatory, 2006; Wong et al., 2006). The reduction, therefore, should not be linear of the same for all Member States, as it is neither fair nor logical to obligate countries with lower road mortality rates to reduce them by the same percentages. The states with the highest initial rates should make a greater effort to reduce them. As background for weighted overall policies, we highlight the EU energy policy, provided for in the “Directive of the European Parlia-
Castellón Illes Balears Alicante Zamora La Rioja Valencia Madrid ˜ A Coruna Teruel Girona Burgos Pontevedra Lleida Asturias Badajoz Las Palmas Barcelona Palencia Zaragoza S.C. Tenerife Guipúzcoa Álava Navarra Vizcaya Soria
2000
2001
2002
2003
2004
2005
2006
100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
105.0 103.0 90.7 98.4 118.6 95.1 98.5 87.7 65.9 96.0 90.6 100.7 75.6 65.1 74.3 86.2 98.4 120.0 79.0 98.9 83.7 96.7 89.8 80.0 53.3
128.0 75.8 84.0 63.9 91.5 93.0 93.6 83.6 73.2 104.1 109.4 80.1 85.9 80.5 85.3 76.7 90.1 120.0 70.2 92.6 97.7 81.7 77.1 85.7 37.7
123.0 84.9 87.6 83.6 101.7 100.8 91.6 87.7 87.8 89.2 102.8 78.2 82.2 99.3 88.1 92.2 85.8 73.3 94.2 75.5 96.5 76.7 70.3 100.0 33.8
95.0 83.0 80.4 70.5 117.0 90.5 76.7 71.3 78.1 66.9 67.0 61.6 72.6 72.5 93.6 75.9 76.5 62.2 75.4 81.9 58.1 55.0 70.3 69.5 46.8
88.0 79.4 83.0 70.5 86.4 79.0 70.1 73.3 95.1 73.0 68.9 66.2 74.8 70.5 66.1 71.6 71.3 104.4 63.2 78.7 48.8 51.7 70.3 35.2 40.3
73.0 70.9 70.6 70.5 69.5 69.1 68.8 66.7 65.9 65.5 64.2 63.6 63.0 62.4 61.5 60.3 59.6 57.8 53.2 52.1 48.8 45.0 42.4 39.1 31.2
ment and of the Council on the promotion of the use of energy from renewable sources amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC” European Parliament and European Council (2009). The Directive sets an overall EU target of 20% target for the overall share of energy from renewable sources, and determines weighted or individualized targets for each Member State according to their GDP. Consequently, this study proposes a weighted modulation of the reduction coefficients based on the initial road mortality rate, taking 2000 as the reference year for its application. The desired value of road mortality would always be zero as the ultimate, albeit utopian goal (Tolón et al., in press). Objective progress targets towards this goal must be dynamic and redefined over time, varying according to the area in question. The targets for each area should be obtained as a function of that area’s distance from the desired value, in such a way that all areas converge towards it. In this way, the reduction coefficient, expressed in relative terms of improvement per unit, should vary between 1 (i.e. a hypothetical case in which all the population die in road accidents) and 0 (i.e. no deaths in road accidents). Since the EU aims for a reduction coefficient of 0.5 (mortality rate in 2010/mortality rate in 2000), on a more local scale the progress would have to be greater if the initial distance from the desired value (0) is greater. The present work applies this reasoning in two phases. Firstly the EU is considered as a geographic unit (contemplating two scenarios: EU-25 and EU-15), taking each Member State as a subunit. The sum of road fatalities of all the sub-units, once the corresponding modulated coefficients of reduction are applied, will result in half the number of fatalities from 2000 in the EU-25 and EU-15. Secondly, the results obtained for Spain (in the two scenarios: EU-25 and EU-15), are modulated using the distribution formula on a smaller scale in which the Spanish State is the geographic unit. In this case the sub-units are the 50 provinces, and modulated reduction coefficients are generated for each one. Subsequently, the road mortality rates generated using the proposed methodology are contrasted with the real data obtained in 2006. Finally, new targets are proposed for the reduction of road mortality in EU-25 countries by 2015.
A. Tolón-Becerra et al. / Accident Analysis and Prevention 41 (2009) 1008–1015
3. Methodology We propose a methodology to calculate weighed coefficients of reduction of absolute road mortality at various geographic levels using a weighted distribution, through an inverse logarithmic function of distribution based on the initial mortality rate (2000). For each geographic unit (i), the mortality rate is the number of fatalities (Fi ) in a year divided by the total population (Pi ) at the beginning of the year, expressed per 100 000 inhabitants: Mi =
Fi × 100 000 Pi
The initial rate of mortality was used because it expresses the severity of the social problem, and as it is the only homogenous statistic at international level (Page, 2001). The inverse logarithmic function was proposed because it adapts to the objectives of the study as regards obtaining modulated coefficients of reduction. Furthermore, it is coherent with the expressed principle that the reduction in road fatalities must be higher in those areas where the problem is greater. To achieve the EU target for 2010 of halving the number of fatalities from 2000, the following initial premise was considered: F2010 = c × F2000
(1)
where c is the total residual coefficient, complementary to the reduction coefficient, and F the absolute value of fatalities, i.e. the sum of the fatalities in each geographic sub-unit Fi : F=
i=n
Fi
(2)
i=1
Therefore, for the EU-25 and EU-15 geographical units: FEU(2010) = 0.5 × FEU(2000) and for each geographical sub-unit, in this case the EU Member States: Fi(2010) = ci × Fi(2000)
(3)
ci
where is the residual coefficient of each geographical sub-unit. This coefficient was calculated using an inverse logarithmic distribution function, depending on its initial fatality rate Mi : ci = f (Mi(2000) ) = a(ln Mi(2000) )−1
(4)
where a is the factor that modulates the weighting coefficient ci . To calculate the value of a, first replace Eq. (4) in Eq. (3): Fi(2010) = (a(ln Mi(2000) )−1 )Fi(2000)
n a × Fi(2000) i=1
(6)
ln Mi(2000)
therefore: a=
n
F(2010)
F /ln Mi(2000) i=1 i(2000)
=
functions gave inconsistent results as negative reduction for safer countries (justifying the elimination of these alternative distributions). The logarithmic distribution takes account of the differences in a smooth way. This methodology can also be applied to smaller geographic areas like Spain, where the total geographic unit is the Spanish state and the geographic sub-units are its provinces. In this case, the distribution formula is used, and the total residual coefficient c for the Spanish unit is the one obtained previously from the general targets of the EU for this state. In this way, new results are obtained as residual coefficients ci , for each province. We have applied this methodology on two levels of territorial aggregation, corresponding to NUTS0 (Member States of the EU-15 and EU-25) and NUTS3 (50 Spanish provinces) of the Nomenclature of Territorial Units for Statistics. In the analysis of Spanish provinces, the autonomous cities of Ceuta and Melilla were not included, because they are small units that tend to produce uncertain results due to the low number of fatalities and population (Deboosere and Gadeyne, 2002; Eksler et al., 2008). Temporal analysis has been carried out using data of the EU states and Spanish provinces from the period 2000 to 2006. In the selection of databases, the homogeneity of definitions was considered the main factor. In the processing of international data, not only in the field of road safety, this homogeneity is a prerequisite for meaningful comparisons, giving scientific validity to the study. At present, the number of fatalities is the only comparable data valid for all the countries, considering that the databases use the same international definitions, or have used a coefficient to correct the differences between definitions (Luoma and Sivak, 2007; Page, 2001). The road mortality data for EU countries are taken from the statistics published by CARE, and population and surface area data from EUROSTAT (EC, 1995). CARE (2006) defines “person killed at 30 days” as “death within 30 days of a road accident”, applying correction coefficients for countries that have a different definition in their national statistics. The coefficients were proposed by the EU Member States, and they are applied to the absolute values of “killed person”. In the case of Spain, the values of fatalities correspond to those published by the “Dirección General de Tráfico” (DGT), and the statistics of population and surface area come from the “Instituto Nacional de Estadística” (INE) (INE, 2008). DGT defines a “killed person” as “any person who died as a result of the accident, either in the act or within the following 30 days”, in line with the international definition.
4. Results
(5)
then, as F(2010) is the sum of the number of fatalities in each geographical sub-unit, Fi(2010) , we have: F(2010) =
1011
n
c × F2000
F /ln Mi(2000) i=1 i(2000)
We calculated a weighting factor a for both the EU-25 and EU15, from which we obtained the residual coefficients c for each Member State in both scenarios. The inverse logarithmic distribution function was selected, after testing empirically different distribution functions (as inverse quadratic or cubic ones) because it equilibrates the requirements of reduction in all the sub-units and a more ambitious reduction for those with worse actual behaviour. Alternative distribution
4.1. Results of the application of the methodology on the European scale By applying the proposed methodology, we obtained a set of target values for the reduction of fatalities for the EU-25 and EU15 Member States for 2010, as shown in Table 4. The higher the country’s initial mortality rates, the greater the reduction coefficients. Two clear examples are Latvia, with a reduction coefficient of 62.5% in the case of the EU-25 and Greece, with 59.1% for the EU-15. The total number of fatalities in absolute terms for each country is reduced unevenly, but in such a way that the total sum would achieve the EU’s overall target. In addition, the great difference in mortality rates between Member States is considerably reduced over time, changing from an initial range of 4.0–26.7, to one of 3.4–10.8. It is worthy of note that the results obtained for each particular country differ depending on the scenario considered (EU-25 or EU15). For instance, in the case of Spain the reduction coefficient is higher for the EU-15 than for the EU-25 (55.2% vs. 53.9%). However,
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Table 4 Weighted rates of reduction for EU-25 and EU-15 Member States. c = 0.5
EU-25
EU-15
Regions
Fatalities 2000
Mortality rate 2000
c
Reduction (%)
Fatalities 2010
Mortality rate 2010
Latvia Greece Portugal Lithuania Luxembourg Poland Cyprus Slovenia Estonia Czech Republic Spain Belgium France Austria Hungary Italy Slovakia Ireland Denmark Germany Finland Netherlands Sweden United Kingdom Malta
635 2037 1877 641 76 6294 111 313 204 1486 5777 1470 8079 976 1200 6649 628 418 498 7503 396 1082 591 3580 15
26.7 18.7 18.4 18.3 17.5 16.3 16.1 15.8 14.9 14.5 14.4 14.4 13.4 12.2 11.7 11.7 11.6 11.1 9.3 9.1 7.7 6.8 6.7 6.1 4.0
0.37 0.42 0.42 0.42 0.43 0.44 0.44 0.45 0.46 0.46 0.46 0.46 0.47 0.49 0.50 0.50 0.50 0.51 0.55 0.56 0.60 0.64 0.65 0.68 0.90
62.5 58.0 57.8 57.6 57.0 55.9 55.7 55.4 54.4 53.9 53.9 53.8 52.5 50.8 50.0 49.9 49.9 48.8 44.9 44.4 39.6 35.9 35.2 31.9 10.3
238 856 793 272 33 2776 49 140 93 685 2664 679 3837 480 600 3329 315 214 274 4175 239 694 383 2439 13
10.8 7.6 7.4 8.2 6.5 7.3 6.2 7.0 7.2 6.8 6.0 6.4 6.2 5.8 6.0 5.7 5.9 5.0 5.0 5.0 4.5 4.2 4.2 4.0 3.4
the average values of reduction, for each of the two hypotheses of aggregation, present only slight differences and both are around 50% (48.8% for the EU-25 and 49.1% for the EU-15).
c
Reduction (%)
0.41 0.41
59.1 58.9
833 771
7.4 7.2
0.42
58.2
32
6.4
0.45 0.45 0.46 0.48
55.2 55.1 53.8 52.2
2590 660 3731 467
5.8 6.2 6.1 5.6
0.49
51.3
3237
5.5
0.50 0.54 0.54 0.59 0.62 0.63 0.66
50.2 46.5 45.9 41.2 37.7 36.9 33.8
208 267 4059 233 674 373 2371
4.8 4.9 4.9 4.4 4.0 4.1 3.9
Fatalities 2010
Mortality rate 2010
the case of the EU-25. These figures imply reduction coefficients of 53.9% or 55.2%, respectively, fixing the Spanish residual coefficient as c = 0.448 for the EU-15 scenario, and as 0.461 for the EU-25 one. Using the proposed methodology, the target values of reduction for each province were then computed. Also the new mortality rates were calculated, using the estimated population in 2010 according to the INE (Table 5). The number of fatalities, in absolute terms, is reduced unevenly in each province, but in such a way that the total number is reduced by 53.9% or 55.2%, according to the scenario considered. Once again it is clear that the reduction coefficients generated are higher when the initial mortality rates are higher, and that the great differences in mortality rates between provinces are reduced considerably. Indeed, in this case the results are even clearer, as the
4.2. Results of the application of the methodology on the local scale (Spanish provinces) Maintaining the premise that a linear reduction of road fatality targets is inadequate, the proposed formula was then applied to Spain as an example of a smaller territorial unit (NUTS3). For this purpose the values obtained for Spain in both previously considered scenarios were used as general national targets. Taking into account previous results, Spain must not exceed 2590 fatalities in 2010, if we consider only the countries of the EU-15, or 2664 in Table 5 Weighted rates of reduction for Spanish provinces.
1 2 3 4 5 6 7 8 9 10 ... 41 42 43 44 45 46 47 48 49 50
Fatalities 2000
Mortality rate 2000
Soria Lleida Cuenca Huesca Burgos Teruel Zamora Tarragona Segovia Girona
77 135 69 67 106 41 61 165 39 148
S.C. Tenerife Valencia Jaén Córdoba Sevilla Barcelona Vizcaya Málaga Cádiz Madrid
94 243 71 74 164 443 105 116 97 391
c = 0.461 c
Reduction (%)
84.7 37.3 34.3 32.6 30.5 30.0 30.0 27.6 26.6 26.2
0.28 0.34 0.35 0.36 0.36 0.36 0.36 0.37 0.38 0.38
72.1 65.8 65.0 64.5 63.8 63.6 63.6 62.7 62.3 62.1
11.5 11.0 11.0 9.6 9.5 9.4 9.3 9.1 8.6 7.5
0.51 0.52 0.52 0.55 0.55 0.55 0.56 0.56 0.57 0.61
49.3 48.4 48.4 45.3 44.9 44.6 44.4 43.8 42.5 38.6
EU-25 scenario
c = 0.448
Fatalities 2010
Mortality rate 2010
c
Reduction (%)
EU-15 scenario
21 46 24 24 38 15 22 62 15 56
23.3 11.2 11.6 10.9 10.8 10.5 11.7 7.8 9.4 7.7
0.27 0.33 0.34 0.35 0.35 0.35 0.35 0.36 0.37 0.37
72.9 66.7 65.9 65.5 64.8 64.6 64.6 63.7 63.3 63.1
21 45 23 23 37 15 22 60 14 55
22.7 10.9 11.3 10.6 10.5 10.2 11.3 7.6 9.2 7.5
48 125 37 40 90 245 58 65 56 240
4.8 5.0 5.6 5.1 4.9 4.6 5.2 4.3 4.6 3.8
0.49 0.50 0.50 0.53 0.54 0.54 0.54 0.55 0.56 0.60
50.7 49.9 49.8 46.8 46.4 46.1 45.9 45.4 44.1 40.3
46 122 36 39 88 239 57 63 54 233
4.7 4.9 5.4 5.0 4.8 4.5 5.1 4.2 4.5 3.7
Fatalities 2010
Mortality rate 2010
A. Tolón-Becerra et al. / Accident Analysis and Prevention 41 (2009) 1008–1015
1013
Table 6 Percentages of reduction in the number of fatalities in the period 2000–2006 (Index = 0 for year 2000), and percentages of reduction for 2010.
Fig. 1. Percentage of real reduction of the number of fatalities in road accidents, in the period 2000–2006 vs. modulated percentage reduction for 2006 and 2010. Index = 100 for year 2000, in the order of greatest to smallest real reduction.
range of mortality rates is greatly reduced, 7.5–84.7 vs. 3.8–23.3 in the EU-25 scenario. As regards the EU-15 scenario, the new range is slightly smaller: 3.7–22.7.
Huelva Salamanca Málaga Almería Cuenca Cádiz Huesca Albacete Lugo Cáceres Córdoba Murcia Ciudad Real Ávila Toledo Valladolid Guadalajara Ourense Jaén Segovia León Cantabria Granada Sevilla Tarragona a b
4.3. Comparison of the real evolution of road mortality in the period 2000–2006 with the proposed weighted values We compared the percentages of reduction experienced by EU Member States during the period 2000–2006 with those expected according to the modulation carried out for 2006 (Fig. 1). This modulation was calculated by making a proportional linear distribution of the percentage calculated for 2010. It can be seen that overall the EU Member States have reduced the number of fatalities, almost reaching the target proposed in this study (30%), with better values for the EU-15 (28.03%) than for the EU-25 (24.95%). However, when the comparisons are made for each country, there are some significant differences. Malta is the country with the best results, with a 33.3% reduction in the number of fatalities in 2006, quite superior to the 6.2% reduction expected for the year 2010, according to the proposed model. The number of fatalities in Lithuania, on the contrary, increased over the same period by 18.4%. According to the proposed model this country should have reduced the number of fatalities by 34.6%. Only six countries show sufficient progress to achieve the proposed reduction. The linear extrapolations of data series from the period 2000–2006 to the year 2010 has resulted in positive projections for most of the countries. The reduction percentages are even higher than those established in this study, in line with the 50% reduction previously accorded by all countries. Lithuania, Hungary, Estonia and Slovakia present the worst results, and their projections do not invite optimism as regards achieving the EU goal. In Spain, comparing the results obtained in 2006 with the proposed reduction values for 2010 (see Table 6), 48% of the Spanish provinces present a reduction of between 30 and 65 percentage points of difference. This implies that a lot of work remains to be done in order to reduce the number of fatalities in these provinces. Vizcaya is the only one that reduced its number of fatalities to 2006 as proposed in this study (by 61.0% as opposed to the 44.4% proposed), and as such it is an example for other provinces to follow. Other provinces that have made significant progress are Guipúzcoa, Tenerife, Navarra, Soria, Barcelona, Álava and Madrid, with a difference of 10 points between both values.
2006
2010a
2010b
−13.8 −8.3 −6.0 0.0 0.0 4.1 6.0 9.0 9.6 10.6 13.5 14.1 15.3 15.4 18.1 20.3 20.5 21.0 21.1 23.1 23.8 23.8 24.8 25.0 25.5
−2.7 −5.4 −22.6 6.2 11.3 0.2 6.1 34.2 33.6 32.7 13.3 14.3 41.1 21.3 18.5 53.9 32.2 38.4 39.5 29.3 53.5 62.0 47.1 30.0 40.1
51.2 52.7 43.8 59.4 65.0 42.5 64.5 57.5 61.9 55.5 45.3 53.3 57.0 60.9 61.6 55.3 60.8 57.1 48.4 62.3 59.3 49.9 56.2 44.9 62.7
2006 Castellón Illes Balears Alicante Zamora La Rioja Valencia Madrid ˜ A Coruna Teruel Girona Burgos Pontevedra Lleida Asturias Badajoz Las Palmas Barcelona Palencia Zaragoza S.C. Tenerife Guipúzcoa Álava Navarra Vizcaya Soria
27.0 29.1 29.4 29.5 30.5 30.9 31.2 33.3 34.2 34.5 35.9 36.4 37.0 37.6 38.5 39.7 40.4 42.2 46.8 47.9 51.2 55.0 57.6 61.0 68.8
2010a 35.3 46.5 41.6 54.8 34.8 42.1 56.2 53.8 28.9 61.7 62.2 70.6 52.3 48.9 49.7 56.9 64.1 62.8 65.2 65.8 89.5 98.0 80.3 99.4 106.9
2010b 59.4 58.3 52.3 63.6 60.1 48.4 38.6 56.8 63.6 62.1 63.8 55.9 65.8 52.9 55.8 51.6 44.6 61.6 58.8 49.3 51.2 59.3 59.8 44.4 72.1
Extrapolate data. Weighted fatalities, EU-25 scenario.
4.4. Proposal of reduction of the mortality rate in the EU for 2015 By 2010, if we extrapolate the values of 2006, overall the EU-25 will achieve a 36.2% reduction. With this result the current EU target would not be reached. We therefore considered that a new commitment should be formulated and agreed for 2015. By this time, those countries with worse rates, especially those incorporated into the EU in 2004, would be able to redesign and/or improve their road safety policies and programmes.
Table 7 Weighted rates of reduction proposed for EU-25. c = 0.4
2006
Regions
Fatalities
Mortality rate
Reduction (%)
2015 Fatalities
Mortality rate
Lithuania Latvia Estonia Greece Poland Slovenia Hungary Cyprus Slovakia Czech Republic Belgium Italy Spain Portugal Austria Ireland Luxembourg France Finland Germany Denmark United Kingdom Sweden Netherlands Malta
759 407 204 1657 5243 262 1303 86 579 1063 1069 5669 4104 969 730 365 36 4709 336 5091 306 3298 445 730 11
22.3 17.7 15.2 14.9 13.7 13.1 12.9 11.2 10.7 10.4 10.2 9.6 9.4 9.2 8.8 8.7 7.7 7.5 6.4 6.2 5.6 5.5 4.9 4.5 2.7
72.4 70.2 68.5 68.2 67.3 66.6 66.5 64.5 63.9 63.3 63.0 62.2 61.7 61.3 60.6 60.3 57.9 57.4 53.8 52.9 50.4 49.5 46.2 42.7 14.2
210 121 64 526 1716 87 437 31 209 390 395 2145 1572 375 287 145 15 2008 155 2398 152 1666 240 418 9
6.4 5.5 4.9 4.6 4.6 4.4 4.5 3.8 3.9 3.9 3.7 3.7 3.5 3.5 3.4 3.2 3.0 3.2 2.9 2.9 2.8 2.7 2.5 2.5 2.4
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Fig. 2. Real evolution of mortality rates in the period 2000–2006 and the modulated proposal for the period 2006–2015 for the EU-25 Member States and the Spanish provinces.
Considering the dynamism that should prevail in the formulation of quantitative targets, a reduction of 60% in the number of fatalities is proposed for the period 2006–2015, equivalent to an approximate reduction of 70% with respect to 2000. We have applied the formula for modulation of the reduction coefficients to the Member States of the EU-25 (see Table 7), and to the Spanish provinces. The new target rates of reduction for 2015 offer different values for each Member State but maintain the target of 70% reduction for the EU as a whole. Once again the states with higher initial mortality rates are assigned higher coefficients of reduction in the number of fatalities, while in those with lower initial mortality rates the progresses would be smaller. The initial dispersion of mortality rates between states would be reduced even more over time, changing from a range of 2.7–22.3 to one of 2.4–6.4. The application of the methodology to Spain and its provinces for the same period (2006–2015) means that the range of road mortality in the different provinces is greatly reduced, changing from the range of 3.6–33.1 to 2.3–8.0 (Fig. 2). Fig. 2 shows the real evolution of mortality rates during the period 2000–2006 in the EU-25 Member States and the provinces of Spain, and the weighted values proposed for the period 2006–2015. It can be seen that both the mean and the range of mortality rates is reduced with time, particularly due to the greater reduction in those areas with higher initial mortality rates.
5. Conclusion The evolution of road mortality has been uneven and with very heterogeneous values of reduction, both in EU Member States and in the Spanish provinces. The countries that have made most progress are those that have implemented road safety policies and programs in the past. These countries differ considerably from those countries incorporated into the EU in 2004, whose overall statistics show the need for greater effort and resources to achieve the EU target as stated in the Transport White Paper. To achieve the desirable values, the objective target values of progress should be implemented in a pragmatic way, in accordance with the context and characteristics of each geographic area. The heterogeneity of the statistics underlines the need for “weighted” decentralized decisions to be taken at different territorial levels with a view to achieving a common aim. Under this
premise, the proposed methodology allows us to distribute targets for the reduction of road mortality according to the situation in the starting year for each geographic area. The proposed model has the advantage of being simple to apply. However, its results are orientative and should not be taken as absolute values, but rather as references for the formulation of road safety policies. References Achterberg, F., 2006. Raising Compliance with Road Safety Law—1st Road Safety PIN Report. European Transport Safety Council, Brussels. ˜ Asociación Espanola de la Carretera (AEC), 2006. Libro Verde de la Seguridad Vial. In: Proceedings of the Congreso internacional de prevención de accidentes de tráfico “La sociedad civil ante el reto de la seguridad vial”, Madrid. ˜ Asociación Espanola de la Carretera (AEC), 2007. Anuario de la carretera 2007. Tecnipublicaciones, Madrid. CARE-EU road accident database, 2006. Glossary. European Commission, Luxemburg. CARE-EU road accident database, 2008. Road safety evolution in EU, September 2008. European Commission, Luxemburg. Deboosere, P., Gadeyne, S., 2002. Can regional patterns of mortality in Belgium be explained by individual socio-economics characteristics? Reflets et perspectives de la vie économique 4 (XLI), 87–103. Dirección General de Tráfico (DGT), 2007. Anuario Estadístico General 2006. Centro de Publicaciones, Madrid. Eksler, V., Lassarre, S., 2008. Evolution of road disparities at small-scale level: example of Belgium. Journal of Safety Research 39, 417–427. Eksler, V., Lassarre, S., Thomas, I., 2008. Regional analysis of road mortality in Europe. Journal of the Royal Institute of Public Health 122, 826–837. Elvik, R., 1993. Quantified road safety targets: a useful tool for policy making? Accident Analysis and Prevention 25 (5), 569– 583. Elvik, R., 2003. An overview of target-setting in Europe. In: Best in Europe Conference on Targeted Road Safety Programmes in the EU, European Transport Safety Council, Brussels. Elvik, R., 2008a. Road safety management by objectives: a critical analysis of the Norwegian approach. Accident Analysis and Prevention 40, 1115–1122. Elvik, R., 2008b. Dimensions of road safety problems and their measurement. Accident Analysis and Prevention 40, 1200–12010. European Commission, 2001. White Paper—European Transport Policy for 2010: Time to Decide. Office for Official Publications of the European Communities, Luxembourg. European Commission, 2003. European Road Safety Action Programme, halving the number of road accident victims in the European Union by 2010: a shared responsibility. Communication from the commission, Brussels. European Commission, 2006. Keep Europe moving—sustainable mobility for our continent mid-term review of the European Commission’s 2001 Transport White Paper. Communication from the commission to the Council and the European Parliament, Brussels. European Commission, 1995–2008. Statistical Office of the European Communities—EUROSTAT. European Parliament and European Council, 2009. Directive of the European Parliament and of the Council on the promotion of the use of energy from
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Accident Analysis and Prevention journal homepage: www.elsevier.com/locate/aap
Proposal for territorial distribution of the 2010 EU road safety target A. Tolón-Becerra a,∗ , X. Lastra-Bravo b , F. Bienvenido-Bárcena c a
University of Almeria, Area of Engineering Projects, Ctra Sacramento s/n, La Ca˜ nada de San Urbano, 04120 Almeria, Spain University of Almeria, Area of Engineering Projects, Junta de Andalucía Scolarship, Spain c University of Almeria, Dept. of Computer Science, Spain b
a r t i c l e
i n f o
Article history: Received 18 November 2008 Received in revised form 19 May 2009 Accepted 8 June 2009 Keywords: Road mortality Quantitative road safety target EU transport policy International comparisons Europe Spain
a b s t r a c t European Union (EU) road safety policies include reduction in road fatalities by 50% during 2000–2010. The original territorial distribution of this target is uniform, as all the territories have to halve the number of fatalities regardless of their previous record. We propose a simple method of distributing the total effort required to reach the EU target of halving fatalities in a territory in such a way that those areas with a higher proportion of fatalities (relative to their populations) have the highest targets and the sum of all of the areas is the 50% reduction. The distribution function we use here is based on an inverse logarithmic function selected from among several alternative functions analyzed in an initial study. This use of weighted distribution functions has been applied since 2000 by the EU in other policies, such as the use of renewable energies. We applied the proposed distribution function to two territorial aggregation levels in the EUROSTAT Nomenclature of Territorial Units for Statistics (NUTS): NUTS0 for EU-15 and EU-25 Member States, and NUTS3 for the 50 Spanish provinces, comparing the new and old targets with the real achievements for the 2000–2006 period, and new and old targets for the 2000–2010 period. This is a simple proposal for modification of target distribution that can be further improved using other parameters, such as road or weather conditions. © 2009 Elsevier Ltd. All rights reserved.
1. Introduction 1.1. Road mortality Road accidents constitute a major public health problem worldwide, causing around 1.2 million deaths and over 50 million injuries each year. Around 16 000 people die every day as a result of injuries caused by accidents, representing 12% of mobility worldwide, which represent the third cause of overall mortality and the main cause of death in the age group 1–40 (WHO, 2004). In the 25 Member States of the European Union (EU-25),1 52 536 people died in road accidents in 2000, and over 1 900 000 were injured, and the fatalities was 33 519 in 2006. It is the first cause of mortality in the population aged 14–25, and an estimated one in three people will be injured in a road accident in the course of their lives.
∗ Corresponding author. Tel.: +34 950015902; fax: +34 950015491. E-mail addresses: [email protected] (A. Tolón-Becerra), [email protected] (X. Lastra-Bravo), [email protected] (F. Bienvenido-Bárcena). 1 The member states of the European Union 25 (EU-25) are: Austria, Belgium, Cyprus, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, and the United Kingdom. 0001-4575/$ – see front matter © 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.aap.2009.06.005
From 2003 to 2006 in Spain over 14 000 people died in road accidents while around 565 000 suffered injuries. The approximate cost per death was 1 000 000 Euros, and twice that amount for people suffering long-term injuries (DGT, 2007; AEC, 2007). The vast majority of road accidents involve private traffic. This situation is not helped by the popular misconception that road accidents are isolated facts, rather than a social problem involving other economic, environmental, professional and emotional aspects (AEC, 2006). Trawen et al. (2002) reported an increase of 6% per annum in the average cost per fatality in 11 developed countries, from US$ 0.9 million in 1990 to US$ 1.56 million in 1999. The EU estimated the direct cost of road accidents in 2000 at 45 000 million Euros. The indirect costs were three to four times higher, reaching a total of 160 000 million Euros, equivalent to 2% of the GNP of the 15member European Union2 (EU-15) (EC, 2001). In short, road accidents constitute a serious public health problem requiring the political involvement of policy makers at regional and national levels, as well as of all the agents in the field of road safety (EC, 2001; WHO, 2004). The policies implemented must be
2 The member states of the former European Union 15 (EU-15) were Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom.
A. Tolón-Becerra et al. / Accident Analysis and Prevention 41 (2009) 1008–1015
effective, coordinated and sustainable measures, capable of achieving positive results in the reduction of road accidents and all the other aspects related to transport. Their performance and effectiveness should be assessed by comparisons between countries (Achterberg, 2006; Page, 2001; Richardson, 2005). Despite the above, it is true that since the 1990s there has been a downturn in the number of accidents, fatalities and injuries on the road in Europe (CARE, 2008; EC, 2001). But further reduction is one of the biggest challenges in the field of the road safety. Important progress has been made in this field over the past 30–35 years, allowing us to develop and detect effective strategies to prevent collisions and injuries or reduce their number (Elvik, 2008a,b; WHO, 2004). Road safety figures vary in both time and space. Variations in time have been the object of considerable study and analysis by researchers and policy makers. Despite the fact that most of the factors involved in road safety are linked to space, reducing the geographic scale in the spatial analysis of road accidents is an important tool for understanding regional differences and enabling us to focus on the measures to be implemented (Deboosere and Gadeyne, 2002; Eksler et al., 2008; Eksler and Lassarre, 2008; Hakim et al., 1991; Lassarre and Thomas, 2005). 1.2. Road mortality in Europe and in Spain in 2000 The analysis of road mortality in 2000 shows that the basic indicators are very heterogeneous, varying considerably among EU Member States, and even more so among Spanish provinces. Of the 25 EU Member States, seven presented lower road mortality rates than the EU-25 mean. Malta, the United Kingdom, Sweden and the Netherlands stand out, with rates of 3.9, 6.1, 6.7 and 6.8 fatalities per 100 000 inhabitants, respectively. Analysing absolute values, countries with higher population and surface area (Germany, France, the United Kingdom, Italy, Spain and Poland) presented the highest numbers of fatalities. However, Page (2001) established the elasticity of the population of these countries at 0.96, meaning that a 10% increase in population produces a 9.6% increase in the number of fatalities, as long as the remaining variables remain constant. Eksler et al. (2008) estimated the elasticity of the population density as −0.32, that is to say a 10% increase in density means a 3.2% reduction in the number of fatalities. Of the 50 Spanish provinces, Soria had by far the highest road mortality rate, with 84.7 deaths per 100 000 inhabitants. This is six times higher than the Spanish mean (14.4), while the remaining provinces varied between 7.5 and 37.3 fatalities. The effect of population can be observed in provinces with a low population such as Soria, Cuenca, Huesca, Burgos, Teruel and Zamora, which have a low absolute number of fatalities and a relatively high mortality rate. The opposite proves true for the most populated provinces like Madrid, Barcelona, Valencia, Sevilla or Vizcaya. In the statistical analysis of the data, the mean and the standard deviation are the parameters that describe best and in the simplest way the variations of spatial data (Lassarre and Thomas, 2005). The differences between the means for the EU-15 and the EU-25 areas are not great, but they differ significantly in comparison to the average value for Spanish provinces. The standard deviation is greater when the number of regions (n) increases, and when the geographic scope is smaller, as in the Spanish provinces (Table 1). 1.3. Evolution of road mortality 2000–2006 in Europe and in Spain Although the overall evolution of road mortality in the period 2000–2006 is quite irregular, the number of fatalities in most EU Member States follows a downward trend (Table 2). By 2006 the EU-
1009
Table 1 Mean, standard deviation, minimum and maximum values of the mortality rate for NUTSa regions in 2000. Level
EU-25 states EU-15 states Spanish provinces
n
25 15 50
Population (hundred thousands)
Road fatalities
Avg.
Min.
Max.
Avg.
Min.
Max.
180.85 251.49 8.07
3.80 4.34 0.91
821.64 821.64 52.05
2101.44 2733.93 115.42
15 76 39
8079 8079 443
a This analysis covers 25 and 15 EU Member States (NUTS0) and 50 Spanish provinces (NUTS3), and is geographically based on the EUROSTAT’s NUTS 2003 regional classification (EUROSTAT, 2005).
25 Member States had achieved a reduction of 24.9% in the number of fatalities in comparison with 2000, with an average reduction per country of 22.3 ± 15.95%. The EU-15 Member States had been more successful, achieving a reduction of 28.0% and a mean of 28.1 ± 13.2%. While more than a third of the countries of the EU25 had made significant progress, it should be noted that in some countries road mortality actually increased over this period. The results for Spanish provinces over the period 2000–2006, shown in Table 3, present a more irregular evolution. Comparison of the road mortality data for 2000 and 2006 reveals heterogeneous results, ranging from a 68.8% decrease in Soria to a 13.8% increase in Huelva. The provinces of Huelva, Salamanca, Malaga, Almería and Cuenca increased or maintained their values of road mortality. The remaining provinces have made varying degrees of progress: in 9 provinces road mortality fell by less than 15%, in 15 provinces it fell by between 15% and 30%, in 14 provinces by 30–45%, and in 7 it fell by over 45%. 2. Desirable threshold and dynamic target values for the reduction of road mortality In the field of road safety, quantitative targets represent the results that policy makers wish to achieve for a certain geographic area (group of countries, country, region, etc.) in a certain period Table 2 Road mortality in the Member States of the EU-25 in the period 2000–2006. Index = 100 for year 2000. 2001
2002
2003
2004
2005
2006
EU-25 EU-15
2000 100 100
96.0 97.2
94.7 94.1
88.8 87.4
82.8 79.6
79.4 76.5
75.1 72.0
Lithuania Hungary Estonia Slovakia United Kingdom Ireland Italy Finland Slovenia Poland Greece Cyprus Sweden Austria Belgium Czech Republic Spain Germany Netherlands Malta Latvia Denmark France Portugal Luxembourg
100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
110.1 103.3 97.6 97.8 100.5 98.6 100.6 109.3 88.8 87.9 92.3 88.3 98.7 98.2 101.1 89.8 95.5 93.0 91.8 106.7 87.9 86.6 101.0 89.0 92.1
108.7 119.1 109.3 97.1 100.0 90.0 101.4 104.8 85.9 92.6 80.2 84.7 94.8 98.0 88.8 96.3 92.6 91.2 91.2 106.7 88.0 93.0 94.8 88.2 81.6
110.6 110.5 80.4 102.7 102.2 80.6 91.2 95.7 77.3 89.6 78.8 87.4 89.5 95.4 82.6 97.4 93.5 88.1 95.0 106.7 83.8 86.8 75.0 82.2 69.7
117.3 108.0 83.3 96.0 94.1 89.5 85.6 94.7 87.5 90.8 82.0 105.4 81.2 90.0 79.1 93.0 82.2 77.9 74.3 86.7 81.3 74.1 68.5 68.9 64.5
118.6 106.5 82.8 89.2 93.2 95.5 87.5 95.7 82.4 86.5 81.4 91.9 74.5 78.7 74.1 86.5 76.9 71.5 69.3 113.3 69.6 66.5 65.8 66.4 60.5
118.4 108.8 100.0 92.2 92.1 88.0 85.3 84.9 83.7 83.3 81.4 77.5 75.3 74.8 72.7 71.5 71.0 67.9 67.5 66.7 64.1 61.5 58.3 51.6 47.4
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Table 3 Road mortality in Spanish provinces over the period 2000–2006. Index = 100 for year 2000.
Huelva Salamanca Málaga Almería Cuenca Cádiz Huesca Albacete Lugo Cáceres Córdoba Murcia Ciudad Real Ávila Toledo Valladolid Guadalajara Ourense Jaén Segovia León Cantabria Granada Sevilla Tarragona
2000
2001
2002
2003
2004
2005
2006
100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
129.3 125.0 111.2 105.5 82.6 118.6 100.0 113.4 102.1 118.2 89.2 114.7 107.1 112.8 82.0 112.7 125.6 87.1 105.6 123.1 101.9 82.5 92.7 101.8 83.0
137.9 143.8 111.2 96.3 87.0 105.2 109.0 101.5 110.6 109.1 97.3 96.9 110.6 123.1 77.4 122.8 102.6 109.7 88.7 130.8 94.3 109.5 84.7 92.1 87.3
110.3 122.9 128.5 82.6 118.8 121.7 117.9 88.1 103.2 92.4 110.8 106.1 98.8 120.5 102.3 86.1 102.6 103.2 94.4 100.0 81.9 87.3 78.1 111.0 88.5
86.2 131.3 124.1 99.1 81.2 122.7 94.0 82.1 85.1 112.1 82.4 103.1 76.5 87.2 72.9 70.9 66.7 87.1 93.0 128.2 83.8 68.3 76.6 107.9 83.6
113.8 93.8 113.8 97.3 85.5 97.9 100.0 80.6 72.3 69.7 100.0 101.8 77.7 102.6 98.5 76.0 112.8 71.0 74.7 87.2 63.8 50.8 73.7 80.5 73.9
113.8 108.3 106.0 100.0 100.0 95.9 94.0 91.0 90.4 89.4 86.5 85.9 84.7 84.6 82.0 79.8 79.5 79.0 78.9 76.9 76.2 76.2 75.2 75.0 74.6
of time (European Road Safety Observatory, 2006). The establishment of threshold values and quantitative targets is a catalyst for the efforts of the different agents involved in road safety, aware that individually they would not have a direct bearing on the outcome of road safety programmes (Loo et al., 2005; Wong et al., 2006; Yannis et al., 2008). It has been found that the most ambitious quantitative targets generate a greater impact on the policy makers and on the implementation of safety programmes (Elvik, 1993). Countries that set out to improve road safety by implementing specific policies and defining clear targets were successful in reducing road mortality, e.g. the UK in 1983, Spain in 1991 and the Netherlands in 1972 (Lassarre, 2001). For Elvik (2008a,b), setting targets of road safety is an attractive idea which requires strong political commitment, although this was not the case in Norway. Given this scenario, the European Union set itself the target of halving the number of fatalities between 2000 and 2010. This goal was reflected in the White Paper “European transport policy for 2010: time to decide”. In this document are designated the national or local authorities as being responsible for achieving the proposed goals in each country. The Commission also reserved the right to propose regulatory measures in the report of 2005 if the number of fatalities were not reduced, mainly in the candidate countries (EC, 2001, 2003, 2006). The White Paper does not specify how this target should be achieved, so each Member State could consider that its aim is to halve its own number of road fatalities. We believe that our goal of reducing road mortality, which effectively shapes a country’s road safety policies, should differ for each geographic area (Lassarre and Thomas, 2005). The higher the mortality rate in a given area, the more ambitious that area target should be, considering that geographic areas with highly ambitious quantified road safety targets have been more successful than areas with less ambitious or nonquantified targets (Elvik, 1993, 2003; European Road Safety Observatory, 2006; Wong et al., 2006). The reduction, therefore, should not be linear of the same for all Member States, as it is neither fair nor logical to obligate countries with lower road mortality rates to reduce them by the same percentages. The states with the highest initial rates should make a greater effort to reduce them. As background for weighted overall policies, we highlight the EU energy policy, provided for in the “Directive of the European Parlia-
Castellón Illes Balears Alicante Zamora La Rioja Valencia Madrid ˜ A Coruna Teruel Girona Burgos Pontevedra Lleida Asturias Badajoz Las Palmas Barcelona Palencia Zaragoza S.C. Tenerife Guipúzcoa Álava Navarra Vizcaya Soria
2000
2001
2002
2003
2004
2005
2006
100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100
105.0 103.0 90.7 98.4 118.6 95.1 98.5 87.7 65.9 96.0 90.6 100.7 75.6 65.1 74.3 86.2 98.4 120.0 79.0 98.9 83.7 96.7 89.8 80.0 53.3
128.0 75.8 84.0 63.9 91.5 93.0 93.6 83.6 73.2 104.1 109.4 80.1 85.9 80.5 85.3 76.7 90.1 120.0 70.2 92.6 97.7 81.7 77.1 85.7 37.7
123.0 84.9 87.6 83.6 101.7 100.8 91.6 87.7 87.8 89.2 102.8 78.2 82.2 99.3 88.1 92.2 85.8 73.3 94.2 75.5 96.5 76.7 70.3 100.0 33.8
95.0 83.0 80.4 70.5 117.0 90.5 76.7 71.3 78.1 66.9 67.0 61.6 72.6 72.5 93.6 75.9 76.5 62.2 75.4 81.9 58.1 55.0 70.3 69.5 46.8
88.0 79.4 83.0 70.5 86.4 79.0 70.1 73.3 95.1 73.0 68.9 66.2 74.8 70.5 66.1 71.6 71.3 104.4 63.2 78.7 48.8 51.7 70.3 35.2 40.3
73.0 70.9 70.6 70.5 69.5 69.1 68.8 66.7 65.9 65.5 64.2 63.6 63.0 62.4 61.5 60.3 59.6 57.8 53.2 52.1 48.8 45.0 42.4 39.1 31.2
ment and of the Council on the promotion of the use of energy from renewable sources amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC” European Parliament and European Council (2009). The Directive sets an overall EU target of 20% target for the overall share of energy from renewable sources, and determines weighted or individualized targets for each Member State according to their GDP. Consequently, this study proposes a weighted modulation of the reduction coefficients based on the initial road mortality rate, taking 2000 as the reference year for its application. The desired value of road mortality would always be zero as the ultimate, albeit utopian goal (Tolón et al., in press). Objective progress targets towards this goal must be dynamic and redefined over time, varying according to the area in question. The targets for each area should be obtained as a function of that area’s distance from the desired value, in such a way that all areas converge towards it. In this way, the reduction coefficient, expressed in relative terms of improvement per unit, should vary between 1 (i.e. a hypothetical case in which all the population die in road accidents) and 0 (i.e. no deaths in road accidents). Since the EU aims for a reduction coefficient of 0.5 (mortality rate in 2010/mortality rate in 2000), on a more local scale the progress would have to be greater if the initial distance from the desired value (0) is greater. The present work applies this reasoning in two phases. Firstly the EU is considered as a geographic unit (contemplating two scenarios: EU-25 and EU-15), taking each Member State as a subunit. The sum of road fatalities of all the sub-units, once the corresponding modulated coefficients of reduction are applied, will result in half the number of fatalities from 2000 in the EU-25 and EU-15. Secondly, the results obtained for Spain (in the two scenarios: EU-25 and EU-15), are modulated using the distribution formula on a smaller scale in which the Spanish State is the geographic unit. In this case the sub-units are the 50 provinces, and modulated reduction coefficients are generated for each one. Subsequently, the road mortality rates generated using the proposed methodology are contrasted with the real data obtained in 2006. Finally, new targets are proposed for the reduction of road mortality in EU-25 countries by 2015.
A. Tolón-Becerra et al. / Accident Analysis and Prevention 41 (2009) 1008–1015
3. Methodology We propose a methodology to calculate weighed coefficients of reduction of absolute road mortality at various geographic levels using a weighted distribution, through an inverse logarithmic function of distribution based on the initial mortality rate (2000). For each geographic unit (i), the mortality rate is the number of fatalities (Fi ) in a year divided by the total population (Pi ) at the beginning of the year, expressed per 100 000 inhabitants: Mi =
Fi × 100 000 Pi
The initial rate of mortality was used because it expresses the severity of the social problem, and as it is the only homogenous statistic at international level (Page, 2001). The inverse logarithmic function was proposed because it adapts to the objectives of the study as regards obtaining modulated coefficients of reduction. Furthermore, it is coherent with the expressed principle that the reduction in road fatalities must be higher in those areas where the problem is greater. To achieve the EU target for 2010 of halving the number of fatalities from 2000, the following initial premise was considered: F2010 = c × F2000
(1)
where c is the total residual coefficient, complementary to the reduction coefficient, and F the absolute value of fatalities, i.e. the sum of the fatalities in each geographic sub-unit Fi : F=
i=n
Fi
(2)
i=1
Therefore, for the EU-25 and EU-15 geographical units: FEU(2010) = 0.5 × FEU(2000) and for each geographical sub-unit, in this case the EU Member States: Fi(2010) = ci × Fi(2000)
(3)
ci
where is the residual coefficient of each geographical sub-unit. This coefficient was calculated using an inverse logarithmic distribution function, depending on its initial fatality rate Mi : ci = f (Mi(2000) ) = a(ln Mi(2000) )−1
(4)
where a is the factor that modulates the weighting coefficient ci . To calculate the value of a, first replace Eq. (4) in Eq. (3): Fi(2010) = (a(ln Mi(2000) )−1 )Fi(2000)
n a × Fi(2000) i=1
(6)
ln Mi(2000)
therefore: a=
n
F(2010)
F /ln Mi(2000) i=1 i(2000)
=
functions gave inconsistent results as negative reduction for safer countries (justifying the elimination of these alternative distributions). The logarithmic distribution takes account of the differences in a smooth way. This methodology can also be applied to smaller geographic areas like Spain, where the total geographic unit is the Spanish state and the geographic sub-units are its provinces. In this case, the distribution formula is used, and the total residual coefficient c for the Spanish unit is the one obtained previously from the general targets of the EU for this state. In this way, new results are obtained as residual coefficients ci , for each province. We have applied this methodology on two levels of territorial aggregation, corresponding to NUTS0 (Member States of the EU-15 and EU-25) and NUTS3 (50 Spanish provinces) of the Nomenclature of Territorial Units for Statistics. In the analysis of Spanish provinces, the autonomous cities of Ceuta and Melilla were not included, because they are small units that tend to produce uncertain results due to the low number of fatalities and population (Deboosere and Gadeyne, 2002; Eksler et al., 2008). Temporal analysis has been carried out using data of the EU states and Spanish provinces from the period 2000 to 2006. In the selection of databases, the homogeneity of definitions was considered the main factor. In the processing of international data, not only in the field of road safety, this homogeneity is a prerequisite for meaningful comparisons, giving scientific validity to the study. At present, the number of fatalities is the only comparable data valid for all the countries, considering that the databases use the same international definitions, or have used a coefficient to correct the differences between definitions (Luoma and Sivak, 2007; Page, 2001). The road mortality data for EU countries are taken from the statistics published by CARE, and population and surface area data from EUROSTAT (EC, 1995). CARE (2006) defines “person killed at 30 days” as “death within 30 days of a road accident”, applying correction coefficients for countries that have a different definition in their national statistics. The coefficients were proposed by the EU Member States, and they are applied to the absolute values of “killed person”. In the case of Spain, the values of fatalities correspond to those published by the “Dirección General de Tráfico” (DGT), and the statistics of population and surface area come from the “Instituto Nacional de Estadística” (INE) (INE, 2008). DGT defines a “killed person” as “any person who died as a result of the accident, either in the act or within the following 30 days”, in line with the international definition.
4. Results
(5)
then, as F(2010) is the sum of the number of fatalities in each geographical sub-unit, Fi(2010) , we have: F(2010) =
1011
n
c × F2000
F /ln Mi(2000) i=1 i(2000)
We calculated a weighting factor a for both the EU-25 and EU15, from which we obtained the residual coefficients c for each Member State in both scenarios. The inverse logarithmic distribution function was selected, after testing empirically different distribution functions (as inverse quadratic or cubic ones) because it equilibrates the requirements of reduction in all the sub-units and a more ambitious reduction for those with worse actual behaviour. Alternative distribution
4.1. Results of the application of the methodology on the European scale By applying the proposed methodology, we obtained a set of target values for the reduction of fatalities for the EU-25 and EU15 Member States for 2010, as shown in Table 4. The higher the country’s initial mortality rates, the greater the reduction coefficients. Two clear examples are Latvia, with a reduction coefficient of 62.5% in the case of the EU-25 and Greece, with 59.1% for the EU-15. The total number of fatalities in absolute terms for each country is reduced unevenly, but in such a way that the total sum would achieve the EU’s overall target. In addition, the great difference in mortality rates between Member States is considerably reduced over time, changing from an initial range of 4.0–26.7, to one of 3.4–10.8. It is worthy of note that the results obtained for each particular country differ depending on the scenario considered (EU-25 or EU15). For instance, in the case of Spain the reduction coefficient is higher for the EU-15 than for the EU-25 (55.2% vs. 53.9%). However,
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Table 4 Weighted rates of reduction for EU-25 and EU-15 Member States. c = 0.5
EU-25
EU-15
Regions
Fatalities 2000
Mortality rate 2000
c
Reduction (%)
Fatalities 2010
Mortality rate 2010
Latvia Greece Portugal Lithuania Luxembourg Poland Cyprus Slovenia Estonia Czech Republic Spain Belgium France Austria Hungary Italy Slovakia Ireland Denmark Germany Finland Netherlands Sweden United Kingdom Malta
635 2037 1877 641 76 6294 111 313 204 1486 5777 1470 8079 976 1200 6649 628 418 498 7503 396 1082 591 3580 15
26.7 18.7 18.4 18.3 17.5 16.3 16.1 15.8 14.9 14.5 14.4 14.4 13.4 12.2 11.7 11.7 11.6 11.1 9.3 9.1 7.7 6.8 6.7 6.1 4.0
0.37 0.42 0.42 0.42 0.43 0.44 0.44 0.45 0.46 0.46 0.46 0.46 0.47 0.49 0.50 0.50 0.50 0.51 0.55 0.56 0.60 0.64 0.65 0.68 0.90
62.5 58.0 57.8 57.6 57.0 55.9 55.7 55.4 54.4 53.9 53.9 53.8 52.5 50.8 50.0 49.9 49.9 48.8 44.9 44.4 39.6 35.9 35.2 31.9 10.3
238 856 793 272 33 2776 49 140 93 685 2664 679 3837 480 600 3329 315 214 274 4175 239 694 383 2439 13
10.8 7.6 7.4 8.2 6.5 7.3 6.2 7.0 7.2 6.8 6.0 6.4 6.2 5.8 6.0 5.7 5.9 5.0 5.0 5.0 4.5 4.2 4.2 4.0 3.4
the average values of reduction, for each of the two hypotheses of aggregation, present only slight differences and both are around 50% (48.8% for the EU-25 and 49.1% for the EU-15).
c
Reduction (%)
0.41 0.41
59.1 58.9
833 771
7.4 7.2
0.42
58.2
32
6.4
0.45 0.45 0.46 0.48
55.2 55.1 53.8 52.2
2590 660 3731 467
5.8 6.2 6.1 5.6
0.49
51.3
3237
5.5
0.50 0.54 0.54 0.59 0.62 0.63 0.66
50.2 46.5 45.9 41.2 37.7 36.9 33.8
208 267 4059 233 674 373 2371
4.8 4.9 4.9 4.4 4.0 4.1 3.9
Fatalities 2010
Mortality rate 2010
the case of the EU-25. These figures imply reduction coefficients of 53.9% or 55.2%, respectively, fixing the Spanish residual coefficient as c = 0.448 for the EU-15 scenario, and as 0.461 for the EU-25 one. Using the proposed methodology, the target values of reduction for each province were then computed. Also the new mortality rates were calculated, using the estimated population in 2010 according to the INE (Table 5). The number of fatalities, in absolute terms, is reduced unevenly in each province, but in such a way that the total number is reduced by 53.9% or 55.2%, according to the scenario considered. Once again it is clear that the reduction coefficients generated are higher when the initial mortality rates are higher, and that the great differences in mortality rates between provinces are reduced considerably. Indeed, in this case the results are even clearer, as the
4.2. Results of the application of the methodology on the local scale (Spanish provinces) Maintaining the premise that a linear reduction of road fatality targets is inadequate, the proposed formula was then applied to Spain as an example of a smaller territorial unit (NUTS3). For this purpose the values obtained for Spain in both previously considered scenarios were used as general national targets. Taking into account previous results, Spain must not exceed 2590 fatalities in 2010, if we consider only the countries of the EU-15, or 2664 in Table 5 Weighted rates of reduction for Spanish provinces.
1 2 3 4 5 6 7 8 9 10 ... 41 42 43 44 45 46 47 48 49 50
Fatalities 2000
Mortality rate 2000
Soria Lleida Cuenca Huesca Burgos Teruel Zamora Tarragona Segovia Girona
77 135 69 67 106 41 61 165 39 148
S.C. Tenerife Valencia Jaén Córdoba Sevilla Barcelona Vizcaya Málaga Cádiz Madrid
94 243 71 74 164 443 105 116 97 391
c = 0.461 c
Reduction (%)
84.7 37.3 34.3 32.6 30.5 30.0 30.0 27.6 26.6 26.2
0.28 0.34 0.35 0.36 0.36 0.36 0.36 0.37 0.38 0.38
72.1 65.8 65.0 64.5 63.8 63.6 63.6 62.7 62.3 62.1
11.5 11.0 11.0 9.6 9.5 9.4 9.3 9.1 8.6 7.5
0.51 0.52 0.52 0.55 0.55 0.55 0.56 0.56 0.57 0.61
49.3 48.4 48.4 45.3 44.9 44.6 44.4 43.8 42.5 38.6
EU-25 scenario
c = 0.448
Fatalities 2010
Mortality rate 2010
c
Reduction (%)
EU-15 scenario
21 46 24 24 38 15 22 62 15 56
23.3 11.2 11.6 10.9 10.8 10.5 11.7 7.8 9.4 7.7
0.27 0.33 0.34 0.35 0.35 0.35 0.35 0.36 0.37 0.37
72.9 66.7 65.9 65.5 64.8 64.6 64.6 63.7 63.3 63.1
21 45 23 23 37 15 22 60 14 55
22.7 10.9 11.3 10.6 10.5 10.2 11.3 7.6 9.2 7.5
48 125 37 40 90 245 58 65 56 240
4.8 5.0 5.6 5.1 4.9 4.6 5.2 4.3 4.6 3.8
0.49 0.50 0.50 0.53 0.54 0.54 0.54 0.55 0.56 0.60
50.7 49.9 49.8 46.8 46.4 46.1 45.9 45.4 44.1 40.3
46 122 36 39 88 239 57 63 54 233
4.7 4.9 5.4 5.0 4.8 4.5 5.1 4.2 4.5 3.7
Fatalities 2010
Mortality rate 2010
A. Tolón-Becerra et al. / Accident Analysis and Prevention 41 (2009) 1008–1015
1013
Table 6 Percentages of reduction in the number of fatalities in the period 2000–2006 (Index = 0 for year 2000), and percentages of reduction for 2010.
Fig. 1. Percentage of real reduction of the number of fatalities in road accidents, in the period 2000–2006 vs. modulated percentage reduction for 2006 and 2010. Index = 100 for year 2000, in the order of greatest to smallest real reduction.
range of mortality rates is greatly reduced, 7.5–84.7 vs. 3.8–23.3 in the EU-25 scenario. As regards the EU-15 scenario, the new range is slightly smaller: 3.7–22.7.
Huelva Salamanca Málaga Almería Cuenca Cádiz Huesca Albacete Lugo Cáceres Córdoba Murcia Ciudad Real Ávila Toledo Valladolid Guadalajara Ourense Jaén Segovia León Cantabria Granada Sevilla Tarragona a b
4.3. Comparison of the real evolution of road mortality in the period 2000–2006 with the proposed weighted values We compared the percentages of reduction experienced by EU Member States during the period 2000–2006 with those expected according to the modulation carried out for 2006 (Fig. 1). This modulation was calculated by making a proportional linear distribution of the percentage calculated for 2010. It can be seen that overall the EU Member States have reduced the number of fatalities, almost reaching the target proposed in this study (30%), with better values for the EU-15 (28.03%) than for the EU-25 (24.95%). However, when the comparisons are made for each country, there are some significant differences. Malta is the country with the best results, with a 33.3% reduction in the number of fatalities in 2006, quite superior to the 6.2% reduction expected for the year 2010, according to the proposed model. The number of fatalities in Lithuania, on the contrary, increased over the same period by 18.4%. According to the proposed model this country should have reduced the number of fatalities by 34.6%. Only six countries show sufficient progress to achieve the proposed reduction. The linear extrapolations of data series from the period 2000–2006 to the year 2010 has resulted in positive projections for most of the countries. The reduction percentages are even higher than those established in this study, in line with the 50% reduction previously accorded by all countries. Lithuania, Hungary, Estonia and Slovakia present the worst results, and their projections do not invite optimism as regards achieving the EU goal. In Spain, comparing the results obtained in 2006 with the proposed reduction values for 2010 (see Table 6), 48% of the Spanish provinces present a reduction of between 30 and 65 percentage points of difference. This implies that a lot of work remains to be done in order to reduce the number of fatalities in these provinces. Vizcaya is the only one that reduced its number of fatalities to 2006 as proposed in this study (by 61.0% as opposed to the 44.4% proposed), and as such it is an example for other provinces to follow. Other provinces that have made significant progress are Guipúzcoa, Tenerife, Navarra, Soria, Barcelona, Álava and Madrid, with a difference of 10 points between both values.
2006
2010a
2010b
−13.8 −8.3 −6.0 0.0 0.0 4.1 6.0 9.0 9.6 10.6 13.5 14.1 15.3 15.4 18.1 20.3 20.5 21.0 21.1 23.1 23.8 23.8 24.8 25.0 25.5
−2.7 −5.4 −22.6 6.2 11.3 0.2 6.1 34.2 33.6 32.7 13.3 14.3 41.1 21.3 18.5 53.9 32.2 38.4 39.5 29.3 53.5 62.0 47.1 30.0 40.1
51.2 52.7 43.8 59.4 65.0 42.5 64.5 57.5 61.9 55.5 45.3 53.3 57.0 60.9 61.6 55.3 60.8 57.1 48.4 62.3 59.3 49.9 56.2 44.9 62.7
2006 Castellón Illes Balears Alicante Zamora La Rioja Valencia Madrid ˜ A Coruna Teruel Girona Burgos Pontevedra Lleida Asturias Badajoz Las Palmas Barcelona Palencia Zaragoza S.C. Tenerife Guipúzcoa Álava Navarra Vizcaya Soria
27.0 29.1 29.4 29.5 30.5 30.9 31.2 33.3 34.2 34.5 35.9 36.4 37.0 37.6 38.5 39.7 40.4 42.2 46.8 47.9 51.2 55.0 57.6 61.0 68.8
2010a 35.3 46.5 41.6 54.8 34.8 42.1 56.2 53.8 28.9 61.7 62.2 70.6 52.3 48.9 49.7 56.9 64.1 62.8 65.2 65.8 89.5 98.0 80.3 99.4 106.9
2010b 59.4 58.3 52.3 63.6 60.1 48.4 38.6 56.8 63.6 62.1 63.8 55.9 65.8 52.9 55.8 51.6 44.6 61.6 58.8 49.3 51.2 59.3 59.8 44.4 72.1
Extrapolate data. Weighted fatalities, EU-25 scenario.
4.4. Proposal of reduction of the mortality rate in the EU for 2015 By 2010, if we extrapolate the values of 2006, overall the EU-25 will achieve a 36.2% reduction. With this result the current EU target would not be reached. We therefore considered that a new commitment should be formulated and agreed for 2015. By this time, those countries with worse rates, especially those incorporated into the EU in 2004, would be able to redesign and/or improve their road safety policies and programmes.
Table 7 Weighted rates of reduction proposed for EU-25. c = 0.4
2006
Regions
Fatalities
Mortality rate
Reduction (%)
2015 Fatalities
Mortality rate
Lithuania Latvia Estonia Greece Poland Slovenia Hungary Cyprus Slovakia Czech Republic Belgium Italy Spain Portugal Austria Ireland Luxembourg France Finland Germany Denmark United Kingdom Sweden Netherlands Malta
759 407 204 1657 5243 262 1303 86 579 1063 1069 5669 4104 969 730 365 36 4709 336 5091 306 3298 445 730 11
22.3 17.7 15.2 14.9 13.7 13.1 12.9 11.2 10.7 10.4 10.2 9.6 9.4 9.2 8.8 8.7 7.7 7.5 6.4 6.2 5.6 5.5 4.9 4.5 2.7
72.4 70.2 68.5 68.2 67.3 66.6 66.5 64.5 63.9 63.3 63.0 62.2 61.7 61.3 60.6 60.3 57.9 57.4 53.8 52.9 50.4 49.5 46.2 42.7 14.2
210 121 64 526 1716 87 437 31 209 390 395 2145 1572 375 287 145 15 2008 155 2398 152 1666 240 418 9
6.4 5.5 4.9 4.6 4.6 4.4 4.5 3.8 3.9 3.9 3.7 3.7 3.5 3.5 3.4 3.2 3.0 3.2 2.9 2.9 2.8 2.7 2.5 2.5 2.4
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Fig. 2. Real evolution of mortality rates in the period 2000–2006 and the modulated proposal for the period 2006–2015 for the EU-25 Member States and the Spanish provinces.
Considering the dynamism that should prevail in the formulation of quantitative targets, a reduction of 60% in the number of fatalities is proposed for the period 2006–2015, equivalent to an approximate reduction of 70% with respect to 2000. We have applied the formula for modulation of the reduction coefficients to the Member States of the EU-25 (see Table 7), and to the Spanish provinces. The new target rates of reduction for 2015 offer different values for each Member State but maintain the target of 70% reduction for the EU as a whole. Once again the states with higher initial mortality rates are assigned higher coefficients of reduction in the number of fatalities, while in those with lower initial mortality rates the progresses would be smaller. The initial dispersion of mortality rates between states would be reduced even more over time, changing from a range of 2.7–22.3 to one of 2.4–6.4. The application of the methodology to Spain and its provinces for the same period (2006–2015) means that the range of road mortality in the different provinces is greatly reduced, changing from the range of 3.6–33.1 to 2.3–8.0 (Fig. 2). Fig. 2 shows the real evolution of mortality rates during the period 2000–2006 in the EU-25 Member States and the provinces of Spain, and the weighted values proposed for the period 2006–2015. It can be seen that both the mean and the range of mortality rates is reduced with time, particularly due to the greater reduction in those areas with higher initial mortality rates.
5. Conclusion The evolution of road mortality has been uneven and with very heterogeneous values of reduction, both in EU Member States and in the Spanish provinces. The countries that have made most progress are those that have implemented road safety policies and programs in the past. These countries differ considerably from those countries incorporated into the EU in 2004, whose overall statistics show the need for greater effort and resources to achieve the EU target as stated in the Transport White Paper. To achieve the desirable values, the objective target values of progress should be implemented in a pragmatic way, in accordance with the context and characteristics of each geographic area. The heterogeneity of the statistics underlines the need for “weighted” decentralized decisions to be taken at different territorial levels with a view to achieving a common aim. Under this
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