Madrid tops European ranking for highest excess mortality in 2020

BarcelonaIn the first months of the pandemic, coronavirus raged in the Community of Madrid, which concentrated the largest proportion of deaths in Europe, with 44% more deaths than in previous years. The excess mortality in the region directed Isabel Díaz Ayuso is the highest in the EU alongside Lombardy (39%), the northernmost region of Italy and the first to record coronavirus cases in the EU. This is the conclusion of the annual regional and local barometer published by the European Committee of the Regions in October, which this year is marked by the impact of the pandemic and includes a ranking of the ten areas with the highest excess mortality rates. This indicator has been calculated by comparing the number of deaths recorded in 2020 with the average number of deaths from 2016 to 2019.

In the case of Madrid, the peak in deaths occurred mainly between the months of March and April (although the trickle of victims continued throughout the year) and the EU calculates that the average number of weekly victims in Madrid in that period was already 2.9% higher than that recorded in previous years. In addition, the transmission spread to nearby regions and, in fact, the EU report concludes that central Spain was one of the two deadliest hotspots. Specifically, Castilla-La Mancha, which ranks third in the ranking with 34% more deaths than expected, and Castilla y León, in sixth position with 29% more victims, were dragged down by the close connection with Madrid (they could be considered conurbations of the capital). Catalonia also appears in this ranking, in eighth position, with 27% excess deaths.

In the EU as a whole, average excess mortality in 2020 increased for the first time in April. A 25% rise coincided with the first wave, the most aggressive of all. With the exception of the French island of Mayotte (the fifth most affected area with 32% excess mortality) and the Subcarpathian Voivodeship in Poland (ninth with 26% more), the highest mortality occurred in Spanish and Italian regions.

The committee notes that Italy has the greatest variability between regions. For example, the province of Bergamo in Lombardy had a 63% increase in deaths in 2020 compared to the province of Catanzaro in Calabria, which only saw a 2% increase. In the ranking, the city of Trento is the fourth most affected, with 32% more victims, the Aosta Valley (28%) is the seventh and Piedmont the tenth (25%). "The differences are also evident for Spain in comparison with the Portuguese regions to the west and the French regions to the east," the report notes. Apart from pockets in the central regions of Spain and northern Italy, there were also overmortality peaks in the southeastern part of Belgium and in southern Poland and Bulgaria.

The second wave moved to the East

The EU continues the report by stating that there were up to three more peaks in deaths before the end of the year in Europe as a whole and that these peaks affected states that had not previously suffered major loss of life. In October, 18% more deaths than expected were recorded in Europe, in November 41% more (Spain was experiencing the third wave, one of the hardest in terms of deaths) and in December 30% more. From October 19 (the second wave) the great peak of deaths was concentrated mainly in the Baltic and Eastern European countries, specifically in Bulgaria, Poland and Romania.

Among the reasons for the differences in excess mortality between European regions, the EU highlights five. Firstly, the capacity of the health system to cope with the increase in cases and inequality in access to well-equipped facilities and, secondly, the basic health status of the population in each region (if they have many pathologies, especially affecting the respiratory system or not). In addition, it stresses that the timing, speed and intensity of the government measures that were put in place to curb the spread and mitigate the impact of the virus, along with awareness, vigilance and compliance with restrictions by the population, played a key role.

The EU also points to differences in population pyramids, i.e. the proportion of elderly and care home users, as well as the proportion of vulnerable people and minority groups, as a cause. The fifth reason points to the diversity of socio-economic factors, such as the average number of people living alone or with extended families, or the proportion of the population that was able to work from home in the first months of the pandemic.