Figure 3 - uploaded by Antoni Rangachev
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Geographic distribution of excess mortality-based ASYR and PYLL values for European countries in 2020. Shown are the total (per 100K people) values. (A) ASYR values for the whole population; (B) ASYR values for females; (C) ASYR values for males; (D) PYLL values for the whole population; (E) PYLL values for females; (F) PYLL values for males.
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Background: The COVID-19 pandemic followed a unique trajectory in Eastern Europe compared to other heavily affected regions, with most countries there only experiencing a major surge of cases and deaths towards the end of 2020 after a relatively uneventful first half of the year. However, the consequences of that surge have not received as much att...
Contexts in source publication
Context 1
... next examined the impact of the pandemic in terms of years of life lost using the PYLL and ASYR metrics based on excess mortality (Figure 3). Both metrics paint a similar picture, which is also consistent with the raw excess mortality measures. ...
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... only three countries with an average PYLL greater than 13 are Bulgaria, Poland, and Romania, compared to values as low as in the 10 to 11 years range for countries such as Denmark, Switzerland and Sweden (Supplementary Table 17). Despite males exhibiting higher mortality due to COVID-19, the average PYLL based on excess deaths in Bulgaria is higher for females (it is also higher for females in several other European countries; Supplementary Figure 3). ...
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... rough approximation gives an upper bound of how large the ASYRs can go. It leads to 5%−14% and 14%−22% increase in the ASYRs for the (0−89) population of Eastern and Western European countries, respectively, but it does not yield a decrease between the inequalities of the countries from the two groups or any significant change in their ranks (see Supplementary Fig. 3 and Supplementary Table 5). ...
Context 4
... next examined the impact of the pandemic in terms of years of life lost using the PYLL and ASYR metrics based on excess mortality (Figure 3). Both metrics paint a similar picture, which is also consistent with the raw excess mortality measures. ...
Context 5
... only three countries with an average PYLL greater than 13 are Bulgaria, Poland, and Romania, compared to values as low as in the 10 to 11 years range for countries such as Denmark, Switzerland and Sweden (Supplementary Table 17). Despite males exhibiting higher mortality due to COVID-19, the average PYLL based on excess deaths in Bulgaria is higher for females (it is also higher for females in several other European countries; Supplementary Figure 3). ...
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The COVID-19 pandemic followed a unique trajectory in Eastern Europe compared to other heavily affected regions, with most countries there only experiencing a major surge of cases and deaths towards the end of 2020 after a relatively uneventful first half of the year. However, the consequences of that surge have not received as much attention as th...
Citations
... An analysis of COVID-19 impact in Bulgaria confirms that excess mortality characterises more peripheral and remote areas than highly populated areas such as Plovdiv, Varna, Burgas and the city of Sofia. In fact, after a first phase where better connected territories were affected more, the spread of coronavirus to peripheral areas put these latter areas under a much greater pressure because of fewer resources 'to test, track and treat COVID-19 patients' (Rangachev et al., 2020). ...
... In addition, the analysis found that excess mortality in 2020 characterises working-age people and females in particular. This is potentially explained by the fact that several recorded outbreaks occurred at garment, textile and shoe workplaces, i.e. in plants with a mainly female workforce (Rangachev et al., 2020). In Blagoevgrad and Smolyan provinces, where excess mortality was 25% and 27%, respectively, these types of factories represent an important component of the local economy. ...
... Among the drivers of excess mortality, the analysis of Rangachev et al. (2020) mentions the limited testing, the delayed adoption of control and restriction measures, the high incidence of comorbidities, in particular related to cardiovascular diseases, and the low availability and/or accessibility of health facilities in remote areas. The data in the influencing factors' matrix ( Figure 8) 21 confirm the high incidence of comorbidities in the two Bulgarian provinces but also highlight very high shares of people at risk of poverty and social exclusion, especially in Yuzhen tsentralen (38% versus an EU average of 21%) where the fatality rate is as high as 5.3%. ...
The focus of this research is on highlighting differences among regions in terms of health impact suffered from the COVID-19 pandemic and capability of regional health systems to learn and react. Differences are discussed in terms of exposure, resilience and progress in the rollout of COVID-19 vaccinations. Special emphasis is given to identify a potential rural/urban divide. The study concludes highlighting recommendations for enhancing the resilience of regional health systems in line with the creation of a European Health Union. Several working hypotheses are made in this research which was challenged by the need to work on almost real-time data at the regional level.
The COVID-19 pandemic has resulted in more than 282 million cases and almost 5.5 million deaths (WHO Coronavirus Disease (COVID-19) Dashboard, 2022). Its impact, however, has not been uniform. This analysis examines differences in COVID-19 cases and mortality rates amongst different welfare states within the first three waves of the pandemic using repeated measures Multivariate Analysis of Covariance (MANCOVA). Liberal states fared much better on the number of COVID-19 cases, deaths, and excess deaths than the Conservative/Corporatist welfare democracies. Social Democratic countries, in turn, did not fare any better than their Conservative/Corporatist counterparts once potential confounding economic and political variables were accounted for: countries’ economic status, healthcare spending, availability of medical personnel, hospital beds, pandemic-related income support and debt relief, electoral events, and left-power mobilization. The pandemic-related welfare responses after the first wave were similar across all three types of western democracies, but the differences in pandemic outcomes remained. The somewhat better outlook of the Liberal states could be attributed to the so-called social democratization of the Anglo-American democracies, but also to the fact that neoliberalism could have flattened the previous differences between the welfare states typologies and could have brought states closer to each other, ideologically speaking, in terms of welfare provision.
