Area Deprivation and COVID-19 Incidence and Mortality in Bavaria, Germany: A Bayesian Geographical Analysis

Abstract

BackgroundArea deprivation has been shown to be associated with various adverse health outcomes including communicable as well as non-communicable diseases. Our objective was to assess potential associations between area deprivation and COVID-19 standardized incidence and mortality ratios in Bavaria over a period of nearly 2 years. Bavaria is the federal state with the highest infection dynamics in Germany and demographically comparable to several other European countries.MethodsIn this retrospective, observational ecological study, we estimated the strength of associations between area deprivation and standardized COVID-19 incidence and mortality ratios (SIR and SMR) in Bavaria, Germany. We used official SARS-CoV-2 reporting data aggregated in monthly periods between March 1, 2020 and December 31, 2021. Area deprivation was assessed using the quintiles of the 2015 version of the Bavarian Index of Multiple Deprivation (BIMD 2015) at district level, analyzing the overall index as well as its single domains.ResultsDeprived districts showed higher SIR and SMR than less deprived districts. Aggregated over the whole period, the SIR increased by 1.04 (95% confidence interval (95% CI): 1.01 to 1.07, p = 0.002), and the SMR by 1.11 (95% CI: 1.07 to 1.16, p < 0.001) per BIMD quintile. This represents a maximum difference of 41% between districts in the most and least deprived quintiles in the SIR and 110% in the SMR. Looking at individual months revealed clear linear association between the BIMD quintiles and the SIR and SMR in the first, second and last quarter of 2021. In the summers of 2020 and 2021, infection activity was low.ConclusionsIn more deprived areas in Bavaria, Germany, higher incidence and mortality ratios were observed during the COVID-19 pandemic with particularly strong associations during infection waves 3 and 4 in 2020/2021. Only high infection levels reveal the effect of risk factors and socioeconomic inequalities. There may be confounding between the highly deprived areas and border regions in the north and east of Bavaria, making the relationship between area deprivation and infection burden more complex. Vaccination appeared to balance incidence and mortality rates between the most and least deprived districts. Vaccination makes an important contribution to health equality.

Socioeconomic Inequalities in SARS-CoV-2 Infection and COVID-19 Health Outcomes in Urban Italy During the COVID-19 Vaccine Rollout, January–November 2021

“…Conversely, findings from a study in Bavaria, Germany showed that increasing vaccination coverage appeared to balance incidence and mortality rates between the most and least deprived districts [ 19 ]. Two of several factors which could explain these temporal pattern differences are inter-study heterogeneity (e.g.…”

Influencia del índice de privación social en resultados durante la pandemia de COVID-19

“…Aunque la COVID-19 ha afectado a países de ingresos dispares, existe evidencia para demostrar que los determinantes sociales y económicos tienen un impacto en la incidencia, la gravedad y la mortalidad asociada 21 , 22 , 23 , 24 , 25 , 26 , 27 . La mayoría de los estudios sobre la COVID-19 y los diferentes niveles de privación se han centrado en averiguar si había diferencias en las tasas de mortalidad y de hospitalización según los niveles de privación 21 , 22 , 23 , 25 , 28 , 29 , 30 ; otros se han centrado en su relación con la tasa de infección 21 , 23 , 24 , 25 , 27 . En todos ellos se ha encontrado que los colectivos más desfavorecidos, con mayor nivel de privación, han tenido tasas más altas de infección, de mortalidad y de ingreso en comparación con los colectivos con unas tasas de privación más bajas.…”

“…En algunos casos, los estudios también han encontrado discrepancias entre diferentes tiempos de la pandemia, con resultados dispares por estudios y olas 21 , 25 . En nuestro caso, al igual que en el estudio de Manz et al 25 , las mayores desigualdades se observaron durante el primer y el tercer periodos.…”

“…En algunos casos, los estudios también han encontrado discrepancias entre diferentes tiempos de la pandemia, con resultados dispares por estudios y olas 21 , 25 . En nuestro caso, al igual que en el estudio de Manz et al 25 , las mayores desigualdades se observaron durante el primer y el tercer periodos. En el primero, coincidiendo con la primera ola de la pandemia, esto puede ser más fácilmente comprensible debido a la emergencia que la pandemia ocasionó en esos momentos y la sobrecarga de los servicios hospitalarios.…”

Health promotion networks in two districts in Bavaria, Germany: an exploratory case study mapping networks with respect to thematic agenda and location

“…The BIMD is a measure of relative deprivation which combines indicators in certain domains of deprivation to generate a comprehensive deprivation index ( 19 , 20 ). The index, last updated in 2015, consists of the following seven domains: income (weight: 25%), employment (25%), education (15%), district revenue (15%), social capital (10%), environment (5%), and security (5%) ( 19 , 21 ). High BIMD values indicate high deprivation (meaning low income, high unemployment, etc.)…”