key: cord-0691078-30hhk94v
authors: Hoebel, Jens; Michalski, Niels; Diercke, Michaela; Hamouda, Osamah; Wahrendorf, Morten; Dragano, Nico; Nowossadeck, Enno
title: Emerging socioeconomic disparities in COVID-19–related deaths during the second pandemic wave in Germany
date: 2021-10-29
journal: Int J Infect Dis
DOI: 10.1016/j.ijid.2021.10.037
sha: 1611d6b1b731bef0469915e56b72d3cf5b50825c
doc_id: 691078
cord_uid: 30hhk94v

In the course of the second pandemic wave in late 2020, new infections with SARS-CoV-2 shifted from the most affluent to the most deprived regions of Germany. We investigated how this trend in infections played out for COVID-19 deaths by examining area-level socioeconomic disparities in COVID-19–related mortality during the second pandemic wave in Germany. The analysis was based on nationwide data on notified deaths, which were linked with an area-based index of socioeconomic deprivation. In the fall and winter of 2020/2021, COVID-19–related mortality increased faster among residents in Germany's more deprived districts. From late 2020 onwards, the mortality risk of men and women in the most deprived districts was 1.52 (95% CI 1.27−1.82) and 1.44 (95% CI 1.19−1.73) times higher than among those in the most affluent districts, net of age, urbanization, and population density. To promote health equity in the pandemic and beyond, deprived populations should receive increased attention in pandemic planning, infection control, and disease prevention.

infections in Germany has differed from that reported from other high-income countries, 23 revealing lower infection rates in socioeconomically deprived areas of Germany in the early 24 phase of the first wave (Wachtler et al., 2020a (Wachtler et al., , 2020b The notification data were linked with the German Index of Socioeconomic Deprivation 41 (GISD), which is a composite index of area-based socioeconomic indicators in the domains of 42 education, employment, and income (Kroll et al., 2017) . The use of an area-based measure 43 was necessary because the notification data do not contain individual socioeconomic data. 44 level available in the notification data at the time of analysis. 46 Mortality rates were stratified by quintiles of socioeconomic deprivation and age-47 standardized to the 2013 European standard population using direct standardization 48 (Eurostat, 2013) . In the multivariable analysis, adjusted mortality rate ratios were estimated 49 by deprivation quintiles using multilevel Poisson regression models with 5-year age groups 50 within districts as first-level units and districts as second-level units. Table S1 ). The regression 57 analysis was conducted separately for an early stage (calendar weeks 40/2020−51/2020) and 58 a later stage (calendar weeks 52/2020−9/2021) of the pandemic's second wave in Germany. 59

The early stage was marked by an exponentially increasing incidence of infections peaking in 60 mid-December 2020. The later stage was the wave's post-peak period with a declining 61 incidence of new infections (Robert Koch Institute, 2021). 62

From calendar week 52/2020 onwards, the mortality risk of men and women in the most 71 deprived districts was 1.52 and 1.44 times higher, respectively, than among those living in 72 the most affluent districts, net of age, urbanization, and population density ( Table 1) to higher burden of pre-existing health conditions), increased susceptibility (due to 84 weakened immune function; e.g., as a result of chronic stress from long-term exposure to 85 adverse circumstances), increased exposure (e.g., due to working conditions), and increased 86 transmission (e.g., due to crowded housing) in disadvantaged socioeconomic groups 87 (Bambra et al., 2021) . Most of these explanations, though, appear rather consistent across 88 the entire period of the pandemic. Therefore, they alone may not explain why the 89 socioeconomic patterning of COVID-19 in Germany changed in the course of the pandemic 90 from the first to second wave. In this context, it is worth considering factors that changed 91 differently across socioeconomic groups over the pandemic period. 92

Specifically, the first COVID-19 cases in Germany were related to business travel from China 93 and skiing trips to European ski resorts, activities more common among the better-off, which 94 may explain higher COVID-19 rates in Germany's more affluent areas in the early first wave 95 (Wachtler et al., 2020b ). An important factor that may have changed differently across 96 socioeconomic groups as the pandemic progressed was mobility. Whereas privileged groups, 97 such as white-collar and managerial workers, have been able to reduce their mobility sharply 98 by working from home during the lockdowns, this was not necessarily the case for more 99 disadvantaged groups. For instance, essential workers in the service, care, and production 100 sectors were possibly more likely of having to go to work during the lockdowns, including the 101 necessity to use public transport to do so (Bambra et al., 2021) . Lockdowns may therefore 102 have been less effective in more deprived areas and disparities in mobility reductions may 103 help explain why COVID-19 rates dropped early in affluent areas, but increased in deprived 104 areas at later stages of the pandemic. Other explanations could be related to healthcare, 105 including comparatively limited access to medical care or less frequent opportunities for 106 testing in deprived areas. However, as having health insurance is compulsory in Germany, 107 access to hospitals and intensive care units is likely to be largely universal across the 108

This study is not free of limitations. Due to the ecological study design, causation cannot be 110 inferred from our findings, and the possibility of ecological fallacy cannot be ruled out. The authors declare that they have no known competing financial interests or personal 143 relationships that could have appeared to influence the work reported in this paper. 144 

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Special thanks are due to Marvin Reis for his contribution to producing the map illustrations 146 in the supplementary material. 147