Socioeconomic inequalities and COVID-19 – A review of the current international literature

Abstract

Social epidemiological research describes correlations between socioeconomic status and the population’s risk to become diseased or die. Little research of such correlations for SARS-CoV-2 and COVID-19 has so far been conducted. This scoping review provides an overview of the international research literature. Out of the 138 publications found, 46 were later included in the analysis. For the US and the UK, the reported findings indicate the presence of socioeconomic inequalities in infection risks as well as the severity of the course of the disease, with socioeconomically less privileged populations being hit harder. There are far fewer findings for Germany to date, as is the case for most other European countries. However, the scant evidence available so far already indicates that social inequalities are a factor in COVID-19. Most of these analyses have been ecological studies with only few studies considering socioeconomic inequalities at the individual level. Such studies at the individual level are particularly desirable as they could help to increase our understanding of the underlying pathways that lead to the development of inequalities in infection risks and the severity of disease and thereby could provide a basis to counteract the further exacerbation of health inequalities.

COVID-19: Regional Differences in Austria

“…Furthermore, sociodemographic and socioeconomic aspects might be of importance regarding case severity, such as general health status, that is demographically linked to age group and sex, but also socioeconomic factors such as income and educational level might be of importance: A US study showed that socioeconomic factors, especially educational level, play an important role in disease prevalence and mortality [36], and that low income was associated with more cases and fatalities [36]. Similar results can be found internationally: A Japanese study showed highest incidence and mortality in the group of the lowest income [37], a Swedish study showed that dying from COVID-19 mainly affects elderly, residents from nursing homes, and persons from less advantaged social groups [38], and an international review concluded that socioeconomically disadvantaged groups are hit harder by the pandemic [39]. Though sociodemographic or socioeconomic influences all point in the same direction, there still might be geographical differences regarding their effect: In a comparison of European countries, Austria ranked among the countries where sociodemographic influences on both case number and death number were highest, whereas the UK and Ireland ranked under countries with less impact of sociodemographic factors [40].…”

The social specificities of hostility toward vaccination against Covid-19 in France

“…In particular, ethno-racial minorities are both more exposed to this pandemic and more reluctant to be vaccinated than the majority population, so a major effort must be made to reach them in this vaccination campaign. Failure to take into account the social determinants of reluctance to vaccinate could lead to strengthening social inequalities in terms of morbidity and mortality [ 43 , 44 ], as well as in terms of care work, mental health, and sexual and reproductive health, which particularly affect women [ 45 ].…”

Regional disparities in SARS-CoV-2 infections by labour market indicators: a spatial panel analysis using German notification data

“…For example, studies from Germany [16][17][18][19], the UK [20], and the US [21,22], suggest that SARS-CoV-2 infections risks and COVID-19 mortality rates are comparatively higher in regions with high poverty rates or low income levels, or in regions that are generally socioeconomically disadvantaged. Interestingly, studies that also compare associations between different phases of the pandemic in Germany demonstrate that these socioeconomic differences are less pronounced (or even inversed) in the early rst wave of the pandemic (with lower infection rates and mortality in more disadvantaged regions) [19,23,24]. Such an inverse association during the early phase of the pandemic was also found for the US [25] and France [26].…”