Socioeconomic factors and the probability of death by Covid-19 in Brazil

Abstract

Background To design better measures to contain the Covid-19 epidemics, it is relevant to know whether socioeconomic factors are associated with a higher risk of death by Covid-19. This work estimates the effects of individual socioeconomic characteristics on the risk of death by Covid-19. Methods Logistic models were estimated to assess the effect of socioeconomic characteristics (income, race/ethnicity, schooling, occupation and economic activity) on the risk of death from Covid-19. For this purpose, Covid-19 individual death records in Rio de Janeiro state, Brazil were combined with the Annual Register of Social Information, which contains socioeconomic information about formal workers. Findings Workers employed in establishments in the health and public safety sectors present a risk of dying 2.46 and 2.25 times higher than those employed in other activities. Non-white people, men, and those who work in the Metropolitan Region are also more likely to die from Covid-19. People with higher education are 44% less likely to die from the disease. Conclusions Some population groups are more vulnerable to the Covid-19 pandemic and individual socioeconomic conditions play a relevant role in the probability of death by the disease. That should be considered in the design of prevention policies to be adopted.

Identifying regional variation in place visit behavior during a global pandemic

“…Recent work by Verma et al [63] demonstrated that COVID-19 case count was significantly higher in lower-income neighborhoods within the United States. Similar findings have been reported in other parts of the world [39,9], all while controlling for external factors and environmental variables. Few studies have explored the combination of visit duration and global pandemics but those that have are typically focused on the epidemiological facet.…”

Social contact patterns and implications for infectious disease transmission – a systematic review and meta-analysis of contact surveys

“…Data constraints limited the numbers of factors we were able to explore – for example, despite evidence ( Kiti et al, 2014 ) suggesting that contact patterns differ across rural and urban settings, only three studies ( Kiti et al, 2014 ; le Polain de Waroux et al, 2018b ; Neal et al, 2020 ) contained information from both rural and urban sites, allowing classification. Similarly, we were unable to examine the impact of socioeconomic factors such as household wealth, despite experiences with COVID-19 having highlighted strong socioeconomic disparities in both transmission and burden of disease ( De Negri et al, 2021 ; Routledge et al, 2021 ; Ward et al, 2021 ; Winskill et al, 2020 ) and previous work suggesting that poorer individuals are less likely to be employed in occupations amenable to remote working ( Loayza, 2020 ). A lack of suitably detailed information in the studies conducted precludes analysis of these factors but highlights the importance of incorporating economic questions into future contact surveys, such as household wealth and house square footage.…”

Social Contact Patterns and Implications for Infectious Disease Transmission: A Systematic Review and Meta-Analysis of Contact Surveys

“…Similarly, we were unable to examine the impact of socioeconomic factors such as household wealth, despite experiences with COVID-19 having highlighted strong socio-economic disparities in both transmission and burden of disease (De Negri et al, 2021;Routledge et al, 2021;Ward et al, 2021;Winskill et al, 2020) and previous work suggesting that poorer individuals are less likely to be employed in occupations amenable to remote working (Loayza, 2020). A lack of suitably detailed information in the studies conducted precludes analysis of these factors but highlights the importance of incorporating economic questions into future contact surveys, such as household wealth and house square footage.…”