Social vulnerability and COVID-19 in Maringá, Brazil

Abstract

This research explores the relationship between COVID-19 and social vulnerability on an intra-urban scale. For this, two composite indicators of social vulnerability have been constructed. The composite indicator constructed by the Benefit-of-the-Doubt considers spatial heterogeneity. It weakly captures the conceptually most significant individual indicator of social vulnerability ( R =-0.39), as it overestimates the above-average performance sub-indicators. The composite indicator constructed by the Principal Component Analysis considers that the sub-indicators have the same weights in different census tracts, resulting in a highly consistent composite indicator as a multidimensional phenomenon concept ( R =-0.93). These findings allow reaching four conclusions. First, the direction and strength of correlations associated with COVID-19 are sensitive to the method employed to construct the composite indicator and not just the geographic scale and space. Second, Medium and High social vulnerability census tracts concentrate 97% of the population but only 93% of COVID-19 cases and deaths. Third, people living in census tracts of None and Low social vulnerability are 3.87 and 2.13 times more likely to be infected or die from COVID-19. Fourth, policies to combat COVID-19 in the study area should prioritize older populations regardless of their social conditions.

Socio-Economic Vulnerability Assessment for Supporting a Sustainable Pandemic Management in Austria

“…In Figure 9, we see a relation between a high VI and an increased number of deaths indicating a successful application of the VA. This correlation has also been confirmed in other studies [36]. Still, some differences can be seen.…”

“…Furthermore, the correlation between COVID-19 and VI was influenced by the creation of the composite indicator. In addition to the impact of different weighting methods, the selection of indicators is also important [36]. In our case, important indicators are missing due to the lack of data at the municipality level.…”

“…The capacity to anticipate and adapt to an epidemic/pandemic was described through economic, political, and educational factors. In the literature, the economic situation commonly refers to the financial status of residents [15,36]. The economic situation can be estimated through purchasing power and unemployment.…”

Fuzzy-Set-Based Multi-Attribute Decision-Making, Its Computing Implementation, and Applications

“…The appropriation of the system by researchers in these areas favors the understanding and elaboration of public policies that allow for reductions in social vulnerabilities [84], the equitable distribution of public infrastructure in cities [85], improvements in public healthcare services [86], making better decisions in custody hearings [87], promoting the digital maturation of companies, achieving opportunities and avoiding market threats [88], and improving accessibility to healthcare facilities [89], among others.…”

Main social vulnerability indicators in the COVID-19 pandemic in Iran

“…Previous findings from the studies of vulnerability-relevant factors for COVID-19 have also confirmed our results. Living in high-density populations causes the spread of COVID-19 due to crowded areas and high physical contact with other people ( 36 – 38 ). Furthermore, vulnerable groups ( aged 65 years or older, aged 17 years or younger, older than age 5 with a disability, and single-parent households) and public health infrastructure ( number of healthcare facilities in the area ) were the other considerable domains and indicators with the highest weight.…”