Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: May 7, 2025
Date Accepted: Dec 22, 2025
Digital exclusion among people experiencing homelessness and residents of urban communities in Brazil: an intersectional multilevel analysis
ABSTRACT
Background:
The COVID-19 pandemic highlighted digital inequalities, limiting access to health information and hindering the adoption of preventive measures.
Objective:
This study aims to identify intersectional profiles associated with a lower likelihood of seeking COVID-19-related information online among vulnerable populations in Brazil, using an intersectional statistical approach.
Methods:
A cross-sectional study conducted between 2021 and 2023. The MAIHDA (Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy) approach was applied with 115 intersectional strata defined by sex, race/ethnicity, income, education, and SUS usage. The outcome variable was the search for COVID-19 information online.
Results:
A total of 2,652 individuals participated, 60.4% of whom were male, and 73.3% identified as Black or Mixed-race. The majority (60.8%) did not use the internet as a source of information. Information-seeking was more frequent among women (OR = 1.49), individuals with higher education (OR = 5.59), and those with an income greater than 3 minimum wages (OR = 4.54). The intersectional analysis demonstrated good model fit (VPC: 25%; ROC: 0.74) and showed that men with low income and education were the least likely to seek information online.
Conclusions:
The intersectional analysis revealed structural patterns of informational exclusion, calling for policies that promote digital inclusion, critical literacy, and more equitable health communication strategies.
Citation
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