Inequities in COVID-19 morbidity in Brazil: the influence of demographic and socioeconomic characteristics and preexisting health conditions

Abstract

Objective: To analyze COVID-19 morbidity according to sociodemographic characteristics and preexisting health conditions, based on data from a survey conducted in 2023 online called “ConVid-2 Behavior Survey”. Methods: This was a cross-sectional epidemiological study using the Respondent-Driven Sampling (RDS) method. Prevalence estimates and 95% confidence intervals were calculated for five COVID-19-related indicators. Logistic regression models were applied to test the hypothesis of associations between outcomes and sociodemographic characteristics. Results: The sample included 3,805 individuals aged 18 years or older. Approximately 50% of participants had received four or more doses of the COVID-19 vaccine. The estimated prevalence of COVID-19 was 49.5%, with significant and increasing gradients by age and decreasing gradients by education level. Long COVID was identified in 32% of individuals with confirmed COVID-19, with the highest proportions among women (38.3%; OR=0.52; p=0.002), those with financial difficulties (38.9%; OR=1.68; p=0.02), and those with a chronic noncommunicable disease (36.3%; OR=1.58; p=0.03). The highest rate of hospitalization occurred among those with Long COVID (12.7%). Death of a household member due to COVID-19 was reported by 5.1% of participants. Conclusion: The findings revealed major socioeconomic inequalities across all indicators related to COVID-19 morbidity. Older age, preexisting health conditions, and Long COVID contributed to greater disease severity and increased hospitalization. These findings are relevant to inform public policies aimed at supporting the diagnosis and management of COVID-19-related complications within the public health system.