Factors associated with access to health services among people with long COVID in the Brazilian Amazon
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Amanda Loyse da Costa Miranda1, Vanessa Ladyanne da Silva Costa1, Ana Rosa Tavares da Paixão1
1Graduate Program in Nursing at the Federal University of Pará (PPGENF/UFPA), Universidade Federal do Pará, Belém, Pará, Brazil.
Background:
Access to healthcare services for the population with long COVID is a challenge, as healthcare systems have been tasked with responding effectively to the extensive clinical heterogeneity of this disease.
Objective:
To analyze the factors associated with access to health services among people with long COVID in the Brazilian Amazon.
Methods:
This is a cross-sectional study using a quantitative method, conducted through an online survey between May 2023 and January 2024. The study included participants aged 18 years or older, residing in the northern region of Brazil, with a confirmed diagnosis of COVID-19 and who experienced long COVID. Participants completed an adapted version of the questionnaire on the Research Electronic Data Capture platform. Data were analyzed by multiple logistic regression.
Results:
A total of 364 people with long COVID participated in the study, of which only 167 (45.88%) had access to healthcare to treat the symptoms of this clinical condition. In the final multiple logistic regression model, only factors related to the need for services were associated with healthcare access. Participants with symptoms of dermatological alterations (AOR = 2.57; p = 0.01), a pre-COVID-19 diagnosis of chronic disease (AOR = 5.62; p = 0.04), those who treated their most severe COVID-19 infection with the assistance of a healthcare professional (AOR = 4.97; p = 0.01), and those who used antibiotics during their most severe COVID-19 infection (AOR = 3.24; p = 0.01) were more likely to access healthcare services for treating long COVID.
Conclusion:
Factors related to the need for services were the only ones associated in this population. It is important to know these aspects to identify the most affected populations and propose measures.
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