ABSTRACT
BACKGROUND: Evidence on inequalities in the health services use is important for public policy formulation, even more so in a pandemic context. The aim of this study was to evaluate socioeconomic inequities in the specialized health use services according to health insurance and income, following COVID-19 in individuals residing in Southern Brazil. METHODS: This was a cross-sectional telephone survey with individuals aged 18 years or older diagnosed with symptomatic COVID-19 using the RT-PCR test between December 2020 and March 2021. Questions were asked about attendance at a health care facility following COVID-19, the facilities used, health insurance and income. Inequalities were assessed by the following measures: Slope Index of Inequality (SII) and Concentration Index (CIX). Adjusted analyses were performed using Poisson regression with robust variance adjustment using the Stata 16.1 statistical package. RESULTS: 2,919 people (76.4% of those eligible) were interviewed. Of these, 24.7% (95%CI 23.2; 36.3) used at least one specialized health service and 20.3% (95%CI 18.9; 21.8) had at least one consultation with specialist doctors after diagnosis of COVID-19. Individuals with health insurance were more likely to use specialized services. The probability of using specialized services was up to three times higher among the richest compared to the poorest. CONCLUSIONS: There are socioeconomic inequalities in the specialized services use by individuals following COVID-19 in the far south of Brazil. It is necessary to reduce the difficulty in accessing and using specialized services and to extrapolate the logic that purchasing power transposes health needs. The strengthening of the public health system is essential to guarantee the population's right to health.
Subject(s)
COVID-19 , Healthcare Disparities , Humans , Socioeconomic Factors , Brazil/epidemiology , Cross-Sectional Studies , COVID-19/epidemiology , Health ServicesABSTRACT
Health counseling is a prevention and health promotion action, especially in the context of a pandemic, for both preventing disease and maintaining health. Inequalities may affect receipt of health counseling. The aim was to provide an overview of the prevalence of receiving counseling and to analyze income inequality in the receipt of health counseling. METHODS: This was a cross-sectional telephone survey study with individuals aged 18 years or older with diagnosis of symptomatic COVID-19 using RT-PCR testing between December 2020 and March 2021. They were asked about receipt of health counseling. Inequalities were assessed using the Slope Index of Inequality (SII) and Concentration Index (CIX) measures. We used the Chi-square test to assess the distribution of outcomes according to income. Adjusted analyses were performed using Poisson regression with robust variance adjustment. RESULTS: A total of 2919 individuals were interviewed. Low prevalence of health counseling by healthcare practitioner was found. Participants with higher incomes were 30% more likely to receive more counseling. CONCLUSIONS: These results serve as a basis for aggregating public health promotion policies, in addition to reinforcing health counseling as a multidisciplinary team mission to promote greater health equity.
Subject(s)
COVID-19 , Health Equity , Adult , Humans , Brazil/epidemiology , COVID-19/epidemiology , Cross-Sectional Studies , Health Status Disparities , Prevalence , Socioeconomic Factors , AdolescentABSTRACT
OBJETIVO: To describe the initial baseline results of a population-based study, as well as a protocol in order to evaluate the performance of different machine learning algorithms with the objective of predicting the demand for urgent and emergency services in a representative sample of adults from the urban area of Pelotas, Southern Brazil. METHODS: The study is entitled "Emergency department use and Artificial Intelligence in PELOTAS (RS) (EAI PELOTAS)" (https://wp.ufpel.edu.br/eaipelotas/). Between September and December 2021, a baseline was carried out with participants. A follow-up was planned to be conducted after 12 months in order to assess the use of urgent and emergency services in the last year. Afterwards, machine learning algorithms will be tested to predict the use of urgent and emergency services over one year. RESULTS: In total, 5,722 participants answered the survey, mostly females (66.8%), with an average age of 50.3 years. The mean number of household people was 2.6. Most of the sample has white skin color and incomplete elementary school or less. Around 30% of the sample has obesity, 14% diabetes, and 39% hypertension. CONCLUSION: The present paper presented a protocol describing the steps that were and will be taken to produce a model capable of predicting the demand for urgent and emergency services in one year among residents of Pelotas, in Rio Grande do Sul state.
Subject(s)
Artificial Intelligence , Obesity , Adult , Female , Humans , Middle Aged , Male , Socioeconomic Factors , Brazil , Emergency Service, HospitalABSTRACT
Objetivo: Descrever o perfil de óbitos por COVID-19 no município de Rio Grande, Rio Grande do Sul, Brasil. Metodologia: Trata-se de um estudo transversal, descritivo, com dados oriundos do banco de óbitos da Vigilância Epidemiológica, registrados no período de março a dezembro de 2020. Resultados: Dos 194 óbitos, a maioria era do sexo masculino (63,4%), com 60 anos ou mais (82,5%), de cor da pele branca (82,5%), residentes na região central histórica do município (11,3%). Quanto à ocupação, a maior ocorrência de óbitos foi entre os aposentados (69,5%), seguido por comerciante ou autônomo (17,7%). Com relação às morbidades, 38,7% tinha cardiopatias, 29,4% hipertensão arterial sistêmica, 28,0% diabetes mellitus e praticamente a metade dos indivíduos tinha multimorbidade (49,0%). Conclusões: Com a identificação do perfil de óbitos por COVID-19 no município de Rio Grande no período de março a dezembro de 2020, esses dados podem contribuir para auxiliar os gestores no planejamento de ações estratégicas e educativas de prevenção e combate à COVID-19, principalmente no direcionamento de grupos prioritários nas campanhas de vacinação (AU)
Objective: Describe the COVID-19 death profile in the city of Rio Grande, Rio Grande do Sul, Brazil. Methods: This is a cross-sectional descriptive study using data from the Epidemiological Surveillance service deaths database of deaths notified from March to December 2020. Results: Of the 194 deaths, most were male (63.4%), aged 60 years or more (82.5%), of white skin color (82.5%), and living in the central historic district of the city (11.3%). With regard to occupation, the highest occurrence of deaths was among retirees (69.5%), followed by tradesmen or the self-employed (17.7%). Regarding morbidities, 38.7% had heart disease, 29.4% hypertension, 28.0% diabetes mellitus, and practically half of the individuals had multiple morbidities (49.0%). Conclusions: We identified the profile of COVID-19 deaths in the city of Rio Grande in the period from March to December 2020. These data can help health service managers to plan strategic and educational actions to prevent and combat COVID-19, mainly by targeting priority groups in vaccination campaigns
Subject(s)
Humans , Cross-Sectional Studies , Immunization Programs , Epidemiological Monitoring , Multimorbidity , COVID-19/mortality , COVID-19/epidemiologyABSTRACT
Objetivo: Descrever o perfil de óbitos por COVID-19 no município de Rio Grande, Rio Grande do Sul, Brasil. Metodologia: Trata-se de um estudo transversal, descritivo, com dados oriundos do banco de óbitos da Vigilância Epidemiológica, registrados no período de março a dezembro de 2020. Resultados: Dos 194 óbitos, a maioria era do sexo masculino (63,4%), com 60 anos ou mais (82,5%), de cor da pele branca (82,5%), residentes na região central histórica do município (11,3%). Quanto à ocupação, a maior ocorrência de óbitos foi entre os aposentados (69,5%), seguido por comerciante ou autônomo (17,7%). Com relação às morbidades, 38,7% tinha cardiopatias, 29,4% hipertensão arterial sistêmica, 28,0% diabetes mellitus e praticamente a metade dos indivíduos tinha multimorbidade (49,0%). Conclusões: Com a identificação do perfil de óbitos por COVID-19 no município de Rio Grande no período de março a dezembro de 2020, esses dados podem contribuir para auxiliar os gestores no planejamento de ações estratégicas e educativas de prevenção e combate à COVID-19, principalmente no direcionamento de grupos prioritários nas campanhas de vacinação (AU)
Objective: Describe the COVID-19 death profile in the city of Rio Grande, Rio Grande do Sul, Brazil. Methods: This is a cross-sectional descriptive study using data from the Epidemiological Surveillance service deaths database of deaths notified from March to December 2020. Results: Of the 194 deaths, most were male (63.4%), aged 60 years or more (82.5%), of white skin color (82.5%), and living in the central historic district of the city (11.3%). With regard to occupation, the highest occurrence of deaths was among retirees (69.5%), followed by tradesmen or the self-employed (17.7%). Regarding morbidities, 38.7% had heart disease, 29.4% hypertension, 28.0% diabetes mellitus, and practically half of the individuals had multiple morbidities (49.0%). Conclusions: We identified the profile of COVID-19 deaths in the city of Rio Grande in the period from March to December 2020. These data can help health service managers to plan strategic and educational actions to prevent and combat COVID-19, mainly by targeting priority groups in vaccination campaigns