The novel of COVID-19 disease started in late 2019 making the worldwide governments came across a high number of critical and death cases, beyond constant fear of the collapse in their health systems. Since the beginning of the pandemic, researchers and authorities are mainly concerned with carrying out quantitative studies (modeling and predictions) overcoming the scarcity of tests that lead us to under-reporting cases. To address these issues, we introduce a Bayesian approach to the SIR model with correction for under-reporting in the analysis of COVID-19 cases in Brazil. The proposed model was enforced to obtain estimates of important quantities such as the reproductive rate and the average infection period, along with the more likely date when the pandemic peak may occur. Several under-reporting scenarios were considered in the simulation study, showing how impacting is the lack of information in the modeling.
The novel of COVID-19 disease started in late 2019 making the worldwide governments came across a high number of critical and death cases, beyond constant fear of the collapse in their health systems. Since the beginning of the pandemic, researchers and authorities are mainly concerned with carrying out quantitative studies (modeling and predictions) overcoming the scarcity of tests that lead us to under- reporting cases. To address these issues, we introduce a Bayesian approach to the SIR model with correction for under-reporting in the analysis of COVID-19 cases in Brazil. The proposed model was enforced to obtain estimates of important quantities such as the reproductive rate and the average infection period, along with the more likely date when the pandemic peak may occur. Several under-reporting scenarios were considered in the simulation study, showing how impacting is the lack of information in the modeling.
O texto tem por objetivo avaliar indicadores produzidos a partir de dados do Censo da Educação Superior na perspectiva do acesso à Educação Superior Pública no Brasil. Para essa análise utilizou-se os indicadores definidos por Silva e Veloso (2013), que estabelecem para as dimensões do acesso os seguintes indicadores: Dimensão do Ingresso – indicadores - vagas, ingressos e formato seletivo; Dimensão da permanência – matrículas – taxa de trancamento e taxa de conclusão. No que refere as vagas, inscritos e ingressos, entre os anos de 2010 e 2019, houve aumento de vagas foi de cerca de 23,2%, de 75,8% no número de candidatos inscritos, e consequentemente uma maior relação candidato/vaga, e de 15,3% de ingressantes. Observa-se que as matrículas se concentraram na modalidade de ensino presencial, com cerca de 6,1 milhões de matrículas ofertadas nesta modalidade. Das cerca de 2,1 milhões as matrículas ocorridas na rede pública, em torno de 1,5 milhões dessas matrículas não estiveram vinculadas a programas de reserva de vagas. Entre as matrículas de estudantes que ingressaram por meio de reserva de vagas, verifica-se que apenas cerca de 32,0% estavam relacionadas a estudantes que participam de algum tipo de apoio social. Entre os estudantes que ingressaram por meio de ampla concorrência, 15,4% dos estudantes participaram de algum tipo de apoio social. As políticas públicas instituídas possibilitaram o ingresso de estudantes das escolas públicas e com vulnerabilidade social, entretanto as ações e programas ainda não afirmam a permanência nas instituições de educação superior com o objetivo de conclusão dos cursos.
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