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Título: POISSON REGRESSION TO ANALYZE THE INCIDENCE OF DEATHS FROM IN THE CITIES OF RIO DE JANEIRO: A SOCIO-DEMOGRAPHIC APPROACH
Instituição: PONTIFÃCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO - PUC-RIO
Autor(es): DAYANA XIMENES DOS SANTOS FRAZAO
Colaborador(es): PAULA MEDINA MACAIRA LOURO - Orientador
PEDRO GOMES ANDRADE - Coorientador
Data da catalogação: 23 11:10:20.000000/06/2022
Tipo: THESIS Idioma(s): PORTUGUESE - BRAZIL
Referência [pt]: https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/DEI/serieConsulta.php?strSecao=resultado&nrSeq=59715@1
Referência [en]: https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/DEI/serieConsulta.php?strSecao=resultado&nrSeq=59715@2
Referência DOI: https://doi.org/10.17771/PUCRio.acad.59715

Resumo:
Since February 2020 the pandemic generated by the new coronavirus SarsCoV-2, the virus generating the disease COVID-19, has caused many deaths, mainly in large urban centers. In Brazil, one of the most affected states was Rio de Janeiro, which, despite all the actions taken to mitigate the progress of COVID19, reached on March 1, 2021 a mortality rate of 206.9 percent, which corresponds to approximately 207 deaths per thousand inhabitants. However, the Rio de Janeiro municipalities were affected differently, where the least affected city reached 9.7 percent and the most affected 331.3 percent. Previous studies in the specialized literature indicate that the main reason for this discrepancy may be associated with factors related to population, income, education, health, economy, territory, and environment. Therefore, this work has as main objective to identify the main socioeconomic, socio-demographic factors and access to hospital resources that are associated with the mortality rate from Sars-CoV-2 in the ninety-two municipalities in the state of Rio de Janeiro based on the Poisson Regression model, in the period from March 01, 2020 to March 01, 2021, accounting for 12 months. From the model chosen it was possible to detect those ten of the eleven factors analyzed influence the mortality rate. The factors being, municipal human development index (IDHM), per capita income (RDPC), percentage of poor (PMPOB), gross domestic product (GDP), gross attendance rate to higher (T_FBSUPER), percentage of subnormal settlements (PER_AGSN), demographic density, number of SUS hospital beds per inhabitant, number of total hospital beds per inhabitant and number of respirators per inhabitant. Thus, the results obtained based on these analyzed factors can help in the creation of more targeted and efficient mitigating actions, according to the characteristics of the municipalities in the state of Rio de Janeiro.
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