Análisis de regresión multivariante en la probabilidad de muerte en casos de COVID-19: un estudio de caso en el Estado de Pará, región amazónica, Brasil

Autores/as

DOI:

https://doi.org/10.33448/rsd-v9i11.10299

Palabras clave:

Modelo probabilístico; COVID-19 en Brasil; Grupo de riesgo; Región Amazónica.

Resumen

Desde los primeros casos detectados de COVID-19 en Brasil, los investigadores han hecho un gran esfuerzo para intentar comprender la enfermedad. Comprender el impacto de la enfermedad en las personas puede ser fundamental para identificar qué grupos pueden considerarse en riesgo. Por tanto, este estudio investiga un modelo probabilístico basado en un modelo estadístico de regresión no lineal analizando las siguientes variables: edad, si es un profesional de la salud, si es residente en la Región Metropolitana de Belém (RMB), Estado de Pará y sexo con el objetivo de identificar a aquellas personas que tienen un mayor impacto en la cantidad de personas infectadas y asesinadas por COVID-19, es decir, las personas que tienen más probabilidades de morir. Para realizar la investigación, utilizamos los datos de todas las personas infectadas por COVID-19 en el Estado de Pará hasta julio de 2020. Se puede verificar según la propuesta del modelo probabilístico que las personas mayores, con una razón de momios de 1,69 (IC 95% 1,52-1,88), residentes de La Región Metropolitana de Belém, con un odds ratio de 2,14 (IC 95% 2,02 - 2,27) y los hombres, con un odds ratio de 1,83 (IC 95% 1,73 - 1,95) son grupos de personas con mayor riesgo de morir por enfermedades, mientras que los profesionales de la salud, con una razón de probabilidad de 0,36 (IC9 5% 0,29 - 0,45), tienen menos probabilidades de morir.

Biografía del autor/a

Cássio Pinho dos Reis, Federal University of Mato Grosso of South

Bachelor in statistics graduated from the Federal University of Pará (2007), master in Applied Statistics and Biometrics from the Federal University of Viçosa (2013) and PhD in Biometrics from the Universidade Estadual Paulista - Botucatu (2019). He is currently Adjunct Professor A, level 1, at the Federal University of Mato Grosso do Sul. He teaches Statistics, Probability and Statistics, Biostatistics, Zootechnical Experimentation and Experimental Statistics. Has experience in Experimental Statistics, Regression and Correlation Analysis and Spatial Statistics.

Herson Oliveira da Rocha, Federal Rural University

Herson Rocha has a degree in Mathematics from the State University of Pará (UEPA, 2005), a master's degree in Geophysics from the Institute of Geosciences of the Federal University of Pará (IG / UFPA, 2012), and a doctorate in Reservoir and Exploration Engineering from the Laboratory of Engineering and Petroleum Exploration of the State University of the North Fluminense Darcy Ribeiro (LENEP / CCT / UENF, 2020). He is also a member of the Brazilian Geophysical Society (SBGf) and the European Association of Geoscientists & Engineers (EAGE). He currently holds the position of adjunct professor at the Federal Rural University of the Amazon (UFRA).

Nayara de Araújo Muzili Reis, Municipal Health Secretariat

Physiotherapist graduated from the Federal University of Mato Grosso do Sul Foundation (UFMS) in 2013. Master's Degree in Health and Development in the Midwest Region by the Faculty of Medicine - Federal University of Mato Grosso do Sul, 2016. Specialization in Occupational Physiotherapy and Ergonomics. Effective physiotherapist at the Municipality of Campo Grande.

Sávio Pinho dos Reis , State University of Pará

Graduated in Biological Sciences from the Federal University of Pará (2007), master's degree in Genetics and Molecular Biology from the Federal University of Pará (2009) and doctorate in Genetics and Molecular Biology from the Federal University of Pará (2015). He is currently an assistant professor at the University of the State of Pará. He has experience in the field of Genetics and Molecular Biology, with an emphasis on Plant Molecular Biology and Quantitative Genetics.

Gustavo Nogueira Dias, Colégio Federal Ten. Rêgo Barros

PhD in Education from the National University of Rosario, Argentina (2017); Master in Geophysics from the Federal University of Pará, Belém (2011); specialist in school management at Centro Universitário do Pará (2008); Degree in Mathematics from the Federal University of Pará (2001). He is currently a professor of federal basic education at Colégio Ten. Rêgo Barros, also acting as a researcher in the areas: Mathematics, Environmental Education, Administration, Accounting and Statistics.

Gilberto Emanoel Reis Vogado, Universidade do Estado do Pará

He has a degree in Mathematics from the University of the Amazon (1991), a master's degree in Geophysics from the Federal University of Pará (2005) and a doctorate in Mathematics Education from the Pontifical Catholic University of São Paulo (2014). He is currently assistant professor IV at the State University of Pará, coordinator of the Fundamentals of Elementary Mathematics Specialization course and professor - First Regional Air Command. Has experience in Mathematics, with emphasis on Mathematics, acting mainly on the following subjects: mathematics, mathematics teaching, correction board and mathematical modeling.

Vanessa Mayara Souza Pamplona , Universidade Federal Rural da Amazônia

He joined the Bachelor's Degree in Statistics in 2004, completing the course in 2008, at the Federal University of Pará - UFPA. In the same year, she was approved in a Public Competition by UFPA, to exercise the Post of Statistician, Class E, with capacity at the Belém University Campus and nominated in the same year. In 2010 he joined the Postgraduate Course in Mathematics and Statistics at UFPA, at the Master's Level, in 2011 he obtained a master's degree. In 2012 she joined the Postgraduate Course in Agronomy (Agricultural Entomology), at the Doctoral Level at the Faculty of Agricultural and Veterinary Sciences of the Universidade Estadual Paulista - Jaboticabal Campus - SP, in 2016 she obtained the title of doctor. In 2013, he was approved in a Public Competition for Evidence and Titles, to fill the position of Professor of the Career of the Higher Teaching in Exclusive Dedication (DE) at the Federal Rural University of the Amazon (UFRA) - Campus de Paragominas - PA. She is currently an effective professor of the Higher Teaching and teaches undergraduate courses in Agronomy, Forestry and Zootechnics, in the disciplines of Statistics, Biostatistics, Experimental Statistics and Biometrics.

Washington Luiz da Silva Junior, Colégio Federal Ten. Rêgo Barros

Licensed professor in Mathematics at the State University of Pará - UEPA. Specialist in Fundamentals of Elementary Mathematics, Educational Management and Teaching of Basic and Higher Education, Financial Mathematics, Statistics and Education in the Field and Brazilian Anthropology (ongoing). Professor at the Federal College Tenente Rêgo Barros- CTRB.

Citas

Agresti, A. (1980). Generalized odds ratios for ordinal data. Biometrics, 36, 59–67. https://doi.org/10.2307/2530495

Allison, P. D. (2012). Logistic regression using SAS: Theory and application. In SAS Institute Inc, Second Edition, Cary, North Carolina, USA.

Bland, J. M., & Altman, D. G. (2000). The odds ratio. Bmj, (7247), 1468. https://doi.org/10.1136/bmj.320.7247.1468

Cabral, R. B. G., Chase, S. A. N., Ribeiro, R. C. M., Marques, G. T., Morais, E. C., de Jesus Zissou, A., de Almeida, J. F. S. (2020). On the evolution of new Coronavirus (SARS-CoV-2) in the state of Pará (Brazil), March – June 2020.

Candido, D. D. S., Watts, A., Abade, L., Kraemer, M. U., Pybus, O. G., Croda, J., Faria, N. R. (2020). Routes for COVID-19 importation in Brazil. Journal of Travel Medicine, taaa042.https://doi.org/10.1093/jtm/taaa042.

Cardoso, A. C. D., & Miranda, T. B. (2018). Invisibilidade social e produção do espaço subordinado em Belém (PA). Paisagem e Ambiente, (41), 85–107. https://doi.org/10.11606/issn.2359-5361.v0i41p85-107

Chambers, J. (2008). Software for data analysis: programming with R. In Springer Science and Business Media, Stanford, CA, USA.

Croda, J., Oliveira, W. K. D., Frutuoso, R. L., Mandetta, L. H., Baia-da-Silva, D. C., Brito-Sousa, J. D., & Lacerda, M. V. G. (2020). COVID-19 in Brazil: advantages of a socialized unified health system and preparation to contain cases. Revista da Sociedade Brasileira de Medicina Tropical, 53.

Dias, N. L., Silva, E. V. D., Pires, M. A., Chaves, D., Sanada, K. L., Fecury, A. A., Leal, S. D. (2020). Predição da propagação do SARS-CoV-2 no Estado do Amapá, Amazônia, Brasil, por modelagem matemática. Revista Científica Multidisciplinar Núcleo do Conhecimento, Volume 6(5), 73–95. (in portuguese)

Giancristofaro, R. A., & Salmaso, L. (2007). Model performance analysis and model validation in logistic regression. Statistica, 63(2), 375–396.

Hosmer Jr, D. W., Lemeshow, S., Sturdivant, R. X. (2013). Applied logistic regression. In John Wiley and Sons, Inc, Hoboken, New Jersey, 398.

IBGE (2010). Instituto Brasileiro de Geografia e Estatística (IBGE). In Retrieved from https://www.ibge.gov.br/estatisticas/sociais/populacao/9662-censo-demografico-2010.html ?edicao=9749&t=o-que-e, 2019.

Jesus, J. G., Sacchi, C., Claro, I., Salles, F., Manulli, E., Silva, D., Faria, N. R. (2020). First cases of Coronavirus Disease (COVID-19) in Brazil, South America (2020). United Kingdom: Virological, Retrieved from http://virological.org/t/first-cases-ofcoronavirus-disease-covid-19-in-brazil-south-america-2-genomes-3rd.

Kermack, W. O., & McKendrick, A. G. A (1927). Contribution to the mathematical theory of epidemics. Proceedings of the royal society of london. Series A, Containing papers of a mathematical and physical character, 115(772), 346 700–721.

Kounev, S., Lange, K. D., von Kistowski, J. (2020). Review of basic probability and statistics. In Systems Benchmarking, Springer, Cham, 23–44).

Lewis-Beck, C., and Lewis-Beck, M. (1984). Applied regression: An introduction. InSage publications, 22, 384.

Martins, L. K., Carvalho, A. R. D. S., Oliveira, J. L. C. D., Santos, R. P. D., Lordani, T. V. A. (2020). Quality of life and perception of health status among hospitalized individuals, Escola Anna Nery, 24(4), e20200065, 405 https://doi.org/10.1590/2177-9465-ean-2020-0065

Menard, S. (2002). Applied logistic regression analysis. In Sage publication, 106, Thosand Oak, London, New Delhi.

Mendes, L. A. S. (2018). A Geografia-Histórica da região metropolitana de Belém. Revista Espacialidades, 14(01), 10–39.

Neter, J., Wasserman, W., Kutner, M. H.(1983). Applied linear statistical models. In Richard D. Irwin. Inc., Homewood, IL, 842.

Oliveira, W. K. D., Duarte, E., França, G. V. A. D., Garcia, L. P. (2020). How Brazil can stop COVID-19. Epidemiologia e Serviços de Saúde, 29(2), e2020044. https://doi.org/10.5123/S1679-49742020000200023. (in portuguese).

Oliveira Ribeiro, W. (2016). Entre a metrópole e a cidade média: a complexidade das interações espaciais e 351 das dinâmicas de centralidade da cidade de Castanhal no nordeste paraense. GEOUSP Espaço e Tempo(Online), 20(1), 115–129.

Petropoulos, F., & Makridakis, S., Forecasting (2020). The novel coronavirus COVID-19. PloS one, 15(3), e0231236. https://doi.org/10.1371/journal.pone.0231236

Pregibon, D. (1981). Logistic regression diagnostics. The Annals of Statistics, 9(4), 705–724.

Priyadarshan, P. M. (2019). Basic Statistics. In PLANT BREEDING: Classical to Modern, Springer, Singapore, 131–169.

Pulkstenis, E., and Robinson, T. J. (2002). Two goodness-of-fit tests for logistic regression models with continuous covariates. Statistics in medicine, 21(1), 79–93. https://doi.org/10.1002/sim.943

Qin, X., Chen, C., Yam, K. C., Huang, M., Ju, D. (2020). The double-edged sword of leader humility: Investigating when and why leader humility promotes versus inhibits subordinate deviance. Journal of Applied Psychology, 105(7), 693-–712. https://doi.org/10.1037/apl0000456

Romano, J. P., & Wolf, M. (2005). Stepwise multiple testing as formalized data snooping. Econometrica, 73(4), 1237–1282. https://doi.org/10.1111/j.1468-0262.2005.00615.x

Sarkar, S. K. (2002). Some results on false discovery rate in stepwise multiple testing procedures. Annals of statistics, 30(1), 239–257. Retrieved from https://www.jstor.org/stable/2700010

Silva, P. C., Batista, P. V., Lima, H. S., Alves, M. A., Guimarães, F. G., Silva, R. C. (2020). COVID-ABS: An agent-based 348 model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions. Chaos, Solitons & Fractals, 110088. https://doi.org/10.1016/j.chaos.2020.110088

Szumilas, M. (2010). Explaining odds ratios. Journal of the Canadian academy of child and adolescent psychiatry, 19(3), 227–229.

Xie, X. J., Pendergast, J., Clarke, W. (2002). Increasing the power: A practical approach to goodness-of-fit test for logistic regression models with continuous predictors. Computational Statistics and Data Analysis, 52(5), 2703–2713. https://doi.org/10.1016/j.csda.2007.09.027

Werneck, G. L., and Carvalho, M. S (2020). A pandemia de COVID-19 no Brasil: crônica de uma crise sanitária anunciada. Caderno de Saúde Pública, 36(5), https://doi.org/10.1590/0102-311X00068820

Zhou, P., Yang, X. L., Wang, X. G., Hu, B., Zhang, L., Zhang, W., ... Chen, H. D. A (2020). Pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 579(7798), 270–273. https://doi.org/10.1038/s41586-020-2012-7

Descargas

Publicado

02/12/2020

Cómo citar

REIS, C. P. dos .; ROCHA, H. O. da .; REIS, N. de A. M. .; REIS , S. P. dos .; DIAS, G. N. .; VOGADO, G. E. R. .; PAMPLONA , V. M. S. .; SILVA JUNIOR, W. L. da . Análisis de regresión multivariante en la probabilidad de muerte en casos de COVID-19: un estudio de caso en el Estado de Pará, región amazónica, Brasil. Research, Society and Development, [S. l.], v. 9, n. 11, p. e71291110299, 2020. DOI: 10.33448/rsd-v9i11.10299. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/10299. Acesso em: 30 jun. 2024.

Número

Sección

Ciencias Exactas y de la Tierra