Multivariate regression analysis in the probability of deaths in COVID-19 cases: a case study in the State of Pará, Amazon region, Brazil

Authors

DOI:

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

Keywords:

Probabilistic model; COVID-19 in Brazil; Risk group; Amazon region.

Abstract

Since the first detected cases of COVID-19 in Brazil, researchers have made a great effort to try to understand the disease. Understanding the impact of the disease on people can be instrumental in identifying which groups can be considered at risk. Therefore, this study researches a probabilistic model based on a statistical model of non-linear regression analyzing the following variables: age, if you are a health professional, if you are resident in the Metropolitan Region of Belém (RMB), State of Pará and gender with the objective of identifying those people who have a greater impact on the number of people infected and killed by COVID-19, that is, people who are more likely to die. To carry out the research, we used the data of all infected people by COVID-19 in the State of Pará until July 2020. It can be verified according to the proposal of the probabilistic model that elderly people, with a odds ratio of 1.69 (95% CI 1.52-1.88), residents of Metropolitan Region of Belém, with an odds ratio of 2.14 (95% CI 2.02 - 2.27) and men, with an odds ratio of 1.83 (95% CI 1.73 - 1.95) are groups of people with a higher risk of dying from diseases, while health professionals, with a 0.36 chance ratio (CI9 5% 0.29 - 0.45), are less likely to die.

Author Biographies

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.

References

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

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Published

02/12/2020

How to Cite

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 . Multivariate regression analysis in the probability of deaths in COVID-19 cases: a case study in the State of Pará, Amazon region, Brazil. 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: 23 nov. 2024.

Issue

Vol. 9 No. 11

Section

Exact and Earth Sciences

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Copyright (c) 2020 Cássio Pinho dos Reis; Herson Oliveira da Rocha; Nayara de Araújo Muzili Reis; Sávio Pinho dos Reis ; Gustavo Nogueira Dias; Gilberto Emanoel Reis Vogado; Vanessa Mayara Souza Pamplona ; Washington Luiz da Silva Junior

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