Interiorization of Covid-19: An analysis of the evolution of cases / 10 thousand inhabitants in municipalities in the Microregion of Garanhuns in the State of Pernambuco, using non-linear regression models

Authors

DOI:

https://doi.org/10.33448/rsd-v9i9.6582

Keywords:

Viruses; Forecast; Propagation; Population.

Abstract

The internalization of confirmed cases of COVID-19 in the state of Pernambuco has raised concerns among the population. Thus, it was analyzed the official data provided by the daily bulletins of the municipal health secretariats of the municipalities, in the period from 23/04/2020 to 06/25/2020, collected weekly and the objective was to adjust different non-linear models in the analysis of cases / 10 thousand inhabitants of COVID-19 in the Pernambuco municipalities of Lajedo, Bom Conselho and Garanhuns, in addition to checking the inflection point of the disease, the period that informs about the decrease in the evolution of cases. For the comparison between the models, the adjusted determination coefficient, mean absolute deviation and Akaike information criterion were used. The verification of the assumptions of the residues was carried out through the Shapiro-Wilk tests for normality, Durbin-Watson tests for independence and Breush-Pagan tests for homoscedasticity, the assumptions were met. The best adjustments were Von Bertalanffy for the municipalities of Garanhuns and Bom Conselho and Gompertz for the municipality of Lajedo, despite overestimating the number of cases in the asymptotic limit. In calculating the absolute growth rate (ACT) it was found that the inflection points of all models occurred within the period of 64 days after the start of the pandemic. However, it is not possible to make reliable predictions of when the numbers of confirmed cases will be minimized due to being in an initial stage of interiorization. However, these results can be important in controlling the spread, guiding the authorities and the population to preventive care.

References

Agência Estadual de Planejamento e Pesquisas de Pernambuco – CONDEPE/FIDEM. (2010). Composição setorial do Valor Adicionado Bruto (VAB). Recife: CONDEPE/FIDEM.

Albuquerque, N. L. S. D., & Pedrosa, N. L. (2020). Análise espacial dos casos de COVID-19 e leitos de terapia intensiva no estado do Ceará, Brasil. Ciência & Saúde Coletiva, 25, 2461-2468.

Baker, S. R., Bloom, N., Davis, S. J., & Terry, S. J. (2020). Covid-induced economic uncertainty. National Bureau of Economic Research. 26983, 1-17. doi: 10.3386/w26983

Dong, Y., Mo, X., Hu, Y., Qi, X., Jiang, F., Jiang, Z., & Tong, S. (2020). Epidemiology of COVID-19 among children in China. Pediatrics, 145(6). 1-12. doi: https://doi.org/10.1542/peds.2020-0702

Ferreira, M. R. S. (2013). A construção discursiva da sustentabilidade urbana na Microrregião de Garanhuns-PE. Universidade Federal de Sergipe (UFS). Disponível em: https://ri.ufs.br/handle/riufs/4274

Fundação Oswaldo Cruz (Fiocruz) (2020). Estudo aponta interiorização da Covid-19 em Pernambuco. Disponível em: https://portal.fiocruz.br/noticia/estudo-aponta-interiorizacao-da-covid-19-em-pernambuco

Ghosal, S., Sengupta, S., Majumder, M., & Sinha, B. (2020). Linear Regression Analysis topredict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases -March 14th 2020). Diabetes & metabolic syndrome. Advance online publication, 14(4), 311–315. doi: https://doi.org/10.1016/j.dsx.2020.03.017

Laird, A. K. (1965). Dynamics of relative growth. Growth, Ministério da Saúde [MS] (2020). Painel Coronavírus, 29(9), 249-263. Disponível em: https://covid.saude.gov.br/

Nelder, J. A. (1961). The fitting of a generalization of the logistic curve. Biometrics, 17(1), 89-110. doi: https://www.jstor.org/stable/2527498

Prata, D. N., Rodrigues, W., & Bermejo, P. H. (2020). Temperature significantly changes COVID-19 transmission in (sub) tropical cities of Brazil. Science of the Total Environment, 729, 1-7. doi: https://doi.org/10.1016/j.scitotenv.2020.138862

Rodriguez-Morales, A. J., Gallego, V., Escalera-Antezana, J. P., Méndez, C. A., Zambrano, L. I., Franco-Paredes, C., ... & Risquez, A. (2020). COVID-19 in Latin America: The implications of the first confirmed case in Brazil. Travel medicine and infectious disease, 35, 1-4. doi: 10.1016/j.tmaid.2020.101613

Santiago, E. J. P., da Silva Freire, A. K., Cunha Filho, M., Moreira, G. R., de Almeida Ferreira, D. S., & Cunha, A. L. X. (2020). Non-linear models applicable to mortality and cases of COVID-19 in Brazil, Italy and the world. Research, Society and Development, 9(6), 117963561. doi: http://dx.doi.org/10.33448/rsd-v9i6.3561.

Santos, A.L.P., Moreira, G. R., Gomes-Silva, F., Brito, C., da Costa, M., Pereira, L., Maurício, R. M., Azevêdo, J., Pereira, J. M., Ferreira, A. L., & Filho, M. C. (2019). Generation of models from existing models composition: An application to agrarian sciences. PloS one, 14(12), e0214778. doi: https://doi.org/10.1371/journal.pone.0214778

Santos, A.L.P., Figueiredo, M., Ferreira, T., Gomes-Silva, F., Moreira, G., Silva, J., & Freitas, J. (2020). Analysis and forecasting of the evolution of COVID-19 death numbers in the state of Pernambuco and Ceará using regression models. Research, Society and Development, 9(7), e602974551. doi: http://dx.doi.org/10.33448/rsd-v9i7.4551.

Von Bertalanffy, L. (1957). Quantitative laws in metabolism and growth. The quarterly review of biology, 32(3), 217-231. doi: https://doi.org/10.1086/401873

Wang, L., & Wong, A. (2020). COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images. University of Waterloo, Canada, (4). arXiv preprint arXiv:2003.09871.

World Health Organization, WHO Director-General’s Remarks at the Media Briefingon 2019-nCoV on 11 February 2020, (2020a). Disponível em: https://www.who.int/dg/speeches/detail/whodirector-general-s-remarks-at-the-media-briefing-on-2019-ncov-on-11-february-2020.

World Health Organization, WHO Director-General’s Remarks at the Media Briefingon 2019-nCoV on 11 march 2020, (2020b). Disponível em: https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19---11-march-2020

Yang, W., Zhang, D., Peng, L., Zhuge, C., & Hong, L. (2020). Rational evaluation of various epidemic models based on the COVID-19 data of China. (1). arXiv preprint arXiv:2003.05666

Published

30/08/2020

How to Cite

Amaral, L. S. do, Santos, A. L. P. dos, Figueiredo, M. P. S. de, Ferreira, D. S. de A., Silva, J. E., Santos, H. C. T. dos, Rocha, J. S., Gomes, D. A., & Moreira, G. R. (2020). Interiorization of Covid-19: An analysis of the evolution of cases / 10 thousand inhabitants in municipalities in the Microregion of Garanhuns in the State of Pernambuco, using non-linear regression models. Research, Society and Development, 9(9), e293996582. https://doi.org/10.33448/rsd-v9i9.6582

Issue

Section

Health Sciences