Modeling and analysis of a time series of equine infectious anemia cases in the state of Tocantins, Brazil, between 2007 and 2019

Alessandro José Ferreira dos Santos, Jardel Martins Ferreira, Francisco Baptista, Marco Augusto Giannoccaro da Silva, Bruna Alexandrino, Ana Paula Coelho Ribeiro, Raydleno Mateus Tavares, Katyane de Sousa Almeida

Abstract


Equine infectious anemia (EIA) is a viral infectious disease that affects Equidae and is clinically characterized by intermittent fever, anemia, depression, emaciation, and edema. To evaluate disease dynamics in the state of Tocantins, Brazil, a time series of EIA cases in the period 2007–2019 was analyzed to describe the pattern of occurrence and define the autoregressive integrated by moving average (ARIMA) model best suited to make predictions of cases of this disease for the period 2020–2021. The modeling and statistical analysis of the time series were performed using R software. The ARIMA model (2,1,1) was evaluated by Holdout cross-validation, in which data from the periods 2007–2017 and 2018–2019 were used as training and test data, respectively. The analyses showed that EIA was endemic and non-seasonal in Tocantins. The ARIMA model (2,1,1) showed good predictive capacity adjusted for this time series. However, the prediction of 276 cases of EIA in Tocantins for the period 2020–2021 may vary depending on the demand for diagnostic tests for Equidae transportation and herd sanitation in farms considered infection foci. The ARIMA model helps predict the number of EIA cases in Tocantins and improves planning for disease control by the Official Veterinary Service.

Keywords


ARIMA model; Equine infectious anemia; Forecasting; Time series; Tocantins.

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References


Almeida, V. M. A., Gonçalves, V. S. P., Martins, M. F., Haddad, J. P. A., Dias, R. A., Leite, R. C., & Reis J. K. P. (2006). Anemia infecciosa equina: prevalência em equídeos de serviço em Minas Gerais. Arquivo Brasileiro Medicina Veterinária Zootecnia, 58(2), 141-148. doi: 10.1590/S0102-09352006000200001

Baptista, D. Q., Bruhn, F. R. P., Rocha, C. M. B. M., Torres, F. C., Machado, E. D., Sáfadi T., & Pereira S. M. (2016). Temporal series analyses in equine infectious anemia cases in the State of Rio de Janeiro, Brazil, 2007 to 2011. Revista Brasileira de Medicina Veterinária, 38(4), 431-438.

Box, G. E. P., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2016). Time Series Analysis: forecasting and control (5th ed.). New Jersey: John Wiley & Sons Inc.

Chaves, N. P., Bezerra, D. C., Santos, H. P., Pereira, H. M., Guerra, P. C., & Silva, A. L. A. (2014). Ocorrência e fatores de risco associados à identificação da anemia infecciosa equina em equídeos de tração. Ciência Animal Brasileira, 15(3), 301-306. doi: 10.1590/1809-6891v15i318395

Costa, A. M. P. S. (2018). Análise temporal da ocorrência da anemia infecciosa equina no Brasil no período de 2005 a 2016. Dissertação de mestrado, Universidade Estadual Paulista, São Paulo, SP, Brasil.

Ehlers, R. S. (2007). Análise de séries temporais. Cidade: Curitiba. Departamento de Estatística, Universidade Federal do Paraná. Retrieved from http://www.each.usp.br/rvicente/AnaliseDeSeries Temporais.pdf

Ferreira, P. C., Speranza, T., & Costa, J. (2018). Brazilian economic time series (BETS), R package, version 0.4.9. Retrieved from http://127.0.0.1:12355/library/BETS/DESCRIPTION

Ferreira-Keppler, R., Rafael, J. A., & Guerrero, J. C. H. (2010). Sazonalidade e uso de ambientes por espécies de Tabanidae (diptera) na Amazônia Central, Brasil. Neotropical Entomology, 39(4), 645-65. doi: 10.1590/S1519-566X2010000400028

Helfenstein, U. (1996). Box-Jenkis modelling in medical research. Statistical Methods in Medical Research, 5(1), 3-22. doi: 10.1177/096228029600500102.

Hyndman, R., Athanasopoulos, G., Bergmeir, C., Caceres, G., Chhay, L., O'Hara-Wild, M.,… Yasmeen, F. (2019). Forecast: forecasting functions for time series and linear models. R package, version 8.5. Retrieved from http://pkg.robjhyndman.com/forecast

Ministério da Agricultura, Pecuária e Abastecimento. (2019). Coordenação de informação e epidemiologia em saúde animal. Ministério da Agricultura, Pecuária e Abastecimento. Retrieved from http:// indicadores.agricultura.gov.br/saudeanimal/index.htm

Morettin, P. A., & Toloi C. M. C. (2006). Análise de series temporais (2a ed. rev. e ampl.). São Paulo: Edgard Blücher.

Nascimento, J. B. (2011). Tocantins: história e geografia (7a ed.). Goiânia: Bandeirante.

Nogueira, M. F., Oliveira, J. M., Santos, C. J. S., Petzold, H. V., Aguiar, D. M., Juliano, R. S.,... Abreu, U. G. P. (2017). Equine infectious anaemia in equids of Southern Pantanal, Brazil: seroprevalence and evaluation of the adoption of a control programme. Pesquisa Veterinária Brasileira, 37(3), 227-233.

Sax, C., & Eddelbuettel, D. (2018). Seasonal adjustment by X-13ARIMA-SEATS in R. Journal of Statistical Software, 87(11), 1-17. doi: 10.18637/jss.v087.i11

Van Der Kolk, J. H., & Kroeze, E. J. B. V. (2013). Infectious diseases of the horse: diagnosis, pathology, management, and public health. London: Mason Publishing.

Zeileis, A., Leisch, F., Hornik, K., & Kleiber, C. (2002). Strucchange: an R package for testing for structural change in linear regression models. Journal of Statistical Software, 7(2), 1-38. doi: 10.18637/jss.v007. i02




DOI: http://dx.doi.org/10.5433/1679-0359.2020v41n6Supl2p3145

Semina: Ciênc. Agrár.
Londrina - PR
E-ISSN 1679-0359
DOI: 10.5433/1679-0359
E-mail: semina.agrarias@uel.br
Este obra está licenciado com uma Licença Creative Commons Atribuição-NãoComercial 4.0 Internacional