Prediction of visceral leishmaniasis incidence using the Seasonal Autoregressive Integrated Moving Average model (SARIMA) in the state of Maranhão, Brazil

• Autor(a) principal: Pimentel, K. B. A
• Data de Publicação: 2023
• Outros Autores: Oliveira, R. S, Aragão, Carine Fortes, Aquino Júnior, José, Moura, M. E. S, Silva, A. S. Guimarães e, Pinheiro, Valeria Cristina S, Gonçalves, E. G. R, Silva, A. R
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Digital do Instituto Evandro Chagas (Patuá)
• Texto Completo: https://patua.iec.gov.br/handle/iec/6734
• topic: Leishmaniose Visceral / parasitologia; Incidência; Média Móvel Integrada Autocorrelacionada Sazonal / métodos; Estudos de Séries Temporais; Maranhão (MA)

Visceral leishmaniasis (VL) is an infectious disease predominant in countries located in the tropics. The prediction of occurrence of infectious diseases through epidemiologic modeling has revealed to be an important tool in the understanding of its occurrence dynamic. The objective of this study was to develop a forecasting model for the incidence of VL in Maranhão using the Seasonal Autoregressive Integrated Moving Average model (SARIMA). We collected monthly data regarding VL cases from the National Disease Notification System (SINAN) corresponding to the period between 2001 and 2018. The Box‑Jenkins method was applied in order to adjust a SARIMA prediction model for VL general incidence and by sex (male or female) for the period between January 2019 and December 2013. For 216 months of this time series, 10,431 cases of VL were notified in Maranhão, with an average of 579 cases per year. With regard to age range, there was a higher incidence among the pediatric public (0 to 14 years of age). There was a predominance in male cases, 6437 (61.71%). The Box‑Pierce test figures for overall, male and female genders supported by the results of the Ljung‑Box test suggest that the autocorrelations of residual values act as white noise. Regarding monthly occurrences in general and by gender, the SARIMA models (2,0,0) (2,0,0), (0,1,1) (0,1,1) and (0,1,1) (2, 0, 0) were the ones that mostly adjusted to the data respectively. The model SARIMA has proven to be an adequate tool for predicting and analyzing the trends in VL incidence in Maranhão. The time variation determination and its prediction are decisive in providing guidance in health measure intervention.