A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil

INTRODUCTION: Forecasting dengue cases in a population by using time-series models can provide useful information that can be used to facilitate the planning of public health interventions. The objective of this article was to develop a forecasting model for dengue incidence in Campinas, southeast B...

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Bibliographic Details
Published in:Revista da Sociedade Brasileira de Medicina Tropical
Main Authors: Edson Zangiacomi Martinez, Elisângela Aparecida Soares da Silva, Amaury Lelis Dal Fabbro
Format: Article in Journal/Newspaper
Language:English
Published: Sociedade Brasileira de Medicina Tropical (SBMT) 2011
Subjects:
Dengue
SARIMA
Análise de séries temporais
Estatística
Arctic medicine. Tropical medicine
RC955-962
Arctic
Sarima
Online Access:https://doi.org/10.1590/S0037-86822011000400007
https://doaj.org/article/0f85ef2379f744d081ee35930ec16e73
Description
Summary:INTRODUCTION: Forecasting dengue cases in a population by using time-series models can provide useful information that can be used to facilitate the planning of public health interventions. The objective of this article was to develop a forecasting model for dengue incidence in Campinas, southeast Brazil, considering the Box-Jenkins modeling approach. METHODS: The forecasting model for dengue incidence was performed with R software using the seasonal autoregressive integrated moving average (SARIMA) model. We fitted a model based on the reported monthly incidence of dengue from 1998 to 2008, and we validated the model using the data collected between January and December of 2009. RESULTS: SARIMA (2,1,2) (1,1,1)12 was the model with the best fit for data. This model indicated that the number of dengue cases in a given month can be estimated by the number of dengue cases occurring one, two and twelve months prior. The predicted values for 2009 are relatively close to the observed values. CONCLUSIONS: The results of this article indicate that SARIMA models are useful tools for monitoring dengue incidence. We also observe that the SARIMA model is capable of representing with relative precision the number of cases in a next year.

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