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A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil.
Rev Soc Bras Med Trop. 2011 Jul-Aug; 44(4):436-40.RS

Abstract

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.

Authors+Show Affiliations

Departamento de Medicina Social, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brasil.No affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

21860888

Citation

Martinez, Edson Zangiacomi, et al. "A SARIMA Forecasting Model to Predict the Number of Cases of Dengue in Campinas, State of São Paulo, Brazil." Revista Da Sociedade Brasileira De Medicina Tropical, vol. 44, no. 4, 2011, pp. 436-40.
Martinez EZ, Silva EA, Fabbro AL. A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil. Rev Soc Bras Med Trop. 2011;44(4):436-40.
Martinez, E. Z., Silva, E. A., & Fabbro, A. L. (2011). A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil. Revista Da Sociedade Brasileira De Medicina Tropical, 44(4), 436-40.
Martinez EZ, Silva EA, Fabbro AL. A SARIMA Forecasting Model to Predict the Number of Cases of Dengue in Campinas, State of São Paulo, Brazil. Rev Soc Bras Med Trop. 2011 Jul-Aug;44(4):436-40. PubMed PMID: 21860888.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil. AU - Martinez,Edson Zangiacomi, AU - Silva,Elisângela Aparecida Soares da, AU - Fabbro,Amaury Lelis Dal, PY - 2010/06/29/received PY - 2011/02/11/accepted PY - 2011/8/24/entrez PY - 2011/8/24/pubmed PY - 2012/2/4/medline SP - 436 EP - 40 JF - Revista da Sociedade Brasileira de Medicina Tropical JO - Rev. Soc. Bras. Med. Trop. VL - 44 IS - 4 N2 - 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. SN - 1678-9849 UR - https://www.unboundmedicine.com/medline/citation/21860888/A_SARIMA_forecasting_model_to_predict_the_number_of_cases_of_dengue_in_Campinas_State_of_São_Paulo_Brazil_ L2 - http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822011000400007&lng=en&nrm=iso&tlng=en DB - PRIME DP - Unbound Medicine ER -
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