HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Luz, P. M. Articles by Galvani, A. P. Search for Related Content PubMed Articles by Luz, P. M. Articles by Galvani, A. P.

Time Series Analysis of Dengue Incidence in Rio de Janeiro, Brazil

We use the Box-Jenkins approach to fit an autoregressive integrated moving average (ARIMA) model to dengue incidence in Rio de Janeiro, Brazil, from 1997 to 2004. We find that the number of dengue cases in a month can be estimated by the number of dengue cases occurring one, two, and twelve months prior. We use our fitted model to predict dengue incidence for the year 2005 when two alternative approaches are used: 12-steps ahead versus 1-step ahead. Our calculations show that the 1-step ahead approach for predicting dengue incidence provides significantly more accurate predictions (P value = 0.002, Wilcoxon signed-ranks test) than the 12-steps ahead approach. We also explore the predictive power of alternative ARIMA models incorporating climate variables as external regressors. Our findings indicate that ARIMA models are useful tools for monitoring dengue incidence in Rio de Janeiro. Furthermore, these models can be applied to surveillance data for predicting trends in dengue incidence.

Received October 26, 2007. Accepted for publication August 4, 2008.

Acknowledgments: We thank the reviewers for their relevant comments, and Kristina Talbert-Slagle and Angie Hofmann for editing the revision.

Financial support: P. M. Luz was funded by the Brazilian Government (CAPES), Fulbright, Notsew Orm Sands Foundation, and Garfield Weston. V. M. Mendes received financial support from the Brazilian Government (CNPq) and COPPEAD/UFRJ. C. T. Codeço was partially funded by FIOCRUZ (PDTSP-Dengue). C. J. Struchiner was partially funded by CNPq and FAPERJ. A. P. Galvani acknowledges funding from the Notsew Orm Sands Foundation and Garfield Weston.

^* Address correspondence to Paula M. Luz, Department of Epidemiology and Public Health, Yale University, 60 College Street, New Haven, CT 06511. E-mail: paula.luz{at}yale.edu

Authors’ addresses: Paula M. Luz, Department of Epidemiology and Public Health, Yale University, 60 College Street, New Haven, CT 06511, Tel: 203-777-4671, E-mail: paula.luz{at}yale.edu. Beatriz V. M. Mendes, Institute of Mathematics/COPPEAD, Rio de Janeiro Federal University, Av. Brigadeiro Trompovisk, Ilha do Fundão, Rio de Janeiro, RJ, Brazil 22221-080, Tel: 55-21-25627910, Fax: 55-21-25901095, E-mail: beatriz{at}im.ufrj.br. Claudia T. Codeço, Program for Scientific Computing, Oswaldo Cruz Foundation, Av. Brasil 4365, Manguinhos, Rio de Janeiro, RJ, Brazil 21040-360, Tel: 55-21-3836-1100, E-mail: codeco{at}fiocruz.br. Claudio J. Struchiner, Program for Scientific Computing, Oswaldo Cruz Foundation, Av. Brasil 4365, Manguinhos, Rio de Janeiro, RJ, Brazil 21040-360, Tel: 55-21-3836-1109, E-mail: stru{at}fiocruz.br. Alison P. Galvani, Department of Epidemiology and Public Health, Yale University, 60 College St., New Haven, CT 06511, Tel: 203-785-2642, E-mail: alison.galvani{at}yale.edu.