Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA model

Detalhes bibliográficos
Autor(a) principal: Martinez, Edson Zangiacomi
Data de Publicação: 2011
Outros Autores: Silva, Elisângela Aparecida Soares da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Cadernos de Saúde Pública
Texto Completo: https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/4516
Resumo: This study aimed to develop a forecasting model for the incidence of dengue in Ribeirão Preto, São Paulo State, Brazil, using time series analysis. The model was performed using the Seasonal Autoregressive Integrated Moving Average (SARIMA). Firstly, we fitted a model considering monthly notifications of cases of dengue recorded from 2000 to 2008 in Ribeirão Preto. We then extracted predicted values for 2009 from the adjusted model and compared them with the number of cases observed for that year. The SARIMA (2,1,3)(1,1,1)12 model offered best fit for the dengue incidence data. The results showed that the seasonal ARIMA model predicts the number of dengue cases very effectively and reliably, and is a useful tool for disease control and prevention.
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spelling Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA modelDengueForecastingBrostatisticsThis study aimed to develop a forecasting model for the incidence of dengue in Ribeirão Preto, São Paulo State, Brazil, using time series analysis. The model was performed using the Seasonal Autoregressive Integrated Moving Average (SARIMA). Firstly, we fitted a model considering monthly notifications of cases of dengue recorded from 2000 to 2008 in Ribeirão Preto. We then extracted predicted values for 2009 from the adjusted model and compared them with the number of cases observed for that year. The SARIMA (2,1,3)(1,1,1)12 model offered best fit for the dengue incidence data. The results showed that the seasonal ARIMA model predicts the number of dengue cases very effectively and reliably, and is a useful tool for disease control and prevention.Este estudo tem por objetivo desenvolver um modelo para a predição do número de casos de dengue em Ribeirão Preto, São Paulo, Brasil, por técnicas de análise de séries temporais. Para isto, foi utilizado o modelo SARIMA (Seasonal Autoregressive Integrated Moving Average). Inicialmente, ajustamos um modelo considerando o número mensal de casos notificados de dengue entre os anos 2000 e 2008 em Ribeirão Preto. Em uma etapa seguinte, obtivemos, com base nesse modelo, valores preditos para 2009, os quais comparamos com os valores observados neste ano. O modelo SARIMA (2,1,3)(1,1,1)12 trouxe o melhor ajuste para os dados de incidência de dengue. Os resultados obtidos neste artigo mostram que o modelo SARIMA é bastante eficiente em descrever o número de casos de dengue no período em estudo e em predizer valores em meses futuros, mostrando-se uma útil ferramenta para estratégias de controle e prevenção da doença.Reports in Public HealthCadernos de Saúde Pública2011-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlapplication/pdfhttps://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/4516Reports in Public Health; Vol. 27 No. 9 (2011): SeptemberCadernos de Saúde Pública; v. 27 n. 9 (2011): Setembro1678-44640102-311Xreponame:Cadernos de Saúde Públicainstname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZenghttps://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/4516/9205https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/4516/9206Martinez, Edson ZangiacomiSilva, Elisângela Aparecida Soares dainfo:eu-repo/semantics/openAccess2024-03-06T15:28:14Zoai:ojs.teste-cadernos.ensp.fiocruz.br:article/4516Revistahttps://cadernos.ensp.fiocruz.br/ojs/index.php/csphttps://cadernos.ensp.fiocruz.br/ojs/index.php/csp/oaicadernos@ensp.fiocruz.br||cadernos@ensp.fiocruz.br1678-44640102-311Xopendoar:2024-03-06T13:05:12.577875Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ)true
dc.title.none.fl_str_mv Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA model
title Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA model
spellingShingle Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA model
Martinez, Edson Zangiacomi
Dengue
Forecasting
Brostatistics
title_short Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA model
title_full Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA model
title_fullStr Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA model
title_full_unstemmed Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA model
title_sort Predicting the number of cases of dengue infection in Ribeirão Preto, São Paulo State, Brazil, using a SARIMA model
author Martinez, Edson Zangiacomi
author_facet Martinez, Edson Zangiacomi
Silva, Elisângela Aparecida Soares da
author_role author
author2 Silva, Elisângela Aparecida Soares da
author2_role author
dc.contributor.author.fl_str_mv Martinez, Edson Zangiacomi
Silva, Elisângela Aparecida Soares da
dc.subject.por.fl_str_mv Dengue
Forecasting
Brostatistics
topic Dengue
Forecasting
Brostatistics
description This study aimed to develop a forecasting model for the incidence of dengue in Ribeirão Preto, São Paulo State, Brazil, using time series analysis. The model was performed using the Seasonal Autoregressive Integrated Moving Average (SARIMA). Firstly, we fitted a model considering monthly notifications of cases of dengue recorded from 2000 to 2008 in Ribeirão Preto. We then extracted predicted values for 2009 from the adjusted model and compared them with the number of cases observed for that year. The SARIMA (2,1,3)(1,1,1)12 model offered best fit for the dengue incidence data. The results showed that the seasonal ARIMA model predicts the number of dengue cases very effectively and reliably, and is a useful tool for disease control and prevention.
publishDate 2011
dc.date.none.fl_str_mv 2011-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/4516
url https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/4516
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/4516/9205
https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/4516/9206
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
application/pdf
dc.publisher.none.fl_str_mv Reports in Public Health
Cadernos de Saúde Pública
publisher.none.fl_str_mv Reports in Public Health
Cadernos de Saúde Pública
dc.source.none.fl_str_mv Reports in Public Health; Vol. 27 No. 9 (2011): September
Cadernos de Saúde Pública; v. 27 n. 9 (2011): Setembro
1678-4464
0102-311X
reponame:Cadernos de Saúde Pública
instname:Fundação Oswaldo Cruz (FIOCRUZ)
instacron:FIOCRUZ
instname_str Fundação Oswaldo Cruz (FIOCRUZ)
instacron_str FIOCRUZ
institution FIOCRUZ
reponame_str Cadernos de Saúde Pública
collection Cadernos de Saúde Pública
repository.name.fl_str_mv Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ)
repository.mail.fl_str_mv cadernos@ensp.fiocruz.br||cadernos@ensp.fiocruz.br
_version_ 1798943369000386560

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