Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019

Detalhes bibliográficos
Autor(a) principal: Morais, Petrúcio Luiz Lins de
Data de Publicação: 2020
Outros Autores: Castanha, Priscila Mayrelle Silva, Nascimento, Gabriela Isabel Limoeiro Alves, Montarroyos, Ulisses Ramos
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/11138
Resumo: In the last five years, the number of Dengue cases has been growing sharply in the city of Garanhuns. The objective of this study was to determine an analysis of the time series of Dengue cases in the medium-sized municipality, associated with climatic factors that contribute to the occurrence of this disease with forecasts, thus facilitating better control and prevention. Methodology: The autoregressive model of seasonal moving averages with exogenous variables (SARIMAX) was applied, which is a linear regression model that involves a process of the SARIMA model. In addition to the graphical analysis of the decomposition of time series, the Dickey-Fuller test was used to assess the stationarity of the series. Considering the seasonal behavior and the non-stationarity of the time series, the adjusted model had as parameters the SARIMA model (p, d, q) (P, D, Q), applying the Akaike Information Criterion (AIC) to select the best model, using the software R. Result: Considering the seasonal component and the non-stationarity of the time series, the model with the best adjustment was SARIMA (0,1,3) (0.1.1), a significance level of 5% (p-value = 0, 01). The SARIMAX model (0, 1, 3) (0,1,1) plus the effect of temperature and humidity were adequate to report the incidence of Dengue. In the correlation, the increase in the temperature component was greater than the humidity in the number of Dengue cases.
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spelling Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019Análisis temporal del dengue asociado a factores climáticos en Garanhuns, Pernambuco, Brasil, de 2010 a 2019Análise temporal da dengue associada a fatores climáticos em Garanhuns, Pernambuco, Brasil, de 2010 a 2019IncidenciaDengueEstacionalidadEpidemiaPrevención.IncidênciaDengueSazonalidadeEpidemiaPrevenção.IncidenceDengueSeasonalityEpidemicPrevention.In the last five years, the number of Dengue cases has been growing sharply in the city of Garanhuns. The objective of this study was to determine an analysis of the time series of Dengue cases in the medium-sized municipality, associated with climatic factors that contribute to the occurrence of this disease with forecasts, thus facilitating better control and prevention. Methodology: The autoregressive model of seasonal moving averages with exogenous variables (SARIMAX) was applied, which is a linear regression model that involves a process of the SARIMA model. In addition to the graphical analysis of the decomposition of time series, the Dickey-Fuller test was used to assess the stationarity of the series. Considering the seasonal behavior and the non-stationarity of the time series, the adjusted model had as parameters the SARIMA model (p, d, q) (P, D, Q), applying the Akaike Information Criterion (AIC) to select the best model, using the software R. Result: Considering the seasonal component and the non-stationarity of the time series, the model with the best adjustment was SARIMA (0,1,3) (0.1.1), a significance level of 5% (p-value = 0, 01). The SARIMAX model (0, 1, 3) (0,1,1) plus the effect of temperature and humidity were adequate to report the incidence of Dengue. In the correlation, the increase in the temperature component was greater than the humidity in the number of Dengue cases.En los últimos cinco años, el número de casos de dengue ha aumentado considerablemente en la ciudad de Garanhuns (Pernambuco). El objetivo de este estudio fue determinar un análisis de series de tiempo de casos de Dengue en el municipio de tamaño mediano, asociados a factores climáticos que contribuyen a la ocurrencia de esta enfermedad con pronósticos, facilitando así un mejor control y prevención de la contaminación. Metodología: Se aplicó el modelo autorregresivo de promedios móviles estacionales con variables exógenas (SARIMAX), un modelo de regresión lineal que involucra un proceso del modelo SARIMA. Además del análisis gráfico de la descomposición de series temporales, se utilizó la prueba de Dickey-Fuller para evaluar la estacionariedad de la serie. Considerando el comportamiento estacional y la no estacionariedad de la serie temporal, el modelo ajustado tuvo como parámetro el modelo SARIMA (p, d, q) (P, D, Q), aplicando el criterio de Información de Akaike (AIC) para seleccionar el mejor modelo, utilizando el software R Resultado: Considerando el componente estacional y la no estacionariedad de la serie temporal, el modelo con mejor ajuste fue SARIMA (0.1.3) (0.1.1), nivel de significancia del 5% ( valor -p = 0,01). El modelo SARIMAX (0, 1, 3) (0, 1, 1) más el efecto de la temperatura y la humedad fueron adecuados para reportar la incidencia de Dengue. En la correlación, el incremento en el componente de temperatura fue mayor que la humedad en el número de casos de Dengue.Nos últimos cinco anos, o número de casos de Dengue vem crescendo acentuadamente na cidade de Garanhuns (Pernambuco). O objetivo deste estudo foi determinar uma análise de séries temporais de casos de Dengue no município de médio porte, associadas a fatores climáticos que contribuem para a ocorrência dessa doença com previsões, facilitando assim um melhor controle e prevenção de contaminações. Metodologia: Foi aplicado o modelo autorregressivo de médias móveis sazonais com variáveis exógenas (SARIMAX) - modelo de regressão linear que envolve um processo do modelo SARIMA. Além da análise gráfica da decomposição das séries temporais, foi utilizado o teste de Dickey-Fuller para avaliar a estacionariedade das séries. Considerando o comportamento sazonal e a não estacionariedade das séries temporais, o modelo ajustado teve como parâmetro o modelo SARIMA (p, d, q) (P, D, Q), sendo aplicado o critério Akaike Information (AIC) para a seleção do melhor modelo, utilizando o software R Resultado: Considerando o componente sazonal e a não estacionariedade das séries temporais, o modelo com melhor ajuste foi o SARIMA (0,1,3) (0,1,1), nível de significância de 5% (p-valor = 0,01). O modelo SARIMAX (0, 1, 3) (0, 1, 1) mais o efeito da temperatura e da umidade foram adequados para relatar a incidência de Dengue. Na correlação, o incremento do componente temperatura foi maior do que a umidade no número de casos de Dengue.Research, Society and Development2020-12-20info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1113810.33448/rsd-v9i12.11138Research, Society and Development; Vol. 9 No. 12; e22891211138Research, Society and Development; Vol. 9 Núm. 12; e22891211138Research, Society and Development; v. 9 n. 12; e228912111382525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/11138/9860Copyright (c) 2020 Petrúcio Luiz Lins de Morais; Priscila Mayrelle Silva Castanha; Gabriela Isabel Limoeiro Alves Nascimento; Ulisses Ramos Montarroyoshttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessMorais, Petrúcio Luiz Lins deCastanha, Priscila Mayrelle SilvaNascimento, Gabriela Isabel Limoeiro AlvesMontarroyos, Ulisses Ramos2020-12-30T23:32:22Zoai:ojs.pkp.sfu.ca:article/11138Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:33:02.772679Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019
Análisis temporal del dengue asociado a factores climáticos en Garanhuns, Pernambuco, Brasil, de 2010 a 2019
Análise temporal da dengue associada a fatores climáticos em Garanhuns, Pernambuco, Brasil, de 2010 a 2019
title Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019
spellingShingle Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019
Morais, Petrúcio Luiz Lins de
Incidencia
Dengue
Estacionalidad
Epidemia
Prevención.
Incidência
Dengue
Sazonalidade
Epidemia
Prevenção.
Incidence
Dengue
Seasonality
Epidemic
Prevention.
title_short Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019
title_full Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019
title_fullStr Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019
title_full_unstemmed Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019
title_sort Temporal analysis of dengue associated with climatic factors in Garanhuns, Pernambuco, Brazil, from 2010 to 2019
author Morais, Petrúcio Luiz Lins de
author_facet Morais, Petrúcio Luiz Lins de
Castanha, Priscila Mayrelle Silva
Nascimento, Gabriela Isabel Limoeiro Alves
Montarroyos, Ulisses Ramos
author_role author
author2 Castanha, Priscila Mayrelle Silva
Nascimento, Gabriela Isabel Limoeiro Alves
Montarroyos, Ulisses Ramos
author2_role author
author
author
dc.contributor.author.fl_str_mv Morais, Petrúcio Luiz Lins de
Castanha, Priscila Mayrelle Silva
Nascimento, Gabriela Isabel Limoeiro Alves
Montarroyos, Ulisses Ramos
dc.subject.por.fl_str_mv Incidencia
Dengue
Estacionalidad
Epidemia
Prevención.
Incidência
Dengue
Sazonalidade
Epidemia
Prevenção.
Incidence
Dengue
Seasonality
Epidemic
Prevention.
topic Incidencia
Dengue
Estacionalidad
Epidemia
Prevención.
Incidência
Dengue
Sazonalidade
Epidemia
Prevenção.
Incidence
Dengue
Seasonality
Epidemic
Prevention.
description In the last five years, the number of Dengue cases has been growing sharply in the city of Garanhuns. The objective of this study was to determine an analysis of the time series of Dengue cases in the medium-sized municipality, associated with climatic factors that contribute to the occurrence of this disease with forecasts, thus facilitating better control and prevention. Methodology: The autoregressive model of seasonal moving averages with exogenous variables (SARIMAX) was applied, which is a linear regression model that involves a process of the SARIMA model. In addition to the graphical analysis of the decomposition of time series, the Dickey-Fuller test was used to assess the stationarity of the series. Considering the seasonal behavior and the non-stationarity of the time series, the adjusted model had as parameters the SARIMA model (p, d, q) (P, D, Q), applying the Akaike Information Criterion (AIC) to select the best model, using the software R. Result: Considering the seasonal component and the non-stationarity of the time series, the model with the best adjustment was SARIMA (0,1,3) (0.1.1), a significance level of 5% (p-value = 0, 01). The SARIMAX model (0, 1, 3) (0,1,1) plus the effect of temperature and humidity were adequate to report the incidence of Dengue. In the correlation, the increase in the temperature component was greater than the humidity in the number of Dengue cases.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-20
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://rsdjournal.org/index.php/rsd/article/view/11138
10.33448/rsd-v9i12.11138
url https://rsdjournal.org/index.php/rsd/article/view/11138
identifier_str_mv 10.33448/rsd-v9i12.11138
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/11138/9860
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 9 No. 12; e22891211138
Research, Society and Development; Vol. 9 Núm. 12; e22891211138
Research, Society and Development; v. 9 n. 12; e22891211138
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
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