DSpace Collection:https://repositorio.ufu.br/handle/123456789/177522026-09-26T16:49:58Z2026-09-26T16:49:58ZInfluência de variáveis climáticas defasadas na incidência de dengue em Uberlândia-mg: uma análise de séries temporaishttps://repositorio.ufu.br/handle/123456789/502612026-09-15T06:26:11Z2026-07-31T00:00:00ZTitle: Influência de variáveis climáticas defasadas na incidência de dengue em Uberlândia-mg: uma análise de séries temporais
Abstract: Dengue is an endemic disease in Brazil, and its transmission is associated with climatic condi
tions, particularly temperature and precipitation. This study aimed to analyze the historical
behavior of dengue cases in Uberlândia, Minas Gerais, Brazil, from January 2014 to April
2026, through SARIMA and SARIMAX time series models, evaluating the influence of time
lagged climatic variables. Case data were obtained from the Notifiable Diseases Information
System (SINAN), and climatic data on temperature and precipitation were obtained from the
NASA POWER platform. The methodology followed the Box-Jenkins approach, including a
trend test (Cox-Stuart) and a seasonality test (Fisher), logarithmic transformation to stabilize
variance, identification and estimation of SARIMA models, and subsequent incorporation of
lagged climatic exogenous variables, selected through cross-correlation function (CCF) analy
sis. The SARIMA(1,1,0)(1,1,1)12 model was selected as the reference model, presenting the
lowest information criterion values among the models with statistically significant coefficients.
The inclusion of temperature lagged by five months as an exogenous variable resulted in the
final SARIMAX model, which showed a lower AIC and a statistically significant coefficient,
evidencing an inverse association between temperature and the subsequent incidence of the
disease. Residual diagnostics indicated the absence of autocorrelation at the first lags, but sig
nificant residual autocorrelation at the longer seasonal lags, attributed to the atypical behavior
of the 2025 outbreak. Model validation was performed through rolling (one-step-ahead) fore
casting, given the atypical nature of that outbreak. The models proved to be complementary,
as SARIMA showed slightly higher predictive performance, while SARIMAX made it possible
to quantify the influence of temperature on dengue incidence. The results reinforce the poten
tial of climatic variables as a tool to support epidemiological surveillance and vector control
planning in the municipality.2026-07-31T00:00:00ZEfeito de diferentes dosagens do adubo orgânico à base de casca de maracujá na cultura da mandioca no Cerradohttps://repositorio.ufu.br/handle/123456789/501092026-09-04T06:31:37Z2026-03-04T00:00:00ZTitle: Efeito de diferentes dosagens do adubo orgânico à base de casca de maracujá na cultura da mandioca no Cerrado2026-03-04T00:00:00ZModelo preditivo do ciclo de colheita de sementes de milhohttps://repositorio.ufu.br/handle/123456789/498812026-08-28T06:19:43Z2026-08-05T00:00:00ZTitle: Modelo preditivo do ciclo de colheita de sementes de milho2026-08-05T00:00:00ZImpacto da COVID-19 na saúde cardiovascularhttps://repositorio.ufu.br/handle/123456789/497792026-08-25T06:22:31Z2026-08-07T00:00:00ZTitle: Impacto da COVID-19 na saúde cardiovascular2026-08-07T00:00:00Z