UMA COMPARAÇÃO DOS MODELOS SARIMA E ESTRUTURAIS PARA A PREVISÃO DA INCIDÊNCIA DE DENGUE EM BELO HORIZONTE, MINAS GERAIS - SANTOS, Thiago Rezende dos (Brazilian Journal of Biometrics, 2017)
Forecasts for dengue incidence are essentials for public policies and actions, providing to health managers monthly estimates of the number of new cases in order that they can, for example, plan and organize strategies, health teams, etc. This paper provides forecasts of the future values of dengue incidence in Belo Horizonte, Brazil, based on Seasonal Autoregressive Integrated Moving Average (SARIMA) models and Structural Models (SM), comparing them with respect to their fit and out-of-sample forecasts. In general, forecasts via the SM had a better performance than the SARIMA ones, according to the forecast error statistics. Furthermore, as the SM decomposes the time series in terms of its unobservable components; the behavior of the trend component of dengue incidence may be studied over time. This component decreases between 2002 and 2005 and increases after 2005. The months of the highest and lowest incidence can also be identified through the seasonality component. The first months of year have a high incidence, which was already expected. The results are very satisfactory and motivate future studies.