Evaluation of prediction models for the occurrence of malaria in the state of Amapá, Brazil, 1997-2016: an ecological study

Abstract

Objective. To evaluate predictive power of different time-series models of malaria cases in the state of Amapá, Brazil, in the period 1997-2016. Methods. This is an ecological study of time series with malaria cases registered in the state of Amapá. Ten 3 deterministic or stochastic statistical models were used for simulation and testing in 3, 6, and 12 month forecast horizons. Results. The initial test showed that the series is stationary. Deterministic models performed better than stochastic models. The ARIMA model showed absolute errors of less than 2% on the logarithmic scale and relative errors 3.4-5.8 times less than the null model. The prediction of future cases of malaria in the horizons of 6 and 12 months in advance was possible. Conclusion. It is recommended the use of the ARIMA model to predict future scenarios and to anticipate planning in state health services in the Amazon Region.