Marcos Venicius Malveira de Lima1,2, Gabriel Zorello Laporta1. 1. Centro Universitário Saúde ABC, Faculdade de Medicina, Santo André, SP, Brasil. 2. Secretaria de Estado de Saúde do Acre, Diretoria de Ações Programáticas e Vigilância em Saúde, Rio Branco, AC, Brasil.
Abstract
OBJECTIVE: To evaluate the predictive power of different malaria case time-series models in the state of Amapá, Brazil, for the period 1997-2016. METHODS: This is an ecological time series study with malaria cases recorded in the state of Amapá. Ten 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. It was possible to predict future malaria cases 6 and 12 months in advance. CONCLUSION: The ARIMA model is recommended for predicting future scenarios and for earlier planning in state health services in the Amazon Region.
OBJECTIVE: To evaluate the predictive power of different malaria case time-series models in the state of Amapá, Brazil, for the period 1997-2016. METHODS: This is an ecological time series study with malaria cases recorded in the state of Amapá. Ten 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. It was possible to predict future malaria cases 6 and 12 months in advance. CONCLUSION: The ARIMA model is recommended for predicting future scenarios and for earlier planning in state health services in the Amazon Region.
Authors: Klauss Kleydmann Sabino Garcia; Amanda Amaral Abrahão; Ana Flávia de Morais Oliveira; Karina Medeiros de Deus Henriques; Anielle de Pina-Costa; André Machado Siqueira; Walter Massa Ramalho Journal: Malar J Date: 2022-05-31 Impact factor: 3.469
Authors: João L Ferrão; Dominique Earland; Anísio Novela; Roberto Mendes; Alberto Tungadza; Kelly M Searle Journal: Int J Environ Res Public Health Date: 2021-05-26 Impact factor: 3.390