Time series modelling of diabetes disease in Taraba State, Nigeria

Abstract

In this study, we applied an Autoregressive Integrated Moving Average (ARIMA) model to predict the spread of Diabetes disease infection in Taraba State, Nigeria. The monthly recorded cases of Diabetes between January 2010 and December 2020 in Federal Medical Centre, Jalingo was used to fit and validate the ARIMA model. A seasonal fluctuation and a slightly increasing pattern of a long-term trend were revealed in the time series of Diabetes disease. ARIMA (0,1,1) was selected as the best optimal model which has the lowest value of AIC/BIC. The root mean square error (RMSE) was used to assessed the predictive capability of the optimal model. The twenty-four (24) months forecast of Diabetes disease infection in Taraba State, Nigeria was also presented. The ARIMA model could be applied to effectively predict the short-term Diabetes disease infections in Taraba State, Nigeria and provide support for the development of interventions for disease control and prevention.