Forecasting Model for Dengue Morbidity Rate in Thailand

Abstract

Dengue infectious is recognized as major health problem and the spread of dengue was found in many countries, especially in tropical and subtropical regions. The mortality rate and morbidity rate have been dramatically increasing in last decade. The mathematical model were now used for explaining the future trends of disease, as the early warning system. It can provide useful information leading to timely decision making process regarding prevention and control planning and intervention strategies in order to reduce the burden of disease. The ARIMA model is famously used to explain the epidemiology of disease. Therefore, the aim of this study was to develop the ARIMA model for explaining dengue morbidity rate. The Average temperature and relative humidity were included in the model. The historical data such as dengue morbidity rate, average temperature and relative humidity in Thailand from 2006–2015 were used in analysis. The result found that ARIMA $\pmb{(3,0,1)_{12}}$ adjusted with average temperature and relative humidity was the optimal model to describe dengue morbidity rate. It had the smallest Al (554.21) and RMSE (0.652).