Using Google Trend data in forecasting number of dengue fever cases with ARIMAX method case study: Surabaya, Indonesia

摘要

Indonesia has the highest number of dengue fever cases in Southeast Asia. Early detection of the disease is required in order to be able to prepare preventive measures against dengue fever. Previous research has shown that certain query search related to communicable disease on Google Trends are highly correlated with number of communicable disease cases in South Korea. Based on previous research, Google Trends search index shows potential to be included as external variable in a multivariate quantitative forecasting model. Using time series model, the role of Google Trends on epidemiology of dengue fever transmissions in Surabaya will be analyzed. This research uses several data (1) Number of dengue fever cases obtained from general local hospital of Dr. Soetomo (2) Google Trends search index of certain queries related to dengue fever. All of the data spans from December 2010 - August 2015. Interpolation and extrapolation techniques are used to handle the missing data. ARIMA and ARIMAX model with Google Trends data are implemented in order to forecast the number of dengue fever cases. The research shows that the addition of Google Trends into ARIMAX model improves forecasting performance. The best ARIMAX with Google Trends model improves MAPE value by 3%.