Risk analysis of dengue fever occurrence in bone province sulawesi south using temporal spatial geostatistical model

Abstract

The purpose of this research is to get the best model prediction of dengue fever risk in Bone District using spatial temporal geostatistical model. Time series model is used to describe the dynamics of dengue fever changes with stages: Identification of data, Model identification, model estimation, model assumption check, best model selection and forecasting stage. Implementation of time series model in Bone District incident data and climatic factors shows that the model obtained has a good accuracy. The results showed that: The prediction model of dengue fever occurrence in Tanete Riattang Barat, China, and Mare sub district using ARIMAX model. Dengue prediction model for Ajangale District, Barebbo, Bengo, Two Boccoe and Tellusiattingge using MAX model. Rainfall is an exogenous variable that affects the incidence of dengue fever. Humidity, temperature and wind speed have no effect on the occurrence of dengue fever.

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