A Bayesian Spatio Temporal for Forecasting of Infectious Diseases by Means CAR Bayes

Abstract

The development model for forecasting purpose in disease mapping is a very necessity. We not only
need the pattern of spread of the disease but also require a predictive value relative risk figures for each location
in the next period. This is necessary as a preventive measure for prevention of this disease provide a greater
negative impact. This research focus to develop a forecasting model in disease mapping by means CAR Bayes.
We applied our method to the dengue fever disease in Bandung city. We found that the humidity and larvae free
rate have a big effect on the relative risk. The forecasting result follows time trend which every mount the relative
risk increase.
Keyword: CAR Bayes, disease mapping, spatio temporal.