The objectives of this research are to estimate the morbidity rate of Dengue Hemorrhagic fever in each province of Thailand and to construct the map of the Dengue Hemorrhagic fever. A Bayesian model is used for the data analysis. The data are mathematical spatial correlated in the form of the conditional autoregressive model (CAR). The secondary data were collected at a provincial level. They were the number of Dengue Hemorrhagic fever patients rainfall and average temperature. The research found that the rainfall (RR = 1.0026) and the average temperature (RR = 1.2681) had influence on the morbidity of Dengue Hemorrhagic fever. The season during July to September had more influence on the morbidity of Dengue Hemorrhagic fever than during the other seasons. The top 5 highest morbidity rates per 100000 population were Chiangmai in October (1288.00) July (1096.00) September (804.30) Surin in October (772.30) and Nakhon Si Thammarat in August (666.20). The disease map constructed for showing the distribution of the disease is easy to understand and useful for public health.

The objectives of this research were to investigate risk factors for Dengue fever in Thailand and to select an appropriate model. The generalized estimating equation (GEE) whose dependent variable has a Poisson distribution and a negative binomial distribution were studied. The secondary data consisting of the number of Dengue fever patients rainfall average temperature forest area household income were collected. Regions and seasons were also considered. The research found that the GEE whose dependent variable has a negative binomial is more appropriate to be used for Dengue patient data analysis. Central region and the season during Feb-Apr were assigned to be reference groups. Risk factors for Dengue fever were rainfall (Relative Risk (RR) = 1.0009) average temperature (RR = 1.1736) forest area (RR = 1.0482) southern region (RR = 2.7390) eastern region (RR = 2.0489) western region (RR = 1.4051) the season during May-Jul (RR = 3.0526) and Aug-Oct (RR = 3.2677)