ANOPHELES MOSQUITO DENSITY PREDICTIVE MODEL USING REMOTELY SENSED DATA

Malaria cases and its consequent deaths have been predominant unsolved public health issues in Thailand. Malaria transmits through three possible mediums; malaria parasite, human hosts, and Anopheles mosquito. One possible way to solve the malaria problem is to have intervention on any of these mediums. This study focuses on Anopheles mosquito medium, a part of the malaria transmission cycle. As the malaria control methods depend on many setting-specific factors such as endemic, vector species and behavior, seasonality, disease patterns, health service factors and more, which they have not been distributed equally in spatial, therefore the accuracy of these predicted information at timely manner are necessary requirements for effective malaria control planning and preparations. Thus, increasing of spatial accuracy and information updates on the vector density are the main issues for the malaria control. In order to support these requirements, Geo-informatics technology is used to develop the model for predicting Anopheles mosquitoes, which is called “Anopheles Mosquito Density Predictive Model (AMDP model)”.