Study On Malaria Prevalent Tendency Based On 3S Technology In Tropical Area Of Yunnan Province, China

Malaria is one of the most serious parasitic diseases in the world. It usually occurs in the countries and areas locating in tropical and subtropical zones, and becomes their main public health problem of the developing countries. Yunnan province is the major malaria prevalent area in China. Yunnan was ranked the first for its malaria cases and second for its malaria incidence in recent ten years in China. Among more than 20 infectious diseases in Yunnan province, malaria is always listed on the top four infectious diseases with highest incidence. This research was accomplished in Mengla county of Xishuangbanna prefecture with a tropical and subtropical climate. We carried out the following studies using the remote sensing (RS), geographic information system (GIS) and global position system (GPS) technology.(1) RS image classification and information derivation of mosquito habitats. We established the RS classification system of mosquito habitats in Mengla county according to the land usage and cover condition, and the main malaria vector. We derived the mosquito habitat RS classification results by correcting, amplifying and classifying the Landsat 7 ETM+ images using the ERDAS 8.5 software. We derived the NDVI value from RS image based on RS model as well. The range of average NDVI value for 13 township resident buffers (buffer radius = 3 km ) is from 152 to 179 based on our RS model and the residents vector map of Mengla county.(2) Establishing the malaria epidemic information database for Mengla county. Our database is composed of three parts: basic geographic information, RS thematic information and malaria specific information. The geDgraphic information software Arc View 3.2 can support us for data entering, data management, information display and spatial analysis etc. These data can provide multi-information for malaria analysis and field control in Mengla county.(3) Analysis of mosquito habitats and malaria incidence. We analyzed mosquito habitats of three different incidence townships. The result was the more an area percentage of plant and water, the higher of malaria incidence.(4) Correlation between the malaria occurrence and NDVI value. We analyzed the correlation between the average NDVI from 13 townships of Mengla and their malaria incidence from 1999 to 2003 using the software SPSS 10.0, and found out their relationship is significant.(5) Application of GIS mapping in analyzing the malaria prevalence tendency of Yunnan Province. By studying the malaria epidemic tendency from 1991 to 2001 in Yunnan with GIS mapping function, we provided a direct and clear map interface for the epidemiological analysis of the temporal and spatial distribution and the changing tendency of malaria occurrence in successive years in whole province.