OBJECTIVES: To perform GIS spatial analysis on malaria transmission patterns in Jiangsu after setting up a malaria database and developing GIS model of malaria transmission in Jiangsu province. METHODS: The epidemiological GIS database of malaria in Jiangsu province was established using ArcView 3.0a software. The climate data covering Jiangsu province and its peripheral area were extracted from the FAOCLIM database, the total growing degree days (TGDD) for Plasmodium vivax were calculated, and spatial distribution for TGDD was analyzed by ArcVeiw 3.0a. RESULTS: The predicted malaria distribution map based on TGDD was created, which showed that the transmission of malaria decreased gradually from west to east, which can be divided into three belts according to the degree of transmission. The 14-year mean morbidity distribution map of malaria in Jiangsu showed that the middle and west parts of Jiangsu is the most serious endemic area. The morbidity in the areas along the Taihu valley, such as Suzhou, Wuxi and Changzhou, as well as Nantong and a few of northern counties are the lowest. The morbidity of other places is at the middle level. The 14-year mean morbidity distribution map of malaria is correlated with predicted malaria distribution map for TGDD. CONCLUSION: It is possible to monitor the malaria transmission by GIS predicted model based on TGDD.
OBJECTIVES: To perform GIS spatial analysis on malaria transmission patterns in Jiangsu after setting up a malaria database and developing GIS model of malaria transmission in Jiangsu province. METHODS: The epidemiological GIS database of malaria in Jiangsu province was established using ArcView 3.0a software. The climate data covering Jiangsu province and its peripheral area were extracted from the FAOCLIM database, the total growing degree days (TGDD) for Plasmodium vivax were calculated, and spatial distribution for TGDD was analyzed by ArcVeiw 3.0a. RESULTS: The predicted malaria distribution map based on TGDD was created, which showed that the transmission of malaria decreased gradually from west to east, which can be divided into three belts according to the degree of transmission. The 14-year mean morbidity distribution map of malaria in Jiangsu showed that the middle and west parts of Jiangsu is the most serious endemic area. The morbidity in the areas along the Taihu valley, such as Suzhou, Wuxi and Changzhou, as well as Nantong and a few of northern counties are the lowest. The morbidity of other places is at the middle level. The 14-year mean morbidity distribution map of malaria is correlated with predicted malaria distribution map for TGDD. CONCLUSION: It is possible to monitor the malaria transmission by GIS predicted model based on TGDD.