OBJECTIVE: To explore the spatial distribution character of dengue fever and the change of Aedes' population, so as to provide macroscopical decision-making evidences of prevention and supervision on dengue fever. METHODS: (1) Collecting data on morbidity of dengue and supervision on vector's population in the corresponding period. (2) Drawing digitized map of Chaozhou in scale of 1:50,000, including elements of boundary, residential areas, road and traffic, altitude, water systems etc. (3) Measuring the latitude and longitude of center position of surveillance safes on the scene. (4) Processing spatial analysis by the ArcGIS 8.5 software. RESULTS: Distribution of Aedes showed spatial cluster in Chaozhou, while its density was related to the distance to the watersides. The closer to the watersides, the higher the density was. Map on spatial distribution showed that although the Aedes epidemic situation changed yearly, but primarily be kept in high, middle, low regions. Cross-validation effects of the distribution maps were satisfactory. CONCLUSION: Geographic information system was promising in analyzing data on dengue fever, and better than other routine research methods.
OBJECTIVE: To explore the spatial distribution character of dengue fever and the change of Aedes' population, so as to provide macroscopical decision-making evidences of prevention and supervision on dengue fever. METHODS: (1) Collecting data on morbidity of dengue and supervision on vector's population in the corresponding period. (2) Drawing digitized map of Chaozhou in scale of 1:50,000, including elements of boundary, residential areas, road and traffic, altitude, water systems etc. (3) Measuring the latitude and longitude of center position of surveillance safes on the scene. (4) Processing spatial analysis by the ArcGIS 8.5 software. RESULTS: Distribution of Aedes showed spatial cluster in Chaozhou, while its density was related to the distance to the watersides. The closer to the watersides, the higher the density was. Map on spatial distribution showed that although the Aedes epidemic situation changed yearly, but primarily be kept in high, middle, low regions. Cross-validation effects of the distribution maps were satisfactory. CONCLUSION: Geographic information system was promising in analyzing data on dengue fever, and better than other routine research methods.