Spatial analyses of typhoid fever in Jiangsu province, People's Republic of China.

An analysis of the geographical distribution of typhoid incidence rates, based on various statistical approaches such as trend surface, spatial autocorrelation, spatial correlation and spatial regression, was carried out at the county level in Jiangsu province, People's Republic of China. Temperature, moisture content, proximity to water bodies and the normalized difference vegetation index in the autumn were the four underlying factors found to contribute the most to the development of the epidemic. Typhoid infection was most severe in the south-eastern region of Jiangsu and a significant hotspot with high positive autocorrelation was detected in Taicang county in the south-east of the province. To improve the typhoid situation, intervention efforts should be concentrated in the south-eastern region of the province, targeting the hotspot and include reduction of lake pollution.

Geographical information systems-based spatial analysis and implications for syphilis interventions in Jiangsu province, People's Republic of China.

Spatial distribution rules and risk factors for syphilis were studied in Jiangsu province, People's Republic of China during 2005 and 2009. Trend surface analysis, spatial autocorrelation analysis and spatio-temporal clustering were applied with the incidence rates of the various counties in the province to determine spatial distribution rules and risk factors. Syphilis was found to be most severe in the southern region of the province where many counties could be shown to be hotspots with positive autocorrelation. Clusters were detected in the south-western region of Jiangsu with the county-level city of Yixing as the centre. Temperature, distance from railways and highways, and the normalised difference vegetation index were determined as supporting variables with regard to the transmission of the disease by both univariate and multivariate spatial correlation analyses. Interventions, including health education and awareness campaigns, should be strengthened throughout the province targeting the south-western areas, especially the clusters and hotspots detected in order to improve the situation.

Spatial distribution of HIV/AIDS in Yunnan province, People's Republic of China.

Risk maps for the geographical distribution of human immunodeficiency virus (HIV) and the acquired immune deficiency syndrome (AIDS) are needed for the direction of HIV prevention interventions. Our study, based on county-level data on the numbers of HIV/AIDS patients in the Yunnan province, People's Republic of China, applied trend surface analysis and spatial autocorrelation analysis to demonstrate the geographical distribution of HIV-positive patients in the province. The case load of HIV was found to be most severe in the central-west region of the province. While Kunming county was shown to be negatively correlated with its surrounding counties, many high-burden counties are surrounded by other counties with similar case numbers. We conclude that intervention efforts in Yunnan province should concentrate on the western and northeast regions, targeting the hotspots of infection.

[Study on the spatial distribution of AIDS based on geographic information system in Jiangsu province].

OBJECTIVE: To analyze the spatial distribution of AIDS in every city of Jiangsu province, trying to describe the geographic characteristics of AIDS and to develop a prediction model. METHODS: Numbers of patients in Jiangsu province were collected, to establish the database for the geographic information system, then setting up a 'risk map' of the disease. Spatial, autocorrelation. Linear spatial analyses were used to study the patients' numbers. RESULTS: (1) Results from the autocorrelation analysis showed that the distribution of AIDS was clustered at some places and was at random on the whole. The results also indicated that the distribution of AIDS in Nanjing was of negative correlation, while that in Suzhou and Wuxi were of positive correlation but in Tongshan, Wujiang, Pukou, Nanjing, Lishui, Wuxi and Suzhou showed seven locations of clusters with significantly higher numbers of patients. (2) The trend of 'surface analysis map' indicated that the disease was more severe in the southern than in the northern parts of Jiangsu province. (3) Ordinary Least Squares method was finally used in the linear spatial regression and the results were: t = -1.045 103 (P = 0.299 904); t = -1.443 668 (P = 0.153 714) respectively. CONCLUSION: According to the feature spatial distribution of the disease, effective measures should be taken to prevent and to keep the prevalence of AIDS under control.