Twenty villages in the Anning River Valley of southwestern Sichuan China were surveyed for Schistosoma japonicum infections in humans and domestic animals. Also surveyed were human water contact patterns, snail populations, cercarial risk in irrigation systems, and agricultural land use. Few animals were infected, while village prevalence of infection in humans ranged from 3% to 68% and average village eggs per gram of stool ranged from 0 to 110. Except for occupation and education, individual characteristics were not strong determinants of infection intensity within a village. Differences in human infection intensity between these villages are strongly associated with crop type, with low-intensity villages principally growing rice, in contrast to villages devoting more land to vegetables and tobacco. Cercarial risk in village irrigation systems is associated with snail density and human infection intensity through the use of manure-based fertilizer. Some of the agricultural and environmental factors associated with infection risk can be quantified using remote sensing technology.

Environmental effects on the transmission of many parasitic diseases are well recognized, but the role of specific factors like climate and agricultural practices in modulating transmission is seldom characterized quantitatively. Based on studies of Schistosoma japonicum transmission in irrigated agricultural environments in western China, a mathematical model was used to quantify environmental impacts on transmission intensity. The model was calibrated by using field data from intervention studies in three villages and simulated to predict the effects of alternative control options. Both the results of these interventions and earlier epidemiological findings confirm the central role of environmental factors, particularly those relating to snail habitat and agricultural and sanitation practices. Moreover, the findings indicate the inadequacy of current niclosamide-praziquantel strategies alone to achieve sustainable interruption of transmission in some endemic areas. More generally, the analysis suggests a village-specific index of transmission potential and how this potential is modulated by time-varying factors, including climatological variables, seasonal water-contact patterns, and irrigation practices. These time-variable factors, a village's internal potential, and its connectedness to its neighbors provide a framework for evaluating the likelihood of sustained schistosomiasis transmission and suggest an approach to quantifying the role of environmental factors for other parasitic diseases.disease control ͉ environment

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Despite considerable achievements in the control of schistosomiasis in China, it remains one of the country’s most serious public health problems. Geographic information systems and remote sensing provide new tools for better understanding the spatial epidemiology of disease transmission. We present applications of these technologies at both the regional and local scale. At the regional scale, we compare remote sensing approaches for mapping snail intermediate host habitat in the mountainous environment and the flood basins of the upper and lower Yangtze River, respectively. At the local scale, we present the use of global positioning systems and geocoding of routinely collected field data. High-resolution IKONOS imagery is used to identify landscape characteristics associated with disease transmission at the village level. We conclude with a discussion of the implications of these technologies for improved disease control.

Spatial interaction and connectivity are important factors in the spread of infectious diseases. We developed a spatial‐temporal model of schistosomiasis japonica transmission, a disease caused by parasites that are transported via surface water and that live in both snail and human hosts. The model employed a spatial interaction matrix based on neighborhood relationships and hydrologic connectivity to assess the effect of intervillage parasitic transport on disease transmission and control. Satellite remote‐sensing data served as input to the model for predicting snail density within each village, and for deriving a digital elevation model that was used to quantify hydrologic connectivity. Simulations of the model with varying levels of connectivity and in the presence and absence of chemotherapy control were run for 227 villages near Xichang City, in southwest Sichuan province, China. Increasing connectivity resulted in a geographic clustering of parasites within particular villages that produced higher levels of worm burden than in low and no connectivity simulations. Worm burden within a village could either increase or decrease with connectivity, depending on the degree to which parasites were imported and exported. Simulations of mass chemotherapy in select villages can result in a beneficial reduction in worm burden that extends to downstream neighbors. These findings suggest that better understanding of intervillage connectedness can be exploited in the design of cost‐effective control strategies.