A Spatial-Temporal Model for Assessing the Effects of Intervillage Connectivity in Schistosomiasis Transmission

Abstract

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. Key Words: geographic information systems, remote sensing, schistosomiasis, spatial interaction, spatial-temporal model.