Spatio-temporal correlation between human and bovine schistosomiasis in China: insight from three national sampling surveys

Submitted: 23 December 2014
Accepted: 23 December 2014
Published: 1 November 2007
Abstract Views: 2091
PDF: 743
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Insight into the spatial and temporal contamination of the environment by bovine faeces in China can provide important information on the significance of bovines in the transmission of human schistosomiasis. This insight will be useful for the new evidence-based strategy of the Chinese national schistosomiasis control programme. To enhance our understanding of the spatio-temporal relationship between the prevalence of human and bovine schistosomiasis, we performed correlation and regression analyses using data from three national sampling surveys on schistosomiasis, carried out in 1989, 1995 and 2004. In addition, we established a geographical information system and performed spatial analyses to identify the high-risk areas of the disease. We found that schistosomiasis is mainly concentrated in the marshlands along the Yangtze River. It was also noted that, although the human prevalence and force of transmission in highly endemic areas has been reduced since 1989, the relative importance of bovine schistosomiasis has increased. This is seen in a declining Spearman correlation coefficient between the infection prevalence in humans and in bovines over time (0.812 in 1989, 0.754 in 1995 and 0.376 in 2004). In parallel, the slope of the linear regression decreased from 0.395 in 1989 to 0.215 in 2004. Our data therefore suggest that future schistosomiasis control efforts in China should more vigorously address the important role of bovines in the transmission of human schistosomiasis, and to reduce the environmental contamination of Schistosoma japonicum eggs by bovines.



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How to Cite

Wu, X.-H., Wang, X.-H., Utzinger, J., Yang, K., Kristensen, T. K., Bergquist, R., Zhao, G.-M., Dang, H., & Zhou, X.-N. (2007). Spatio-temporal correlation between human and bovine schistosomiasis in China: insight from three national sampling surveys. Geospatial Health, 2(1), 75–84.

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