Parasitology

Research Article

Location of active transmission sites of Schistosoma japonicum in lake and marshland regions in China

Z. J. ZHANGa1a2 c1, T. E. CARPENTERa3, H. S. LYNNa4, Y. CHENa5, R. BIVANDa6, A. B. CLARKa7, F. M. HUIa8, W. X. PENGa1a2, Y. B. ZHOUa1a2, G. M. ZHAOa1a2 and Q. W. JIANGa1a2

a1 Department of Epidemiology, School of Public Health, Fudan University, No. 138 Yi Xue Yuan Road, Shanghai 200032, China

a2 Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, China

a3 Center for Animal Disease Modeling and Surveillance (CADMS), Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, One Shields Avenue, Davis, CA 95616, USA

a4 Department of Health Statistics, School of Public Health, Fudan University, No. 138 Yi Xue Yuan Road, Shanghai 200032, China

a5 Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, 451 Smyth Rd, Ottawa, Ontario, Canada

a6 Department of Economics, Norwegian School of Economics and Business Administration, Helleveien 3, N-5045 Bergen, Norway

a7 School of Medicine, Health Policy and Practice, University of East Anglia, Norwich, UK

a8 State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101, China

SUMMARY

Schistosomiasis control in China has, in general, been very successful during the past several decades. However, the rebounding of the epidemic situation in some areas in recent years raises concerns about a sustainable control strategy of which locating active transmission sites (ATS) is a necessary first step. This study presents a systematic approach for locating schistosomiasis ATS by combining the approaches of identifying high risk regions for schisotosmiasis and extracting snail habitats. Environmental, topographical, and human behavioural factors were included in the model. Four significant high-risk regions were detected and 6 ATS were located. We used the normalized difference water index (NDWI) combined with the normalized difference vegetation index (NDVI) to extract snail habitats, and the pointwise ‘P-value surface’ approach to test statistical significance of predicted disease risk. We found complicated non-linear relationships between predictors and schistosomiasis risk, which might result in serious biases if data were not properly treated. We also found that the associations were related to spatial scales, indicating that a well-designed series of studies were needed to relate the disease risk with predictors across various study scales. Our approach provides a useful tool, especially in the field of vector-borne or environment-related diseases.

(Received January 10 2009)

(Revised January 29 2009)

(Accepted January 29 2009)

(Online publication May 06 2009)

Correspondence:

c1 Corresponding author: Department of Epidemiology, School of Public Health, Fudan University, No. 138 Yi Xue Yuan Road, Shanghai 200032, China. Tel:/Fax: +86 21 54237410. E-mail: zhj_zhang@fudan.edu.cn

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