Sandwich mapping of schistosomiasis risk in Anhui Province, China
Authors
Yi Hu – articles in this journalDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Henry Lynn – articles in this journalDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Rui Li – articles in this journalDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Liqian Sun – articles in this journalDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Congcong Xia – articles in this journalDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Zhijie Zhang – articles in this journalCorresponding author
EmailDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai; Laboratory for Spatial Analysis and Modeling, School of Public Health, Fudan University, Shanghai, China.
Qingwu Jiang – articles in this journalDepartment of Epidemiology and Biostatistics, School of Public Health, Fudan University, Shanghai; Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Schistosomiasis mapping using data obtained from parasitological surveys is frequently used in planning and evaluation of disease control strategies. The available geostatistical approaches are, however, subject to the assumption of stationarity, a stochastic process whose joint probability distribution does not change when shifted in time. As this is impractical for large areas, we introduce here the sandwich method, the basic idea of which is to divide the study area (with its attributes) into homogeneous subareas and estimate the values for the reporting units using spatial stratified sampling. The sandwich method was applied to map the county-level prevalence of schistosomiasis japonica in Anhui Province, China based on parasitological data collected from sample villages and land use data. We first mapped the county-level prevalence using the sandwich method, then compared our findings with block Kriging. The sandwich estimates ranged from 0.17 to 0.21% with a lower level of uncertainty, while the Kriging estimates varied from 0 to 0.97% with a higher level of uncertainty, indicating that the former is more smoothed and stable compared to latter. Aside from various forms of reporting units, the sandwich method has the particular merit of simple model assumption coupled with full utilization of sample data. It performs well when a disease presents stratified heterogeneity over space.
