An Optimization Research Of The Survey Method Of Oncomelania Snail In Marshland Endemic Region Of Schistosomiasis In Poyang Lake,China

Oncomelania snail is the unique intermediate host of schistosomiasis.The geographical distribution of snails may determine the spatial distribution of schistosomiasis to a certain extent.Due to the spatial heterogeneity and aggregation of the snail distribution,the traditional mechanical sampling method can not only estimate the oncomelania snails accurately,but also consume a lot of manpower,material and financial resources.At present,the remote sensing method is far from being able to interpret the snail from the remote sensing image directly.Therefore,it is necessary to simplify and optimize the existing snail sampling scheme.In this study,we used the statistical method,K-means clustering algorithm(K-means)and fuzzy C-means clustering(FCM)to explore the impact of the geometric center(the maximum coverage area)and the environmental center(representative sampling points)on sampling efficiency,so as to provide new scientific basis for optimization of snail survey method in the marshland schistosomiasis epidemic area in China.First,A snail sampling strategy(Spatial Sampling Scenario of Oncomelania based on Plant Abundance,SOPA)which took the plant abundance as auxiliary variable was explored and an experimental study in a 50 m×50 m plot in a marshland in the Poyang Lake region was performed.Firstly,the push broom surveyed data was stratified into 5 layers by the plant abundance data;then,the required numbers of optimal sampling points of each layer through Hammond McCullagh equation were calculated;thirdly,every sample point in the line with the Multiple Directional Interpolation(MDI)placement scheme was pinpointed;and finally,the comparison study among the outcomes of the spatial random sampling strategy,the traditional systematic sampling method,the spatial stratified sampling method,Sandwich spatial sampling and inference and SOPA was performed.The outcome showed that the method(SOPA)proposed in this study had the minimal absolute error of 0.213 8;and the traditional systematic sampling method had the largest estimate,and the absolute error was 0.924 4.This indicated that the snail sampling strategy proposed in this study can obtain higher estimation accuracy than spatial random sampling strategy,system sampling strategy,spatial stratification sampling strategy and sandwich sampling strategy,that is to say,we can improve the sampling efficiency by taking the plant abundance as auxiliary variable and obeying the principle of maximization coverage area of sampling points.Then,based on the demonstration of the plant abundance to optimize the sampling plan of snails,we further expand the auxiliary variable.We proposed a spatial sampling scenario of oncomelania based on representative samples-SORS,in which the Fuzzy c-means clustering analysis of snail environmental co-variates was performed to explore for sampling points representative of different numbers of snail spatial distribution.The method was applied to snail sampling design in Chayegang marshland of Henghu farm in the Poyang Lake region,error analysis of the collected representative samples was conducted,and a comparison study was made among the outcomes of the SORS,the random sampling method and the traditional systematic sampling method.The results show that the SORS method proposed is obviously better than the random sampling method and the traditional systematic sampling method,the absolute errors of snail number are 0.4407,1.5514,3.5653 and relative errors of snail number are 1.0481,3.6897,8.4796 respectively.Conclusion It implies the new snail sampling method can obtain higher estimation accuracy than the current snail survey method used by the schistosomiasis control departments,which could provide new scientific basis for optimization of snail survey method in the marshland schistosomiasis epidemic area in China.The study showed that,based on the rich priori knowledge,we can improve the efficiency of snail sampling by obeying the principle of the geometric center or the environment center.This study can provide the basis for optimizing the current snail investigation scheme.