摘要
Background:Schistosomiasis in the People’s Republic of China(PRC)can be traced back to antiquity.In the past 60 years,the Chinese government has made great efforts to control this persistent disease with elimination slated by 2020 through the implementation of a comprehensive control strategy.This strategy aims to reduce the role of bovines and humans as sources of infection as a pre-requisite for elimination through transmission interruption.The goal of elimination will be achievable only by the implementation of a sustainable surveillance and control system,with sensitive diagnosis a key feature so that the true disease burden is not underestimated.Currently used diagnostics lack the necessary sensitivity to accurately determine the prevalence of Schistosoma japonicum infection in areas with low infection intensities.It is of critical importance to find and treat people and to identify animals with low-level infections if the National Control Programme for China is to achieve schistosomiasis elimination.Methods:We evaluated a real-time polymerase chain reaction(qPCR)assay using 633 human stool samples collected from five villages in Hunan,Anhui,Hubei,and Jiangxi provinces,and 182 bovine(70 cattle and 112 buffalo)stool samples obtained from four villages in Hunan,Anhui,and Jiangxi provinces in the PRC.All stool samples were subjected to the miracidium hatching test(MHT,a diagnostic procedure used in the National Schistosomiasis Control Programme)and the qPCR assay.Samples positive by MHT were subjected to either the Kato-Katz technique for humans,or the formalin-ethyl acetate sedimentation-digestion(FEA-SD)procedure for bovines,to determine infection intensities.Results:The qPCR assay exhibited a high level of sensitivity in the detection of S.japonicum infections.With both the human and bovine samples,a significantly higher prevalence was determined using the qPCR assay(11.06%humans,24.73%bovines)than with the MHT(0.93%humans,7.69%bovines).The animal contamination index(calculated using data obtained with the
基金
This work was supported by the Science and Technology Committee of Hunan Province,People’s Republic of China(Grant No.2013WK3023)
by the Australian National Health and Medical Research Council(Project Grants:APP1002245,APP1098244,Program Grant:APP1037304).
