Bayesian estimation of community prevalences of Schistosoma japonicum infection in China.

A Bayesian approach to overcome the imperfections of an immunological test (an antibody-based ELISA) and a parasitological test (Kato-Katz) in the detection of Schistosoma japonicum infection, was used to estimate community prevalences of S. japonicum infection in China. At the same time, the similarity between the prevalence estimates based on data from ELISA alone and those using data from both ELISA and Kato-Katz tests was explored. The database from the third nationwide sampling survey of schistosomiasis in China, 2004, was used for analysis, in which a total of 239 endemic villages were sampled from seven endemic provinces through a stratified cluster sampling technique and 250,987 residents aged from 6 to 65 years, were examined by ELISA followed by a Kato-Katz test applied to the seropositives. Bayesian hierarchical models incorporating random effects to reflect the nested data structure and uncertainty about test properties were employed to analyse the data. Our analysis suggested that using data from ELISA alone or both ELISA and Kato-Katz tests resulted in similar prevalence estimates, probably owing to the lack of sensitivity of Kato-Katz and the fact that Kato-Katz was only applied to the seropositives. We conclude that it is feasible to employ only ELISA, instead of combined ELISA and Kato-Katz tests, to estimate prevalence of S. japonicum infection in large-scale epidemiological settings. This study confirmed heterogeneity in the prevalence of S. japonicum infection in space by the fact that the estimated prevalences of S. japonicum infection in the sampled villages ranged from 0.02% to about 56% (posterior median). It is indicated that the disease remains a threat in some areas along the Yangtze River, although great achievements have been made in the control programme of schistosomiasis in China.