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A Bayesian Approach to Estimate the Prevalence of Schistosomiasis japonica Infection in the Hubei Province Lake Regions, China

Author

Listed:
  • Xin Xia

    (School of Public Health & Global Health Institute, Wuhan University, No. 115, Donghu Road, Wuhan 430071, China
    These authors contributed equally to this work.)

  • Hui-Ping Zhu

    (School of Public Health, Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, No. 10, Xitoutiao, Youanmen, Beijing 100069, China
    These authors contributed equally to this work.)

  • Chuan-Hua Yu

    (School of Public Health & Global Health Institute, Wuhan University, No. 115, Donghu Road, Wuhan 430071, China)

  • Xing-Jian Xu

    (Institute of Schistosomiasis Control, Hubei Provincial Center for Disease Control, No. 6, Zhuodaoquan Road, Wuhan 430079, China)

  • Ren-Dong Li

    (Institute of Geodesy and Geophysics, Chinese Academy of Science, No. 136, Donghu Road, Wuhan 430077, China)

  • Juan Qiu

    (Institute of Geodesy and Geophysics, Chinese Academy of Science, No. 136, Donghu Road, Wuhan 430077, China)

Abstract

A Bayesian inference model was introduced to estimate community prevalence of Schistosomiasis japonica infection based on the data of a large-scale survey of Schistosomiasis japonica in the lake region in Hubei Province. A multistage cluster random sampling approach was applied to the endemic villages in the lake regions of Hubei Province in 2011. IHA test and Kato-Katz test were applied for the detection of the S. japonica infection in the sampled population. Expert knowledge on sensitivities and specificities of IHA test and Kato-Katz test were collected based on a two-round interview. Prevalence of S. japonica infection was estimated by a Bayesian hierarchical model in two different situations. In Situation 1, Bayesian estimation used both IHA test data and Kato-Katz test data to estimate the prevalence of S. japonica . In Situation 2, only IHA test data was used for Bayesian estimation. Finally 14 cities and 46 villages from the lake regions of Hubei Province including 50,980 residents were sampled. Sensitivity and specificity for IHA test ranged from 80% to 90% and 70% to 80%, respectively. For the Kato-Katz test, sensitivity and specificity were from 20% to 70% and 90% to 100%, respectively. Similar estimated prevalence was obtained in the two situations. Estimated prevalence among sampled villages was almost below 13% in both situations and varied from 0.95% to 12.26% when only using data from the IHA test. The study indicated that it is feasible to apply IHA test only combining with Bayesian method to estimate the prevalence of S. japonica infection in large-scale surveys.

Suggested Citation

  • Xin Xia & Hui-Ping Zhu & Chuan-Hua Yu & Xing-Jian Xu & Ren-Dong Li & Juan Qiu, 2013. "A Bayesian Approach to Estimate the Prevalence of Schistosomiasis japonica Infection in the Hubei Province Lake Regions, China," IJERPH, MDPI, vol. 10(7), pages 1-14, July.
    • Handle: RePEc:gam:jijerp:v:10:y:2013:i:7:p:2799-2812:d:26984
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    References listed on IDEAS

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    1. Marios P. Georgiadis & Wesley O. Johnson & Ian A. Gardner & Ramanpreet Singh, 2003. "Correlation‐adjusted estimation of sensitivity and specificity of two diagnostic tests," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(1), pages 63-76, January.
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