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Keywords:

  • schistosomiasis;
  • Schistosoma mansoni;
  • Lot Quality Assurance Sampling;
  • parasitological screening;
  • cost-effectiveness;
  • national control;
  • Uganda

Summary

Rapid and accurate identification of communities at highest risk of morbidity from schistosomiasis is key for sustainable control. Although school questionnaires can effectively and inexpensively identify communities with a high prevalence of Schistosoma haematobium, parasitological screening remains the preferred option for S. mansoni. To help reduce screening costs, we investigated the validity of Lot Quality Assurance Sampling (LQAS) in classifying schools according to categories of S. mansoni prevalence in Uganda, and explored its applicability and cost-effectiveness. First, we evaluated several sampling plans using computer simulation and then field tested one sampling plan in 34 schools in Uganda. Finally, cost-effectiveness of different screening and control strategies (including mass treatment without prior screening) was determined, and sensitivity analysis undertaken to assess the effect of infection levels and treatment costs. In identifying schools with prevalences ≥50%, computer simulations showed that LQAS had high levels of sensitivity and specificity (>90%) at sample sizes <20. The method also provides an ability to classify communities into three prevalence categories. Field testing showed that LQAS where 15 children were sampled had excellent diagnostic performance (sensitivity: 100%, specificity: 96.4%, positive predictive value: 85.7% and negative predictive value: 92.3%). Screening using LQAS was more cost-effective than mass treating all schools (US$218 vs. US$482/high prevalence school treated). Threshold analysis indicated that parasitological screening and mass treatment would become equivalent for settings where prevalence ≥50% in 75% of schools and for treatment costs of US$0.19 per schoolchild. We conclude that, in Uganda, LQAS provides a rapid, valid and cost-effective method for guiding decision makers in allocating finite resources for the control of schistosomiasis.