The control of schistosomiasis calls for rapid and reliable classification tools. This study, involving LSTM, evaluates the performance of one such tool, Lot Quality Assurance Sampling (LQAS) for assessing the prevalence of the S. mansoni species in African schoolchildren.
We outline the design considerations and introduce novel sequential sampling plans for Multiple Category-LQAS. We use data from 388 schools in Uganda, Kenya, and Tanzania to assess the performance of LQAS as a tool for classification of S. mansoni infection. Our findings suggest that an LQAS-based multiple classification system performs as well as the World Health Organization recommended methods at a fraction of the sampling effort. Our work validates LQAS as a rapid assessment tool and extends it to allow investigators to apply the method to control other infectious diseases.