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Using prevalence data of 5 common febrile illnesses from India and Cambodia, and performance characteristics (sensitivity and specificity) of relevant pathogen-specific RDTs, we used a mathematical model to predict the probability of correct identification of each disease when diagnostic testing occurs either simultaneously or sequentially in various algorithms. We developed a web-based application of the model so as to visualize and compare output diagnostic algorithms when different disease prevalence and test performance characteristics are introduced.

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acute undifferentiated febrile illness, algorithm, diagnosis, rapid diagnostic test.