Variation of quantified infection rates of mixed samples to enhance rapid testing during an epidemic

Rapid testing of appropriate samples from patients suspected for a disease during an epidemic, such as the current Coronavirus outbreak, is of a great importance for disease management and control. We propose a method to enhance processing large amounts of collected samples. The method is based on mixing samples in testing tubes (pooling) in a specific configuration, as opposed to testing single samples in each tube, and recognise infected samples from variations of the total infection rates in each tube. To illustrate the efficiency of the suggested method, we carry out numerical tests for actual scenarios under various test conditions. Applying the proposed method allows testing many more patients using the same number of testing tubes, where all positives are identified with no false negatives, and no need for independent testing, and the effective testing time can be reduced drastically even when the uncertainty in the test is relatively high.