In the current study, we successfully trained honeybees (Apis mellifera) to identify SARS-CoV-2 infected samples from minks (Neovison vison) based on Pavlovian conditioning protocols. The bees can be quickly conditioned to respond specifically to infected mink sample odours and could therefore be part of a wider SARS-CoV-2 diagnostic system. We tested two different training protocols to evaluate their performance in terms of learning rate, accuracy and memory retention. We designed a non-invasive rapid test in which multiple bees are tested in parallel on the same samples. This provided reliable results regarding a subjects health status. Using the data from the training experiments, we simulated a diagnostic evaluation trial to predict the potential efficacy of our diagnostic test, which yielded a diagnostic sensitivity of 92% and specificity of 86%. We suggest that a honeybee-based diagnostics can offer a reliable and rapid test that provides a readily available, low-input addition to the currently available testing methods .
|Effective start/end date||1/01/21 → 31/12/22|