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Bees can be trained to identify SARS-CoV-2 infected samples.

Evangelos Kontos1,2, Aria Samimi1, Renate W Hakze-van der Honing3

  • 1InsectSense, Plus Ultra-II Building, Bronland, 10, 6708 WH, Wageningen, The Netherlands.

Biology Open
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Summary

Honeybees can be trained to detect SARS-CoV-2 in minks using their sense of smell. This novel, rapid diagnostic method shows high accuracy and could aid in controlling zoonotic diseases.

Keywords:
ConditioningCovid-19DetectionHoneybeesOlfactionSARS-CoV2

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Area of Science:

  • Veterinary Medicine
  • Animal Health
  • Infectious Disease Diagnostics

Background:

  • The COVID-19 pandemic highlighted the need for rapid, reliable diagnostics for zoonotic viral diseases in both humans and animals.
  • Pathologies alter an animal's volatile organic compound (VOC) profile, offering a potential target for non-invasive diagnostic tests.

Purpose of the Study:

  • To train honeybees (Apis mellifera) to detect SARS-CoV-2 infected minks (Neovison vison) using Pavlovian conditioning.
  • To evaluate different training protocols for optimal learning rate, accuracy, and memory retention in honeybees for disease detection.
  • To assess the potential of a honeybee-based diagnostic system as a rapid, low-input addition to existing SARS-CoV-2 testing methods.

Main Methods:

  • Honeybees were trained using Pavlovian conditioning protocols to identify SARS-CoV-2 infected mink odors.
  • Two distinct training protocols were tested to compare learning rates, accuracy, and memory retention.
  • A non-invasive rapid test was designed, allowing parallel testing of multiple bees on the same samples.
  • Diagnostic efficacy was simulated using training data, calculating sensitivity and specificity.

Main Results:

  • Honeybees were successfully trained to specifically respond to odors from SARS-CoV-2 infected minks.
  • Simulated diagnostic evaluation predicted a sensitivity of 92% and a specificity of 86% for the honeybee-based test.
  • The non-invasive, parallel testing approach provided reliable results regarding the subjects' health status.

Conclusions:

  • Honeybee-based diagnostics offer a reliable, rapid, and low-input method for detecting SARS-CoV-2 in minks.
  • This approach can be integrated into wider diagnostic systems for managing zoonotic viral diseases.
  • Honeybee diagnostics are particularly promising for remote or resource-limited communities lacking advanced testing infrastructure.