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Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study

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  • معلومة اضافية
    • Contributors:
      Medical Detection Dogs; Arctech Innovation; Durham University; London School of Hygiene and Tropical Medicine (LSHTM); Faculty of Infectious and Tropical Diseases; Department of Medical Statistics; Faculty of Epidemiology and Population Health London; Hampden Veterinary Hospital; RoboScientific Ltd; Royal Veterinary College London; University of London London; Cardiff University; Lomond Veterinary Clinic; Department of Health and Social Care, UK Government (2020/023); Durham University COVID-19 response fund (RF020929); NIHR Clinical Research network support (IRAS ID 284222); Charitable donations
    • بيانات النشر:
      HAL CCSD
      Wiley-Blackwell
    • الموضوع:
      2022
    • Collection:
      Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
    • نبذة مختصرة :
      International audience ; Background: A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry. Methods: Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected
    • Relation:
      hal-04164731; https://hal.science/hal-04164731; https://hal.science/hal-04164731/document; https://hal.science/hal-04164731/file/2022_Guest_JTM.pdf; WOS: 000786122700001
    • الرقم المعرف:
      10.1093/jtm/taac043
    • Rights:
      http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.E57C3CA6