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 Table of Contents  
LETTER TO EDITOR
Year : 2022  |  Volume : 12  |  Issue : 5  |  Page : 244-245

Detection dogs cases about their sniffing applications in medical and future application for COVID-19 pandemic


1 Department of Mechanical Engineering, I.K. Gujral Punjab Technical University, Kapurthala, Punjab, India
2 Department of Mechanical Engineering, Dr. B R Ambedkar National Institute of Technology, Jalandhar, Punjab, India
3 Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, India

Date of Submission06-Jul-2021
Date of Decision10-Oct-2022
Date of Acceptance11-Oct-2022
Date of Web Publication31-Oct-2022

Correspondence Address:
Shashi Bahl
Department of Mechanical Engineering, I.K. Gujral Punjab Technical University, Kapurthala - 144 603, Punjab
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/cmrp.cmrp_67_21

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How to cite this article:
Bahl S, Bagha AK, Haleem A, Javaid M. Detection dogs cases about their sniffing applications in medical and future application for COVID-19 pandemic. Curr Med Res Pract 2022;12:244-5

How to cite this URL:
Bahl S, Bagha AK, Haleem A, Javaid M. Detection dogs cases about their sniffing applications in medical and future application for COVID-19 pandemic. Curr Med Res Pract [serial online] 2022 [cited 2022 Nov 27];12:244-5. Available from: http://www.cmrpjournal.org/text.asp?2022/12/5/244/359942



Dear Editor,

Dogs have about 25 times more smell receptors as compared with human beings, making them smell 100,000 times better. Further, a dog's brains also process information differently to detect items; this capability is being used to identify a smelling patient. In human beings, the visual cortex dominates the human brain, whereas the dog's brain is dominated by the olfactory cortex, due to which dogs follow through their noses. In the dog's nose, microscopic hairline structures (multiple cilia) extend into the nasal cavity of the dog's nose from each of the sensory cells; each cilium has many scent receptors, which trap a smell, the scent “signal” is sent to the olfactory system of the brain.

Dogs pick up volatile organic compounds (VOCs) in the air, identifying the COVID-19 virus. These VOCs are present in both gaseous and liquid states. VOCs are microscopic chemicals and can be emitted by both human-made and biological substances. However, humans can detect VOCs too, but the dog's ability of sniffing VOCs is way better. Dogs can detect VOCs in very smaller amounts. The sniffing capability of dogs depends on the dog's breed. Some dogs are just better sniffers than others.[1] COVID-19 virus is known to sustain on different surfaces, and different technologies are introduced to identify the COVID-19 virus and predict its further spread.[2],[3],[4],[5] Diabetes patients face more problems during the current situation, and they need to be regularly provided with telemedicine and other digital services these days.[6],[7],[8],[9],[10] In this article, we discuss a few critical experimental cases of using detection dogs for medical applications. These cases may help us in understanding how these dogs are used gainfully in identifying a COVID-19 patient.

Children of Gambian school aged between 5 and 13 years participated in this research, where foot odour of children with and without asymptomatic falciparum malaria was taken. Each child had to wear nylon socks for a night. Two dogs were trained for this research for about 17–20 months. The sample size had 30infected and 145 uninfected patients for the testing. The first dog discriminated samples of malaria-infected children from a group of infected and noninfected, with a sensitivity of 73.3% and specificity of 91%, whereas the second dog had a specificity of 90.3% and a sensitivity of 70%.[1]

In another study, two trained dogs were used to detect the bovine viral diarrhoea virus (BVDV)-infected cell culture from the unaffected cell culture. Researchers tested cell cultures infected with bovine herpesvirus 1 and bovine parainfluenza virus 3. Dogs were trained to detect infected cell cultures with two different biotypes of BVDV generated in Madin–Darby bovine kidney cells with the help of one of three culture media. For identification, seven uninfected and one infected samples were hung on a scent wheel by the handler, unaware of the target location. The first dog detected the infected sample with a sensitivity of 85% and specificity of 98.1%, whereas the second dog identified the infected sample with improved sensitivity of 96.7% and specificity of 99.3%.[11]

In one crucial research, six dogs were trained for hypoalert for 6 months using positive training methods. Dog's age varies between 1 and 10 years old. Sweat samples of patients during normoglycaemia (85–136 mg/dl) and hypoglycaemia (46–65 mg/dl) conditions were collected for the training purpose of dogs. The sample was randomly placed by rolling a dice in glass vials, which were then placed into steel cans. The dogs were rewarded with foods on successful recognition of the hyposample.[12]

Similarly, in another study, six dogs were trained to discriminate between urine samples from patients with bladder cancer and urine from unhealthy people. Dogs had to identify the infected sample from six samples. The dogs had been taught to lie beside the infected sample. Multivariate analysis showed that the capacity to identify the odour of bladder cancer was independent of other chemical compositions of the urine.[13]

Thus, looking into the successful cases on detection dogs, researchers propose more clinical trials for medical detection dogs to identify other diseases in humans with a high level of precision. Further, in the upcoming time, detection dogs can be successfully used to identify a patient infected by the COVID-19 virus. This will reduce the job of extensive testing, thereby having wider clinical application in the population.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Guest C, Pinder M, Doggett M, Squires C, Affara M, Kandeh B, et al. Trained dogs identify people with malaria parasites by their odour. Lancet Infect Dis 2019;19:578-80.  Back to cited text no. 1
    
2.
Javaid M, Haleem A, Vaishya R, Bahl S, Suman R, Vaish A. Industry 4.0 technologies and their applications in fighting COVID-19 pandemic. Diabetes Metab Syndr 2020;14:419-22.  Back to cited text no. 2
    
3.
Suman R, Javaid M, Haleem A, Vaishya R, Bahl S, Nandan D. Sustainability of Coronavirus on different surfaces. J Clin Exp Hepatol 2020;10:386-90.  Back to cited text no. 3
    
4.
Bahl S, Javaid M, Bagha AK, Singh RP, Haleem A, Vaishya R, et al. Biosensors applications in fighting COVID-19 pandemic. Apollo Med. 2020;17:221-3.  Back to cited text no. 4
    
5.
Sharma A, Bahl S, Bagha A, Javaid M, Shukla D, Haleem A. Multi-agent system applications to fight COVID-19 pandemic. Apollo Med 2020;17:S41-3.  Back to cited text no. 5
    
6.
Iyengar K, Bahl S, Raju Vaishya, Vaish A. Challenges and solutions in meeting up the urgent requirement of ventilators for COVID-19 patients. Diabetes Metab Syndr 2020;14:499-501.  Back to cited text no. 6
    
7.
Bahl S, Singh RP, Javaid M, Khan IH, Vaishya R, Suman R. Telemedicine technologies for confronting COVID-19 pandemic: A review. J Ind Integr Manage 2020;5:547-61.  Back to cited text no. 7
    
8.
Singh RP, Javaid M, Haleem A, Vaishya R, Bahl S. Significance of Health Information Technology (HIT) in context to COVID-19 pandemic: Potential roles and challenges. J Ind Integr Manage 2020;5:427-40.  Back to cited text no. 8
    
9.
Sharma A, Bahl S, Bagha AK, Javaid M, Shukla DK, Haleem A. Blockchain technology and its applications to combat COVID-19 pandemic. Res Biomed Eng 2022;38:173-80.  Back to cited text no. 9
    
10.
Kushwaha S, Bahl S, Bagha AK, Parmar KS, Javaid M, Haleem M, et al. Significant Applications of Machine Learning for COVID-19 Pandemic. J Ind Integr Manag 2020;5:453-79.  Back to cited text no. 10
    
11.
Angle TC, Passler T, Waggoner PL, Fischer TD, Rogers B, Galik PK, et al. Real-Time Detection of a Virus Using Detection Dogs. Front Vet Sci. 2016;2:79.  Back to cited text no. 11
    
12.
Hardin DS, Anderson W, Cattet J. Dogs can be successfully trained to alert to hypoglycemia samples from patients with type 1 diabetes. Diabetes Ther 2015;6:509-17.  Back to cited text no. 12
    
13.
Willis CM, Church SM, Guest CM, Cook WA, McCarthy N, Bransbury AJ, et al. Olfactory detection of human bladder cancer by dogs: Proof of principle study. BMJ 2004;329:712.  Back to cited text no. 13
    




 

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