Evidence map›Paper›PMID 36530913›Full record

ArticleFrontiers in medicine2022

Use of trained scent dogs for detection of COVID-19 and evidence of cost-saving.

Leon Mutesa, Gashegu Misbah, Eric Remera, Hans Ebbers, Esther Schalke, Patrick Tuyisenge, Reuben Sindayiheba, Clement Igiraneza, Jeanine Uwimana, Diane Mbabazi and 20 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 45% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

30 authors at 4 institutions in 3 countries.

Leon MutesaCenter for Human Genetics, Inc., College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda.
Gashegu MisbahRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Eric RemeraRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Hans EbbersKynoscience UG, Praxis und Wissenschaft, Hörstel, Germany.
Esther SchalkeKynoscience UG, Praxis und Wissenschaft, Hörstel, Germany.
Patrick TuyisengeRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Reuben SindayihebaRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Clement IgiranezaRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Jeanine UwimanaRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Diane MbabaziRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Epimaque KayongaK9 Department, Rwanda National Police, Kigali, Rwanda.
Michel TwagiramunguK9 Department, Rwanda National Police, Kigali, Rwanda.
Denyse MugwanezaRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Leandre IshemaRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Yvan ButeraCenter for Human Genetics, Inc., College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda.
Clarisse MusanabaganwaCenter for Human Genetics, Inc., College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda.
Edson RwagasoreRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Friederike TweleDepartment of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hannover, Germany.
Sebastian MellerDepartment of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hannover, Germany.
Albert TuyishimeRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Robert RutayisireRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Marilyn Milumbu MurindahabiRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Lindsay A WilsonSchool of Population and Public Health, University of British Columbia, Vancouver, BC, Canada.
Noella BigirimanaRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Holger A VolkDepartment of Small Animal Medicine and Surgery, University of Veterinary Medicine Hannover, Hannover, Germany.
Vedaste NdahindwaRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Benoit KayijukaK9 Department, Rwanda National Police, Kigali, Rwanda.
Edward J MillsDepartment of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.
Claude Mambo MuvunyiRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
Sabin NsanzimanaRwanda National Joint Task Force COVID-19, Kigali, Rwanda.
University of Rwanda · RWUniversity of Veterinary Medicine Hannover, Foundation · DEImpact · CAUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: One of the lessons learned from the coronavirus disease 2019 (COVID-19) pandemic is the importance of early, flexible, and rapidly deployable disease detection methods. Currently, diagnosis of COVID-19 requires the collection of oro/nasopharyngal swabs, nasal turbinate, anterior nares and saliva but as the pandemic continues, disease detection methods that can identify infected individuals earlier and more quickly will be crucial for slowing the spread of the virus. Previous studies have indicated that dogs can be trained to identify volatile organic compounds (VOCs) produced during respiratory infections. We sought to determine whether this approach could be applied for detection of COVID-19 in Rwanda and measured its cost-saving. Methods: Over a period of 5 months, four dogs were trained to detect VOCs in sweat samples collected from human subjects confirmed positive or negative for COVID-19 by reverse transcription polymerase chain reaction (RT-PCR) testing. Dogs were trained using a detection dog training system (DDTS) and Findings: From August to September 2021 during the Delta wave, the sensitivity of the dogs' COVID-19 detection ranged from 75.0 to 89.9% for the lowest- and highest-performing dogs, respectively. Specificity ranged from 96.1 to 98.4%, respectively. In the second phase coinciding with the Omicron wave (January-March 2022), the sensitivity decreased substantially from 36.6 to 41.5%, while specificity remained above 95% for all four dogs. The sensitivity and specificity by any positive sample detected by at least one dog was 83.9, 95% CI: 75.8-90.2 and 94.9%; 95% CI: 93.9-95.8, respectively. The use of scent detection dogs was also found to be cost-saving compared to antigen rapid diagnostic tests, based on a marginal cost of approximately $14,000 USD for testing of the 5,253 samples which makes 2.67 USD per sample. Testing turnaround time was also faster with the scent detection dogs, at 3 h compared to 11 h with routine diagnostic testing. Conclusion: The findings from this study indicate that trained dogs can accurately identify respiratory secretion samples from asymptomatic and symptomatic COVID-19 patients timely and cost-effectively. Our findings recommend further uptake of this approach for COVID-19 detection.

Indexed as

cost-savingCOVID-19RT-PCRSARS-CoV-2scent dogsvolatile organic compounds (VOCs)

Identifiers

PMID36530913
PMCPMC9751420
OpenAlexW4311049527

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.