Evidence map›Paper›PMID 35445042›Full record

ReviewFrontiers in medicine2022

The Use and Potential of Biomedical Detection Dogs During a Disease Outbreak.

Michele N Maughan, Eric M Best, Jenna Dianne Gadberry, Caitlin E Sharpes, Kelley L Evans, Calvin C Chue, Patrick Lawrence Nolan, Patricia E Buckley

Abstract readReview
In one paragraph

Review 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Human-dog trust and cohesion within French military canine teams.Military psychology : the official journal of the Division of Military Psychology, American Psychological Association · 2025
    Article
  5. Article
  6. 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

8 authors.

Michele N MaughanExcet, Inc., Springfield, VA, United States.
Eric M BestPenn State Harrisburg, Harrisburg, PA, United States.
Jenna Dianne GadberryIntrinsic24, LLC, Hayden, ID, United States.
Caitlin E SharpesExcet, Inc., Springfield, VA, United States.
Kelley L EvansBiochemistry Branch, U.S. Army DEVCOM Chemical Biological Center, Aberdeen Proving Ground, MD, United States.
Calvin C ChueBiochemistry Branch, U.S. Army DEVCOM Chemical Biological Center, Aberdeen Proving Ground, MD, United States.
Patrick Lawrence NolanTactical Directional Canine Systems, LLC, Smithsburg, MD, United States.
Patricia E BuckleyBiochemistry Branch, U.S. Army DEVCOM Chemical Biological Center, Aberdeen Proving Ground, MD, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biomedical detection dogs offer incredible advantages during disease outbreaks that are presently unmatched by current technologies, however, dogs still face hurdles of implementation due to lack of inter-governmental cooperation and acceptance by the public health community. Here, we refine the definition of a biomedical detection dog, discuss the potential applications, capabilities, and limitations of biomedical detection dogs in disease outbreak scenarios, and the safety measures that must be considered before and during deployment. Finally, we provide recommendations on how to address and overcome the barriers to acceptance of biomedical detection dogs through a dedicated research and development investment in olfactory sciences.

Indexed as

biomedical detection dog (BMDD)canineCOVID-19olfactory sciencetraining aid delivery device (TADD)volatile organic compound (VOC)volatilome

Identifiers

PMID35445042
PMCPMC9014822

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.