Evidence map›Paper›PMID 39738471›Full record

ArticleScientific reports2024

Estimation of the size, density, and demographic distribution of the UK pet dog population in 2019.

Kirsten M McMillan, Xavier A Harrison, David C Wong, Melissa M Upjohn, Robert M Christley, Rachel A Casey

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

6 authors.

Kirsten M McMillanDogs Trust, London, UK. kirsten.mcmillan@dogstrust.org.uk.
Xavier A HarrisonUniversity of Exeter, Exeter, UK.
David C WongUniversity of Leeds, Leeds, UK.
Melissa M UpjohnDogs Trust, London, UK.
Robert M ChristleyDogs Trust, London, UK.
Rachel A CaseyDogs Trust, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is limited knowledge about the size of the UK dog population. This makes it difficult to reliably monitor population dynamics and management. A repeatable method of measuring the UK dog population, including owned and unowned dogs i.e., those housed long term by animal welfare charities, would help inform interventions to reduce risks to dog welfare such as poor breeding practices and the illegal import of young or pregnant dogs. However, estimating the total dog population in the UK is not straightforward. Although several estimates of dog numbers have been previously suggested, differing methodologies and limited public access to data sources makes comparison and replication difficult. In this study, we compiled a comprehensive dataset of UK pet dogs in 2019, from multiple sources, including a breed registry, veterinary corporations, pet insurance companies, animal welfare charities and an academic institution. Using a hierarchical Bayesian N-mixture model, we estimate 12.64 million (mean, 95% CI 8.54-15.16 million; median, 13.03 million, 95% CI 8.51-15.24 million) owned and unowned pet dogs within the UK in 2019. Estimates were modelled at the postcode area scale, allowing for aggregation to region or country level, as well as providing associated metrics of uncertainty. Furthermore, we provide spatial demographic estimates, regarding age, breed, cephalic index, and body size. Establishing a population baseline offers significant analytical benefits to welfare, veterinary, epidemiological, and business stakeholders alike: as it provides the spatial data required to underpin robust canine welfare strategies and campaigns. We plan to repeat the described process, in order to provide ongoing estimates: allowing for the interrogation of changes to the UK pet dog population over space and time.

Indexed as

PetsAnimalsAnimal WelfareBayes TheoremBreedingDogsFemaleMaleOwnershipPopulation DensityPopulation DynamicsUnited Kingdom

Identifiers

PMID39738471
PMCPMC11686149

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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.