A non-AI preliminary algorithm for the prediction and detection of highly pathogenic African swine fever in pigs using health monitoring collars.

Rachel Layton, David Beggs, Peter Mansell, Andrew Fisher, Daniel Layton, Brint Gardner, David Williams, Kelly Stanger

Abstract read

In one paragraph

Article in Animal welfare (South Mimms, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Rachel LaytonAustralian Animal Health Laboratory, CSIRO Australian Centre for Disease Preparedness Business Unit, Geelong, VIC, Australia.ORCID https://orcid.org/0009-0000-3155-2789

David BeggsFaculty of Science, Melbourne Veterinary School, The University of Melbourne, Werribee, VIC, Australia.ORCID https://orcid.org/0000-0001-5519-9123

Peter MansellFaculty of Science, Melbourne Veterinary School, The University of Melbourne, Werribee, VIC, Australia.

Andrew FisherFaculty of Science, Melbourne Veterinary School, The University of Melbourne, Werribee, VIC, Australia.

Daniel LaytonHealth and Biosecurity, CSIRO Australian Centre for Disease Preparedness Business Unit, Geelong, VIC, Australia.

Brint GardnerInformation Management and Technology, CSIRO, Clayton, VIC, Australia.

David WilliamsAustralian Animal Health Laboratory, CSIRO Australian Centre for Disease Preparedness Business Unit, Geelong, VIC, Australia.

Kelly StangerAustralian Animal Health Laboratory, CSIRO Australian Centre for Disease Preparedness Business Unit, Geelong, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Collar monitoring devices are used in animals for the minimally invasive collection of physiological data, using software and algorithms to provide general health trends. There is potential to utilise the raw data collected from these devices to improve animal monitoring strategies and intervention points in animal disease studies. We aimed to develop an algorithm for the early detection of highly pathogenic African swine fever disease in research pigs (

Indexed as

Animal welfarebiomarkersHRVPetPaceTMpulserespiratory rate

Identifiers

PMID41695661

DOI10.1017/awf.2026.10060

PMCPMC12895198

What OpenQuestion holds

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LicenceCC BY

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Registered trials

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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.