Evidence map›Paper›PMID 37644835›Full record

ArticleProceedings. Biological sciences2023

Accelerometer-based detection of African swine fever infection in wild boar.

Kevin Morelle, Jose Angel Barasona, Jaime Bosch, Georg Heine, Andreas Daim, Janosch Arnold, Toralf Bauch, Aleksandra Kosowska, Estefanía Cadenas-Fernández, Marta Martinez Aviles and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Proceedings. Biological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
6.9field-weighted citation impact, top 3% 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

13 citing papers in PubMed, 20 citations in OpenAlex.

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  5. From biologging to conservation: Tracking individual performance in changing environments.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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

14 authors at 6 institutions in 4 countries.

Kevin MorelleDepartment of Migration, Max Planck Institute of Animal Behaviour, Radolfzell, Germany.ORCID 0000-0001-9041-6541
Jose Angel BarasonaVISAVET Health Surveillance Center, Department of Animal Health, Complutense University of Madrid, 28040 Madrid, Spain.
Jaime BoschVISAVET Health Surveillance Center, Department of Animal Health, Complutense University of Madrid, 28040 Madrid, Spain.
Georg HeineDepartment of Migration, Max Planck Institute of Animal Behaviour, Radolfzell, Germany.
Andreas DaimDepartment of Integrative Biology and Biodiversity Research, University of Natural Resources and Life Sciences, Institute of Wildlife Biology and Game Management (BOKU), Vienna, Austria.
Janosch ArnoldAgricultural Centre Baden-Württemberg, Wildlife Research Unit, Aulendorf, Germany.
Toralf BauchAgricultural Centre Baden-Württemberg, Wildlife Research Unit, Aulendorf, Germany.
Aleksandra KosowskaVISAVET Health Surveillance Center, Department of Animal Health, Complutense University of Madrid, 28040 Madrid, Spain.
Estefanía Cadenas-FernándezVISAVET Health Surveillance Center, Department of Animal Health, Complutense University of Madrid, 28040 Madrid, Spain.
Marta Martinez AvilesAnimal Health Research Centre (CISA, INIA-CSIC), 28130, Valdeolmos, Madrid, Spain.
Daniel ZuñigaDepartment of Migration, Max Planck Institute of Animal Behaviour, Radolfzell, Germany.
Martin WikelskiDepartment of Migration, Max Planck Institute of Animal Behaviour, Radolfzell, Germany.
Jose Manuel Vizcaino-SanchezVISAVET Health Surveillance Center, Department of Animal Health, Complutense University of Madrid, 28040 Madrid, Spain.
Kamran SafiDepartment of Migration, Max Planck Institute of Animal Behaviour, Radolfzell, Germany.
Universidad Complutense de Madrid · ESMax Planck Institute of Animal Behavior · DEBOKU University · ATCentro de Investigación en Sanidad AnimalCzech University of Life Sciences Prague · CZUniversity of Konstanz · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Infectious wildlife diseases that circulate at the interface with domestic animals pose significant threats worldwide and require early detection and warning. Although animal tracking technologies are used to discern behavioural changes, they are rarely used to monitor wildlife diseases. Common disease-induced behavioural changes include reduced activity and lethargy ('sickness behaviour'). Here, we investigated whether accelerometer sensors could detect the onset of African swine fever (ASF), a viral infection that induces high mortality in suids for which no vaccine is currently available. Taking advantage of an experiment designed to test an oral ASF vaccine, we equipped 12 wild boars with an accelerometer tag and quantified how ASF affects their activity pattern and behavioural fingerprint, using overall dynamic body acceleration. Wild boars showed a daily reduction in activity of 10-20% from the healthy to the viremia phase. Using change point statistics and comparing healthy individuals living in semi-free and free-ranging conditions, we show how the onset of disease-induced sickness can be detected and how such early detection could work in natural settings. Timely detection of infection in animals is crucial for disease surveillance and control, and accelerometer technology on sentinel animals provides a viable complementary tool to existing disease management approaches.

Indexed as

African Swine FeverSus scrofaAccelerationAccelerometryAnimalsAnimals, DomesticAnimals, WildSwineAfrican swine feveranimal sentinelbiosignalwild boarwildlife disease monitoring

Identifiers

PMID37644835
PMCPMC10465979
OpenAlexW4386272656

What OpenQuestion holds

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LicenceCC BY
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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.