Accelerometer-based detection of African swine fever infection in wild boar
Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
37644835
PubMed Central
PMC10465979
DOI
10.1098/rspb.2023.1396
Knihovny.cz E-zdroje
- Klíčová slova
- African swine fever, animal sentinel, biosignal, wild boar, wildlife disease monitoring,
- MeSH
- africký mor prasat * diagnóza MeSH
- akcelerometrie veterinární MeSH
- divoká zvířata MeSH
- hospodářská zvířata MeSH
- prasata MeSH
- Sus scrofa * MeSH
- zrychlení MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
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.
Agricultural Centre Baden Württemberg Wildlife Research Unit Aulendorf Germany
Animal Health Research Centre 28130 Valdeolmos Madrid Spain
Centre for the Advanced Study of Collective Behaviour University of Konstanz Konstanz Germany
Department of Migration Max Planck Institute of Animal Behaviour Radolfzell Germany
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Morens DM, Folkers GK, Fauci AS. 2004. The challenge of emerging and re-emerging infectious diseases. Nature 430, 242-249. (10.1038/nature02759) PubMed DOI PMC
Terrestrial Code Online Access. 2023. WOAH: World Organization for Animal Health. See https://www.woah.org/en/what-we-do/standards/codes-and-manuals/terrestrial-code-online-access/ (accessed 12 June 2023).
Brückner G, et al. . 2014. Guide to terrestrial animal health surveillance. Paris, France: OIE. See https://agritrop.cirad.fr/578667/ (accessed 24 February 2022).
Licoppe A, De Waele V, Malengreaux C, Paternostre J, Van Goethem A, Desmecht D, Herman M, Linden A. 2023. Management of a focal introduction of ASF virus in wild boar: the Belgian experience. Pathogens 12, 152. (10.3390/pathogens12020152) PubMed DOI PMC
Rietz J, et al. 2023. Drone-based thermal imaging in the detection of wildlife carcasses and disease management. Transbound. Emerg. Dis. 2023, e5517000. (10.1155/2023/5517000) DOI
Allepuz A, Hovari M, Masiulis M, Ciaravino G, Beltrán-Alcrudo D. 2022. Targeting the search of African swine fever-infected wild boar carcasses: a tool for early detection. Transbound. Emer. Dis. 69, e1682-e1692. (10.1111/tbed.14504) PubMed DOI PMC
Halliday JEB, Meredith AL, Knobel DL, Shaw DJ, Bronsvoort BdC, Cleaveland S. 2007. A framework for evaluating animals as sentinels for infectious disease surveillance. J. R. Soc. Interface 4, 973-984. (10.1098/rsif.2007.0237) PubMed DOI PMC
Committee on Animals as Monitors of Environmental Hazards. 1991. Animals as sentinels of environmental health hazards. Washington, DC: National Academies Press. See http://www.ncbi.nlm.nih.gov/books/NBK234944/ (accessed 2 June 2022). PubMed
McCluskey BJ. 2003. Use of sentinel herds in monitoring and surveillance systems. In Animal disease surveillance and survey systems (ed. Salman MD), pp. 119-133. Ames, IA: Blackwell. See https://onlinelibrary.wiley.com/doi/abs/10.1002/9780470344866.ch8.
Wikelski M, et al. 2020. Potential short-term earthquake forecasting by farm animal monitoring. Ethology 126, 931-941. (10.1111/eth.13078) DOI
Kays R, Crofoot MC, Jetz W, Wikelski M. 2015. Terrestrial animal tracking as an eye on life and planet. Science 348, aaa2478. (10.1126/science.aaa2478) PubMed DOI
Williams HJ, Shipley JR, Rutz C, Wikelski M, Wilkes M, Hawkes LA. 2021. Future trends in measuring physiology in free-living animals. Phil. Trans. R. Soc. B 376, 20200230. (10.1098/rstb.2020.0230) PubMed DOI PMC
Brown DD, Kays R, Wikelski M, Wilson R, Klimley AP. 2013. Observing the unwatchable through acceleration logging of animal behavior. Anim. Biotelemetry 1, 20. (10.1186/2050-3385-1-20) DOI
Williams HJ, et al. 2020. Optimizing the use of biologgers for movement ecology research. J. Anim. Ecol. 89, 186-206. (10.1111/1365-2656.13094) PubMed DOI PMC
Adelman JS, Córdoba-Córdoba S, Spoelstra K, Wikelski M, Hau M. 2010. Radiotelemetry reveals variation in fever and sickness behaviours with latitude in a free-living passerine. Funct. Ecol. 24, 813-823. (10.1111/j.1365-2435.2010.01702.x) DOI
Chapa JM, Maschat K, Iwersen M, Baumgartner J, Drillich M. 2020. Accelerometer systems as tools for health and welfare assessment in cattle and pigs: a review. Behav. Processes 181, 104262. (10.1016/j.beproc.2020.104262) PubMed DOI
Tobin C, Bailey DW, Trotter MG, O'Connor L. 2020. Sensor based disease detection: a case study using accelerometers to recognize symptoms of Bovine Ephemeral Fever. Comput. Electron. Agric. 175, 105605. (10.1016/j.compag.2020.105605) DOI
Wilson RP, et al. 2014. Wild state secrets: ultra-sensitive measurement of micro-movement can reveal internal processes in animals. Front. Ecol. Environ. 12, 582-587. (10.1890/140068) DOI
Hart BL. 1988. Biological basis of the behavior of sick animals. Neurosci. Biobehav. Rev. 12, 123-137. (10.1016/S0149-7634(88)80004-6) PubMed DOI
Benjamin M, Yik S. 2019. Precision livestock farming in swine welfare: a review for swine practitioners. Animals (Basel) 9, 133. (10.3390/ani9040133) PubMed DOI PMC
Stachowicz J, Umstätter C. 2021. Do we automatically detect health- or general welfare-related issues? A framework. Proc. R. Soc. B 288, 20210190. (10.1098/rspb.2021.0190) PubMed DOI PMC
Virgilio Ad, Morales JM, Lambertucci SA, Shepard ELC, Wilson RP. 2018. Multi-dimensional precision livestock farming: a potential toolbox for sustainable rangeland management. PeerJ 6, e4867. (10.7717/peerj.4867) PubMed DOI PMC
Rabinowitz PM, Gordon Z, Holmes R, Taylor B, Wilcox M, Chudnov D, Nadkarni P, Dein FJ. 2005. Animals as sentinels of human environmental health hazards: an evidence-based analysis. EcoHealth 2, 26-37. (10.1007/s10393-004-0151-1) DOI
Netherton CL, Connell S, Benfield CTO, Dixon LK. 2019. The genetics of life and death: virus-host interactions underpinning resistance to African swine fever, a viral hemorrhagic disease. Front. Genetics 10, 402. (10.3389/fgene.2019.00402) PubMed DOI PMC
Morelle K, Bubnicki J, Churski M, Gryz J, Podgórski T, Kuijper DPJ. 2020. Disease-induced mortality outweighs hunting in causing wild boar population crash after African swine fever outbreak. Front. Vet. Sci. 7, 378. (10.3389/fvets.2020.00378) PubMed DOI PMC
Berthe F. 2020. The global economic impact of ASF. Paris, France: World Organization for Animal Health.
Kivumbi CC, Yona C, Hakizimana JN, Misinzo G. 2021. An assessment of the epidemiology and socioeconomic impact of the 2019 African swine fever outbreak in Ngara district, western Tanzania. Veterinary Anim. Sci. 14, 100198. (10.1016/j.vas.2021.100198) PubMed DOI PMC
Gavier-Widén D, Ståhl K, Neimanis AS, Hård av Segerstad C, Gortázar C, Rossi S, Kuiken T. 2015. African swine fever in wild boar in Europe: a notable challenge. Vet. Rec. 176, 199-200. (10.1136/vr.h699) PubMed DOI
Rodríguez-Bertos A, et al. 2020. Clinical course and gross pathological findings in wild boar infected with a highly virulent strain of African swine fever virus genotype II. Pathogens 9, 688. (10.3390/pathogens9090688) PubMed DOI PMC
Halsey LG, Shepard ELC, Wilson RP. 2011. Assessing the development and application of the accelerometry technique for estimating energy expenditure. Comp. Biochem. Physiol. A: Mol. Integr. Physiol. 158, 305-314. (10.1016/j.cbpa.2010.09.002) PubMed DOI
Gleiss AC, Wilson RP, Shepard ELC. 2011. Making overall dynamic body acceleration work: on the theory of acceleration as a proxy for energy expenditure. Methods Ecol. Evol. 2, 23-33. (10.1111/j.2041-210X.2010.00057.x) DOI
Wilson RP, McMahon CR. 2006. Measuring devices on wild animals: what constitutes acceptable practice? Front. Ecol. Environ. 4, 147-154. (10.1890/1540-9295(2006)004[0147:MDOWAW]2.0.CO;2) DOI
Muggeo VMR. 2003. Estimating regression models with unknown break-points. Stat. Med. 22, 3055-3071. (10.1002/sim.1545) PubMed DOI
Lindeløv JK. 2020. mcp: an R package for regression with multiple change points. (10.31219/osf.io/fzqxv) DOI
Heck DW. 2019. A caveat on the Savage–Dickey density ratio: the case of computing Bayes factors for regression parameters. Br. J. Math. Stat. Psychol. 72, 316-333. (10.1111/bmsp.12150) PubMed DOI
Verdinelli I, Wasserman L. 1995. Computing Bayes factors using a generalization of the Savage-Dickey density ratio. J. Am. Stat. Assoc. 90, 614-618. (10.1080/01621459.1995.10476554) DOI
Chenais E, Depner K, Guberti V, Dietze K, Viltrop A, Ståhl K. 2019. Epidemiological considerations on African swine fever in Europe 2014–2018. Porcine Health Manage. 5, 6. (10.1186/s40813-018-0109-2) PubMed DOI PMC
Schulz K, Masiulis M, Staubach C, Malakauskas A, Pridotkas G, Conraths FJ, Sauter-Louis C. 2021. African swine fever and its epidemiological course in Lithuanian wild boar. Viruses 13, 1276. (10.3390/v13071276) PubMed DOI PMC
Binning SA, Shaw AK, Roche DG. 2017. Parasites and host performance: incorporating infection into our understanding of animal movement. Integr. Comp. Biol. 57, 267-280. (10.1093/icb/icx024) PubMed DOI
Fernández-Carrión E, Barasona JÁ, Sánchez Á, Jurado C, Cadenas-Fernández E, Sánchez-Vizcaíno JM. 2020. Computer vision applied to detect lethargy through animal motion monitoring: a trial on African swine fever in wild boar. Animals 10, 2241. (10.3390/ani10122241) PubMed DOI PMC
Martínez-Avilés M, Fernández-Carrión E, García-Baones JML, Sánchez-Vizcaíno JM. 2017. Early detection of infection in pigs through an online monitoring system. Transbound. Emerg. Dis. 64, 364-373. (10.1111/tbed.12372) PubMed DOI
Arkwright AC, et al. 2020. Behavioral biomarkers for animal health: a case study using animal-attached technology on loggerhead turtles. Front. Ecol. Evol. 7, 504. (10.3389/fevo.2019.00504) DOI
Greenwood EC, Plush KJ, van Wettere WHEJ, Hughes PE. 2014. Hierarchy formation in newly mixed, group housed sows and management strategies aimed at reducing its impact. Appl. Anim. Behav. Sci. 160, 1-11. (10.1016/j.applanim.2014.09.011) DOI
Wolfson DW, Andersen DE, Fieberg JR. 2022. Using piecewise regression to identify biological phenomena in biotelemetry datasets. J. Anim. Ecol. 91, 1755-1769. (10.1111/1365-2656.13779) PubMed DOI PMC
Oczak M, Bayer F, Vetter S, Maschat K, Baumgartner J. 2022. Comparison of the automated monitoring of the sow activity in farrowing pens using video and accelerometer data. Comput. Electron. Agric. 192, 106517. (10.1016/j.compag.2021.106517) DOI
Scheel C, Traulsen I, Auer W, Müller K, Stamer E, Krieter J. 2017. Detecting lameness in sows from ear tag-sampled acceleration data using wavelets. Animal 11, 2076-2083. (10.1017/S1751731117000726) PubMed DOI
Dougherty ER, Seidel DP, Carlson CJ, Spiegel O, Getz WM. 2018. Going through the motions: incorporating movement analyses into disease research. Ecol. Lett. 21, 588-604. (10.1111/ele.12917) PubMed DOI
McElroy EJ, Buron Id. 2014. Host performance as a target of manipulation by parasites: a meta-analysis. J. Parasitol. 100, 399-410. (10.1645/13-488.1) PubMed DOI
Thomas F, Schmidt-Rhaesa A, Martin G, Manu C, Durand P, Renaud F. 2002. Do hairworms (Nematomorpha) manipulate the water seeking behaviour of their terrestrial hosts? J. Evol. Biol. 15, 356-361. (10.1046/j.1420-9101.2002.00410.x) DOI
Stafford CA, Walker GP, Ullman DE. 2011. Infection with a plant virus modifies vector feeding behavior. Proc. Natl Acad. Sci. USA 108, 9350-9355. (10.1073/pnas.1100773108) PubMed DOI PMC
Wild TA, Wikelski M, Tyndel S, Alarcón-Nieto G, Klump BC, Aplin LM, Meboldt M, Williams HJ. et al. 2023. Internet on animals: Wi-Fi-enabled devices provide a solution for big data transmission in biologging. Methods Ecol. Evol. 14, 87-102. (10.1111/2041-210X.13798) DOI
Yu H, Deng J, Leen T, Li G, Klaassen M. 2022. Continuous on-board behaviour classification using accelerometry: a case study with a new GPS-3G-Bluetooth system in Pacific black ducks. Methods Ecol. Evol. 13, 1429-1435. (10.1111/2041-210X.13878) DOI
Kosowska A, Cadenas-Fernández E, Barroso S, Sánchez-Vizcaíno JM, Barasona JA. 2020. Distinct African swine fever virus shedding in wild boar infected with virulent and attenuated isolates. Vaccines 8, 767. (10.3390/vaccines8040767) PubMed DOI PMC
Thumbi SM, Njenga MK, Otiang E, Otieno L, Munyua P, Eichler S, Widdowson MA, McElwain TF, Palmer GH. 2019. Mobile phone-based surveillance for animal disease in rural communities: implications for detection of zoonoses spillover. Phil. Trans. R. Soc. B 374, 20190020. (10.1098/rstb.2019.0020) PubMed DOI PMC
Lawson B, Petrovan SO, Cunningham AA. 2015. Citizen science and wildlife disease surveillance. EcoHealth 12, 693-702. (10.1007/s10393-015-1054-z) PubMed DOI
Kays R, Wikelski M. 2023. The Internet of Animals: what it is, what it could be. Trends Ecol. Evol. 38, 859-869. (10.1016/j.tree.2023.04.007) PubMed DOI
de Knegt HJ, Eikelboom JAJ, van Langevelde F, Spruyt WF, Prins HHT. 2021. Timely poacher detection and localization using sentinel animal movement. Sci. Rep. 11, 4596. (10.1038/s41598-021-83800-1) PubMed DOI PMC
Wild TA, et al. 2023. A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network. Anim. Biotelemetry 11, 13. (10.1186/s40317-023-00326-1) PubMed DOI PMC
Morelle K. 2023. Wild boar accelerometer sensors data. See https://datadryad.org/stash/share/rlAe9c47aD4VOUy_qMTblezVZCw7qoTW2t0rHYzA7Ic.
Morelle K, et al. . 2023. Accelerometer-based detection of African swine fever infection in wild boar. Figshare. (10.6084/m9.figshare.c.6778105) PubMed DOI PMC
Accelerometer-based detection of African swine fever infection in wild boar