Abstract
Prevention and control of production diseases requires a profound knowledge on the epidemiology of the respective disease or disease complex. The objective of this chapter is therefore to introduce important epidemiological concepts and their application to production diseases. When investigating the causal factors which lead to production disease, it is important to keep in mind that, by definition, production diseases are not caused by a single pathogen or factor but rather by a combination of component causes and factors predisposing for disease. Causality should therefore be defined as a range of evidence rather than a direct relation between a factor and disease.
Methods of descriptive epidemiology are an important basis to understand disease. Frequency of disease should be expressed in relation to the population at risk, as an incidence or prevalence. Describing the distribution of disease over time and location is helpful for forming hypotheses on factors contributing to disease risk. Many epidemiological methods exist for analyzing associations between disease and risk factors. These methods range from simple descriptive measures such as relative risk and odds ratios to statistical models such as regression models and more advanced methodologies such as Bayesian methods and machine learning algorithms. For production diseases with infectious etiology, methods from infectious disease epidemiology such as SIR (susceptible-infectious-resistant) models, agent-based models, or network models can also be applied.
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References
Barlow JW, Zadoks RN, Schukken YH (2013) Effect of lactation therapy on Staphylococcus aureus transmission dynamics in two commercial dairy herds. BMC Vet Res 9. https://doi.org/10.1186/1746-6148-9-28
Bassett J, Gethmann J, Blunk P et al (2021) Individual-based model for the control of Bovine Viral Diarrhea spread in livestock trade networks. J Theor Biol 527. https://doi.org/10.1016/j.jtbi.2021.110820
Browne N, Hudson CD, Crossley RE et al (2022) Cow- and herd-level risk factors for lameness in partly housed pasture-based dairy cows. J Dairy Sci 105:1418–1431. https://doi.org/10.3168/jds.2021-20767
Clark B, Stewart GB, Panzone LA et al (2016) A systematic review of public attitudes, perceptions and behaviours towards production diseases associated with farm animal welfare. J Agric Environ Ethics 29:455–478. https://doi.org/10.1007/s10806-016-9615-x
Dalen G, Rachah A, Nørstebø H et al (2018) Transmission dynamics of intramammary infections caused by Corynebacterium species. J Dairy Sci 101:472–479. https://doi.org/10.3168/jds.2017-13162
Deng Z, Koop G, Hogeveen H et al (2021) Transmission dynamics of Staphylococcus aureus and Streptococcus agalactiae in a Dutch dairy herd using an automatic milking system. Prev Vet Med 192. https://doi.org/10.1016/j.prevetmed.2021.105384
Dohoo L, Martin W, Stryhn H (2003) Veterinary epidemiologic research. National Library of Canada, Canada. https://projects.upei.ca/ver/
Ebrahimi M, Mohammadi-Dehcheshmeh M, Ebrahimie E, Petrovski KR (2019) Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: deep learning and gradient-boosted trees outperform other models. Comput Biol Med 114. https://doi.org/10.1016/j.compbiomed.2019.103456
FAO (2022) Animal health. In: Gateway to dairy production and products. https://www.fao.org/dairy-production-products/production/animal-health/en/. Accessed 2 June 2022
Frérot M, Lefebvre A, Aho S et al (2018) What is epidemiology? Changing definitions of epidemiology 1978-2017. PLoS One 13
Hartnack S, Odoch T, Kratzer G et al (2019) Additive Bayesian networks for antimicrobial resistance and potential risk factors in non-typhoidal Salmonella isolates from layer hens in Uganda. BMC Vet Res 15. https://doi.org/10.1186/s12917-019-1965-y
Horpiencharoen W, Thongratsakul S, Poolkhet C (2019) Risk factors of clinical mastitis and antimicrobial susceptibility test results of mastitis milk from dairy cattle in western Thailand: Bayesian network analysis. Prev Vet Med 164:49–55. https://doi.org/10.1016/j.prevetmed.2019.01.014
Kirkeby C, Zervens L, Toft N et al (2019) Transmission dynamics of Staphylococcus aureus within two Danish dairy cattle herds. J Dairy Sci 102:1428–1442. https://doi.org/10.3168/jds.2018-15106
Landers TF, Cohen B, Wittum TE, Larson EL (2012) A review of antibiotic use in food animals: perspective, policy, and potential. Public Health Rep 127:4–22. https://doi.org/10.1177/003335491212700103
Lebl K, Lentz HHK, Pinior B, Selhorst T (2016) Impact of network activity on the spread of infectious diseases through the German pig trade network. Front Vet Sci 3. https://doi.org/10.3389/fvets.2016.00048
Ni H, Klugkist I, van der Drift S et al (2021) Expert opinion as priors for random effects in Bayesian prediction models: subclinical ketosis in dairy cows as an example. PLoS One 16. https://doi.org/10.1371/journal.pone.0244752
Nir O (2003) What are production diseases, and how do we manage them? Acta Vet Scand Suppl 98:21–32
Shimonovich M, Pearce A, Thomson H et al (2021) Assessing causality in epidemiology: revisiting Bradford Hill to incorporate developments in causal thinking. Eur J Epidemiol 36:873–887. https://doi.org/10.1007/s10654-020-00703-7
Snijders T, Bosker R (2012) Multilevel analysis: an introduction to basic and advanced multilevel modeling, second edn. Sage Publishers, London etc.
Thrusfield M, Christley R, Brown H, Diggle P, French N, Howe K, Kelly L, O’Connor A, Sargeant J, Wood H (2018) Veterinary epidemiology. John Wiley & Sons Ltd. https://doi.org/10.1002/9781118280249
Verteramo Chiu LJ, Tauer LW, Al-Mamun MA et al (2018) An agent-based model evaluation of economic control strategies for paratuberculosis in a dairy herd. J Dairy Sci 101:6443–6454. https://doi.org/10.3168/jds.2017-13175
Zingg D, Steinbach S, Kuhlgatz C et al (2017) Epidemiological and economic evaluation of alternative on-farm management scenarios for ovine footrot in Switzerland. Front Vet Sci 4. https://doi.org/10.3389/fvets.2017.00070
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Schüpbach-Regula, G. (2024). Epidemiology of Production Diseases. In: Gross, J.J. (eds) Production Diseases in Farm Animals. Springer, Cham. https://doi.org/10.1007/978-3-031-51788-4_1
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DOI: https://doi.org/10.1007/978-3-031-51788-4_1
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