A framework for handling uncertainty in a large-scale programme estimating the Global Burden of Animal Diseases

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cg.authorship.typesCGIAR and developing country instituteen
cg.authorship.typesCGIAR and advanced research instituteen
cg.contributor.affiliationUniversity of Liverpoolen
cg.contributor.affiliationLancaster Universityen
cg.contributor.affiliationUniversity of Floridaen
cg.contributor.affiliationNewcastle Universityen
cg.contributor.affiliationWashington State Universityen
cg.contributor.affiliationInternational Livestock Research Instituteen
cg.contributor.affiliationUniversity of Gondaren
cg.contributor.affiliationUniversity of Guelphen
cg.contributor.donorGates Foundationen
cg.contributor.donorForeign, Commonwealth and Development Office, United Kingdomen
cg.creator.identifierWudu Temesgen Jemberu: 0000-0002-3769-307Xen
cg.howPublishedFormally Publisheden
cg.identifier.doihttps://doi.org/10.3389/fvets.2025.1459209en
cg.isijournalISI Journalen
cg.issn2297-1769en
cg.journalFrontiers in Veterinary Scienceen
cg.reviewStatusPeer Reviewen
cg.subject.ilriANIMAL DISEASESen
cg.subject.ilriANIMAL HEALTHen
cg.subject.impactAreaNutrition, health and food security
cg.subject.sdgSDG 2 - Zero hungeren
cg.volume12en
dc.contributor.authorClough, H.E.en
dc.contributor.authorChaters, G.L.en
dc.contributor.authorHavelaar, A.H.en
dc.contributor.authorMcIntyre, K.M.en
dc.contributor.authorMarsh, T.L.en
dc.contributor.authorHughes, E.C.en
dc.contributor.authorJemberu, Wudu T.en
dc.contributor.authorStacey, D.en
dc.contributor.authorAfonso, J.S.en
dc.contributor.authorGilbert, W.en
dc.contributor.authorRaymond, K.en
dc.contributor.authorRushton, J.en
dc.date.accessioned2025-03-10T11:16:06Zen
dc.date.available2025-03-10T11:16:06Zen
dc.identifier.urihttps://hdl.handle.net/10568/173537
dc.titleA framework for handling uncertainty in a large-scale programme estimating the Global Burden of Animal Diseasesen
dcterms.abstractLivestock provide nutritional and socio-economic security for marginalized populations in low and middle-income countries. Poorly-informed decisions impact livestock husbandry outcomes, leading to poverty from livestock disease, with repercussions on human health and well-being. The Global Burden of Animal Diseases (GBADs) programme is working to understand the impacts of livestock disease upon human livelihoods and livestock health and welfare. This information can then be used by policy makers operating regionally, nationally and making global decisions. The burden of animal disease crosses many scales and estimating it is a complex task, with extensive requirements for data and subsequent data synthesis. Some of the information that livestock decision-makers require is represented by quantitative estimates derived from field data and models. Model outputs contain uncertainty, arising from many sources such as data quality and availability, or the user’s understanding of models and production systems. Uncertainty in estimates needs to be recognized, accommodated, and accurately reported. This enables robust understanding of synthesized estimates, and associated uncertainty, providing rigor around values that will inform livestock management decision-making. Approaches to handling uncertainty in models and their outputs receive scant attention in animal health economics literature; indeed, uncertainty is sometimes perceived as an analytical weakness. However, knowledge of uncertainty is as important as generating point estimates. Motivated by the context of GBADs, this paper describes an analytical framework for handling uncertainty, emphasizing uncertainty management, and reporting to stakeholders and policy makers. This framework describes a hierarchy of evidence, guiding movement from worst to best-case sources of information, and suggests a stepwise approach to handling uncertainty in estimating the global burden of animal disease. The framework describes the following pillars: background preparation; models as simple as possible but no simpler; assumptions documented; data source quality ranked; commitment to moving up the evidence hierarchy; documentation and justification of modelling approaches, data, data flows and sources of modelling uncertainty; uncertainty and sensitivity analysis on model outputs; documentation and justification of approaches to handling uncertainty; an iterative, up-to-date process of modelling; accounting for accuracy of model inputs; communication of confidence in model outputs; and peer-review.en
dcterms.accessRightsOpen Access
dcterms.audienceAcademicsen
dcterms.audienceScientistsen
dcterms.available2025-03-07en
dcterms.bibliographicCitationClough, H.E., Chaters, G.L., Havelaar, A.H., McIntyre, K.M., Marsh, T.L., Hughes, E.C., Jemberu, W.T., Stacey, D., Afonso, J.S., Gilbert, W., Raymond, K. and Rushton, J. 2025. A framework for handling uncertainty in a large-scale programme estimating the Global Burden of Animal Diseases. Frontiers in Veterinary Science 12: 1459209.en
dcterms.extent1459209en
dcterms.issued2025-03-07en
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherFrontiers Mediaen
dcterms.subjectanimal diseasesen
dcterms.subjectanimal healthen
dcterms.typeJournal Article

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