Global Burden of Animal Diseases

Permanent URI for this collectionhttps://hdl.handle.net/10568/111549

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Economic burden of foot-and-mouth disease outbreaks on farmers and national economies
(Presentation, 2025-06-03) Knight-Jones, Theodore J.D.; Jemberu, Wudu T.; Rushton, J.
Farm-level livestock loss and risk factors in Ethiopian livestock production systems
(Journal Article, 2025-06-03) Yin Li; Jemberu, Wudu T.; Mayberry, D.
This study aims to explore farm-level losses of cattle, goats and sheep and relevant risk factors in the mixed crop-livestock and pastoral production systems in Ethiopia. Data from 1,528 cattle farms, 868 goat farms and 749 sheep farms, spanning the year 2018/19, were analysed in this study. A farm was defined as a case farm if it lost at least one cattle/goat/sheep in the past 12 months. The 12-month incidence of livestock loss was calculated for each region and production system. Logistic regression analysis was employed to assess risk factors contributing to livestock loss in the farms. Forty-five percent of goat farms, 36% of sheep farms and 23% of cattle farms reported losing at least one animal in the past 12 months. Cattle loss in the pastoral system was associated with not using vaccines (Odds Ratio = 7, P < 0.01). In the mixed crop-livestock system cattle loss was associated with the absence of a roofed house (Odds Ratio = 1.40, P < 0.05). Risk factors for goat loss in the mixed crop-livestock system were selling live goats in the past 12 months (Odds Ratio = 1.58, P < 0.05). For sheep loss in the pastoral system, the identified risk factor was having cattle on farm (Odds Ratio = 2.40, P < 0.05). These findings provide valuable insights into the scale and the drivers of livestock loss within the major cattle and small ruminants production systems in Ethiopia.
Economic impact analysis of PPR—Global burden of animal diseases’ (GBADs’) approach
(Presentation, 2025-05-12) Temesgen, Wudu; Knight-Jones, Theodore J.D.
A framework for handling uncertainty in a large-scale programme estimating the Global Burden of Animal Diseases
(Journal Article, 2025-03-07) Clough, H.E.; Chaters, G.L.; Havelaar, A.H.; McIntyre, K.M.; Marsh, T.L.; Hughes, E.C.; Jemberu, Wudu T.; Stacey, D.; Afonso, J.S.; Gilbert, W.; Raymond, K.; Rushton, J.
Livestock 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.
The one-humped wonder: Ethiopia’s camels in focus
(News Item, 2024-06-25) Megersa, B.; Amenu, Kebede; Knight-Jones, Theodore J.D.; Jemberu, Wudu T.
As the United Nations marks 2024 as the International Year of Camelids, we explore some key facts about Ethiopia’s camels, and their crucial but underappreciated role in supporting livelihoods and food security in the face of climate change.
Economic assessment of animal disease burden in Senegalese small ruminants
(Journal Article, 2025-01) Meyer, Anne; Ndiaye, Bakary; Larkins, Andrew; Chaters, G.; Gilbert, W.; Huntington, Benjamin; Ilboudo, Guy S.; Dione, Michel M.; Jemberu, Wudu T.; Diouf, M.N.; Fall, A.G.; Fall, M.; Lo, M.; Rushton, Jonathan
Small ruminant production in sub-Saharan Africa is limited by a range of constraints, including animal health issues. This study aimed at estimating the impact of these issues on the small ruminant production in Senegal in a holistic manner, using an approach developed by the Global Burden of Animal Diseases (GBADs) programme. The estimation focused on the mixed crop-livestock system, representing a large proportion (>60%) of the small ruminant population in the country. It was based on existing data collected via a systematic literature review, acquisition of secondary datasets from local stakeholders, and expert elicitation. A dynamic population model was used to calculate the gross margin of the sector under both the current health constraints and an ideal health state, where animals are not exposed to causes of morbidity and mortality. The difference between the current and ideal health scenarios, termed the Animal Health Loss Envelope (AHLE), provides a quantitative measure of the farm-level cost of disease in the system. The all-cause AHLE was estimated at 292 billion FCFA (468 million USD, with 95% prediction interval 216 – 366 billion FCFA) per year for 2022, for a population of 8.8 million animals. The contribution of Peste des Petits Ruminants (PPR) was modelled separately, as an example of attributing part of the AHLE to a specific disease cause. PPR was estimated to contribute 5% of the total AHLE. The animal disease burden experienced by Senegalese livestock keepers was largely due to loss in animals and production, with relatively small amounts of animal health expenditure. Implementation of this study contributed to the further development of the GBADs approach. Such estimates can support decision making at all levels, from investment decisions at the international level to local disease awareness campaigns targeting livestock keepers.
Global Burden of Animal Diseases: Ethiopia case study phase II closing stakeholder workshop
(Report, 2024-08-30) Temesgen, Wudu; Huntington, B.; Knight-Jones, Theodore J.D.
Prioritization, resource allocation and utilization of decision support tools in animal health: Results of qualitative interviews with experts
(Journal Article, 2024-12) Amenu, Kebede; Daborn, C.; Huntington, B.; Knight-Jones, Theodore J.D.; Rushton, J.; Grace, Delia
A follow up to an online questionnaire survey (in a kind of a sequential study design), qualitative assessment was made on the views of selected animal health experts on disease prioritization methods, resource allocation and use of decision-support tools. This was done through in-depth interviews with experts working for national or international organizations and sectors. A semi-structured question guide was formulated based on the information generated in the online questionnaire and a systematic content analysis of animal and human health manuals for disease prioritization and resource allocation. In-depth, one-on-one, online interviews on the process of disease prioritization, animal health decision-making, types of prioritization tools and aspects of improvements in the tools were conducted during March and April 2022 with 20 expert informants. Prioritization approaches reported by experts were either single criterion-based or multiple criteria-based. Experts appreciated the single-criterion-based approach (quantitative) for its objectivity in contrast to multicriteria prioritization approaches which were criticized for their subjectivity. Interviews with the experts revealed a perceived lack of quality and reliable data to inform disease prioritization, especially in smallholder livestock production systems. It was found that outputs of disease prioritization exercises do not generally directly influence resource allocation in animal health and highlighted the paucity of funding for animal health compared to other agricultural sectors. The experts considered that the available decision-support tools in animal health need improvement in terms of data visualization for interpretation, management decision making and advocacy. Further recommendations include minimizing subjective biases by increasing the availability and quality of data and improving the translation of disease prioritization outputs into actions and the resources to deliver those actions.
How the Global Burden of Animal Diseases links to the Global Burden of Crop Loss: a food systems perspective
(Journal Article, 2024-08-30) Szyniszewska, A.M.; Simpkins, K.M.; Thomas, Lian F.; Beale, T.; Milne, A.E.; Brown, M.E.; Taylor, B.; Oliver, G.; Bebber, D.P.; Woolman, T.; Mahmood, S.; Murphy, C.; Huntington, B.; Finegold, C.
Food systems comprise interconnected webs of processes that together transform inputs (land, labour, water, nutrients and genetics, to mention just a few) into outputs such as nutrition and revenue for human societies. Perfect systems do not exist; rather, global food systems operate in the presence of hazards, biotic and abiotic alike, and under the constraint of limited resources to mitigate these hazards. There are, therefore, inefficiencies in these systems, which lead to losses in terms of monetary, nutritional, health and environmental values and create additional negative externalities in the health, social and environmental spaces. Health hazards in the food system do not respect arbitrary distinctions between the crop and livestock sectors, which are highly interconnected. These linkages exist where one sector provides inputs to another or through substitution effects where supply in one sector influences demand in another. The One Health approach advocates investigating the intersectoral hazards in a highly interdisciplinary manner. This article provides a conceptual framework for integrating the methodologies developed by the Global Burden of Crop Loss and Global Burden of Animal Diseases initiatives to generate burden estimates for hazards in food systems that better account for interconnectivity and foster an improved understanding of food systems that is aligned with the interdisciplinary nature of the One Health approach. A case study related to maize and poultry sector linkages in the wider context of public and environmental health is presented.
Application of the Global Burden of Animal Diseases methods at country level: experiences of the Ethiopia case study
(Journal Article, 2024-08-30) Jemberu, Wudu T.; Chaters, G.; Asfaw, W.; Asteraye, Girma B.; Amenu, Kebede; Huntington, B.; Rushton, J.; Knight-Jones, Theodore J.D.
Animals play a central role in human livelihoods and welfare. Animal diseases have a great impact on the benefits humans derive from animals and can also pose a risk to human health. Better control of animal diseases generates wider societal benefits, including reducing the climate and ecological impacts of livestock and improving animal welfare. To better understand the scale of investment justified for the control and prevention of animal disease, the wide-ranging impacts of disease on animal production and health must be measured. The Global Burden of Animal Diseases (GBADs) programme is quantifying animal disease burden from the local to global levels. The GBADs programme includes country case studies for national- and local-level analysis. Ethiopia is the first case study country in which GBADs methods have been applied. GBADs’ Ethiopia case study consists of three activity areas: i) stakeholder engagement; ii) livestock disease burden estimation, including data collection, analytics, evidence generation and communication; and iii) capacity building in animal health economics. At the start of the case study, various stakeholder communication platforms were used to familiarise stakeholders with GBADs and engage their support in various ways, including data access, and, through this engagement, to ensure the programme tools and outputs were relevant and useful to their needs. Existing data were retrieved from multiple sources and used to estimate disease burden. This process involved multiple steps, including estimation of biomass and economic value, the Animal Health Loss Envelope (farm-level disease burden), wider economic impacts and attribution of the disease burden to different levels of causes. This was carried out for major livestock species (cattle, sheep, goats and poultry) in Ethiopia. Capacity building on animal health economics was carried out for GBADs end users to increase competence in utilising animal health economic evidence, including GBADs outputs. This article documents experiences of the implementation of these activities in the GBADs Ethiopia case study.
A methodological framework for attributing the burden of animal disease to specific causes
(Journal Article, 2024-08-30) Bruce, M.; Jemberu, Wudu T.; Larkins, A.J.
The Global Burden of Animal Diseases provides an analytical framework to measure the overall health of various farmed animal populations, to estimate the farm-level burden of different diseases, incorporating production losses due to morbidity and mortality as well as health expenditure, and to identify the wider economic and human health impacts of animal disease. Attributing the burden of animal diseases to specific causes or groups of causes requires methodological choices, including the classification of diseases and the resulting health states that manifest in loss of production. The aim of this article is to address the key challenges in the process of estimating farm-level disease burden, including ambiguity in terminology, data availability and collation, and adjustments for comorbidity. Using infection with zoonotic Brucella spp. in small ruminants as an aetiological cause of disease and abortion as a sequela of multiple diseases, practical examples of the framework are provided. Cause-specific attribution of the burden of animal disease captures temporal and spatial trends, an understanding of which is essential for planning, monitoring and evaluating animal health programmes and disease interventions.
Understanding decision-makers and their needs: framing Global Burden of Animal Diseases offerings to enhance relevance and increase impact
(Journal Article, 2024-08-30) Smith, D.; Cooper, T.L.; Utomo, B.N.; Wiyono, A.; Kusumaningtyas, E.; Endrawati, D.; Adji, R.S.; Tenzin, G.; Nuradji, H.; Dharmayanti, N.L.P.I.; Grace, Delia
In a world characterised by data deserts and data swamps, translating evidence into actionable policies and practices is not easy. This article addresses this challenge through the lens of evidence emerging from the Global Burden of Animal Diseases (GBADs) initiative. It emphasises the need for an intentional approach that connects research information with the specific needs of decision-makers and identifies specific impact pathways associated with different groups of decision-makers. The GBADs programme aims to support animal health decisions, and the authors outline the diverse landscape of decision-makers in this field, encompassing the public and private sectors, livestock keepers, civil society and international development agencies. Key issues such as disease prioritisation and lobbying are also discussed. The authors propose an ‘evidence ecosystem’ approach, one that understands data users and their interactions, for analysing the needs of decision-makers, and framing GBADs offerings according to these needs. Two case studies, a recently concluded global case study of disease prioritisation decision-making and an ongoing policy analysis and needs assessment for GBADs in Indonesia, are presented to demonstrate how evidence ecosystem analysis and audience segmentation could be used to tailor GBADs information offerings for different decision-making groups. The article concludes by recommending that GBADs’ future applications prioritise information offerings, adapt them to decision-makers’ needs and consider how different segments of decision-makers will utilise the information to achieve real-world impacts.
Camels in Ethiopia: An overview of demography, productivity, socio-economic value and diseases
(Report, 2024-07-30) Megersa, Bekele; Temesgen, Wudu; Amenu, Kebede; Asfaw, Wondwosen; Gizaw, Solomon; Yussuf, Buke; Knight-Jones, Theodore J.D.
Economic losses due to foot-and-mouth disease (FMD) in Ethiopian cattle
(Journal Article, 2024-09) Rasmussen, P.; Shaw, A.P.; Jemberu, Wudu T.; Knight-Jones, Theodore J.D.; Conrady, B.; Apenteng, O.O.; Cheng, Y.; Muñoz, V.; Rushton, J.; Torgerson, P.R.
Ethiopia’s cattle population is among the largest in Africa and is burdened by frequent foot-and-mouth disease (FMD) outbreaks each year. FMD is caused by several distinct and highly contagious viral strains that can result in acute disease in cattle, causing losses in productivity and impeding international trade. This economic simulation study considered four main sources of losses due to FMD in cattle: reduced milk yield, draft power yield, fertility, and increased mortality. Economic losses were estimated per case across age-sex strata in 89 Ethiopian administrative zones for the years 2010 to 2021 using a wide range of data to estimate distributions for 30 input variables in a series of Monte Carlo simulations. It was estimated that an average case of FMD in Ethiopian cattle results in losses (mean values reported followed 95% confidence intervals in brackets) of US dollars (USD) 11 (USD 7 – USD 16) per case. Losses resulting from an average outbreak were estimated to be USD 2,300 (USD 1,400 – USD 3,300), while national annual losses were estimated to be USD 0.9 Mil. (USD 0.2 Mil. – USD 2.3 Mil.). Per cow-year, based on a national cow population of approximately 39 Mil. head, these estimated annual losses are equivalent to losses of only USD 0.02 (USD 0.01 – USD 0.06). Nationally, these losses were significantly less than previously estimated in the literature. Sensitivity analyses suggested losses would be far greater in intensive systems and that certainty surrounding incidence rates is paramount to the formulation of economically sound animal health policy in regions with endemic FMD.
Enhancing evidence-informed decision-making in Ethiopia's animal health sector with Global Burden of Animal Diseases support: Game learning of evidence ecosystem
(Report, 2024-04) Dinede, Getachew; Keba, Abdi; Amenu, Kebede; Makau, D.; Grace, Delia
This report presents the findings from two workshops. In the first workshop held on 15 April 2024, participants answered survey questions designed to assess their institutes' evidence ecosystems, including evidence production and use of evidence for planning, resource allocation, and implementation of various activities. They also answered questions related to identifying the factors that facilitate and hinder the use of evidence in their institutes. In the second workshop held on 16 April 2024, participants worked on simulation exercises related to the management of Rift Valley fever outbreak progressions.
Quantifying cost of disease in livestock: a new metric for the Global Burden of Animal Diseases
(Journal Article, 2024-05) Gilbert, W.; Marsh, T.L.; Chaters, G.; Jemberu, Wudu T.; Bruce, M.; Steeneveld, W.; Afonso, J.S.; Huntington, B.; Rushton, J.
Background: Increasing awareness of the environmental and public health impacts of expanding and intensifying animal-based food and farming systems creates discord, with the reliance of much of the world's population on animals for livelihoods and essential nutrition. Increasing the efficiency of food production through improved animal health has been identified as a step towards minimising these negative effects without compromising global food security. The Global Burden of Animal Diseases (GBADs) programme aims to provide data and analytical methods to support positive change in animal health across all livestock and aquaculture animal populations. Methods: In this study, we present a metric that begins the process of disease burden estimation by converting the physical consequences of disease on animal performance to farm-level costs of disease, and calculates a metric termed the Animal Health Loss Envelope (AHLE) via comparison between the status quo and a disease-free ideal. An example calculation of the AHLE metric for meat production from broiler chickens is provided. Findings: The AHLE presents the direct financial costs of disease at farm-level for all causes by estimating losses and expenditure in a given farming system. The general specification of the model measures productivity change at farm-level and provides an upper bound on productivity change in the absence of disease. On its own, it gives an indication of the scale of total disease cost at farm-level. Interpretation: The AHLE is an essential stepping stone within the GBADs programme because it connects the physical performance of animals in farming systems under different environmental and management conditions and different health states to farm economics. Moving forward, AHLE results will be an important step in calculating the wider monetary consequences of changes in animal health as part of the GBADs programme.
Population, distribution, biomass, and economic value of equids in Ethiopia
(Journal Article, 2024-03-22) Asteraye, Girma B.; Pinchbeck, G.; Knight-Jones, Theodore J.D.; Saville, K.; Temesgen, Wudu; Hailemariam, A.; Rushton, J.
Background Equids play a crucial role in the Ethiopian economy, transporting agricultural inputs and outputs in the dominant subsistence agricultural systems and the critical link for value chains throughout the country. However, these species are often neglected in policies and interventions, which reflects the data and information gaps, particularly the contribution of working equids to Ethiopia. Objective To assess population dynamics, distribution, biomass, and economic value of equids in Ethiopia. Materials and methods Equine population data were obtained from the Ethiopian Central Statistics Agency (CSA) annual national agriculture surveys published yearbooks from 2004 to 2020. Parameters such as the number of effective service days and daily rental value were obtained from interviews and literature to estimate the stock monetary and service value of equids. Descriptive statistics were used to assess population dynamics and the geographical distribution was mapped. Results The estimated total Ethiopian equid population increased by more than doubled (by 131%) between 2004 and 2020 from 5.7 (4.9–6.6) million to 13.3 (11.6–15) million with 2.1 million horses, 10.7 million donkeys, and 380 thousand mules. Similarly, the number of households owning a working equid has increased. Equine populations are unevenly distributed across Ethiopia, although data were lacking in some districts of the country. The per human-capita equine population ranged from 0–0.52, 0–0.13, and 0–0.02 for donkeys, horses, and mules, respectively. The equid biomass was 7.4 (6.3–8.4) million Tropical livestock unit (TLU) (250 kg liveweight), 10% of total livestock biomass of the country. The stock monetary value of equids was USD 1,229 (651–1,908) million, accounting for 3.1% of total livestock monetary value and the services value of equids was USD 1,198 (825–1,516) million, which is 1.2% of Ethiopian 2021 expected GDP. Conclusion The Ethiopian equine population has grown steadily over the last two decades. Equids play a central role in transportation and subsistence agriculture in Ethiopia and contribute significantly to the national economy. This pivotal role is insufficiently recognized in national livestock investments.
Current and potential use of animal disease data by stakeholders in the global south and north
(Journal Article, 2024-05) Grace, Delia; Amenu, Kebede; Daborn, C.J.; Knight-Jones, Theodore J.D.; Huntington, B.; Young, S.; Poole, Elizabeth J.; Rushton, J.
What cannot be measured will not be managed. The Global Burden of Animal Diseases (GBADs) will generate information on animal disease burdens by species, production system, type and gender of farmer and consumer, geographical region, and time period. To understand the demand for burden of animal disease (BAD) data and how end-users might benefit from this, we reviewed the literature on animal diseases prioritisation processes (ADPP) and conducted a survey of BAD information users. The survey covered their current use of data and prioritizations as well as their needs for different, more, and better information. We identified representative (geography, sector, species) BAD experts from the authors’ networks and publicly available documents and e-mailed 1485 experts. Of 791 experts successfully contacted, 271 responded (34% response rate), and 185 complete and valid responses were obtained. Most respondents came from the public sector followed by academia/research, and most were affiliated to institutions in low- and middle-income countries (LMICs). Of the six ADPPs commonly featured in literature, only three were recognised by more than 40% of experts. An additional 23 ADPPs were used. Awareness of ADDPs varied significantly by respondents. Respondents ranked animal disease priorities. We used exploded logit to combine first, second and third disease priorities to better understand prioritization and their determinants. Expert priorities differed significantly from priorities identified by the ADDPs, and also from the priorities stated veterinary services as reported in a survey for a World Organisation of Animal Health (WOAH) technical item. Respondents identified 15 different uses of BAD data. The most common use was presenting evidence (publications, official reports, followed by disease management, policy development and proposal writing). Few used disease data for prioritization or resource allocation, fewer routinely used economic data for decision making, and less than half were aware of the use of decision support tools (DSTs). Nearly all respondents considered current BAD metrics inadequate, most considered animal health information insufficiently available and not evidence-based, and most expressed concerns that decision-making processes related to animal health lacked transparency and fairness. Cluster analysis suggested three clusters of BAD users and will inform DSTs to help them better meet their specific objectives. We conclude that there is a lack of satisfaction with current BAD information, and with existing ADDPs, contributing to sub-optimal decision making. Improved BAD data would have multiple uses by different stakeholders leading to better evidenced decisions and policies; moreover, clients will need support (including DSTs) to optimally use BAD information.
Rationalising development of classification systems describing livestock production systems for disease burden analysis within the Global Burden of Animal Diseases programme
(Journal Article, 2024-03) Yin Li; McIntyre, K. Marie; Rasmussen, Philip; Gilbert, William; Chaters, Gemma; Raymond, Kassy; Jemberu, Wudu T.; Larkins, Andrew; Patterson, Grace T.; Kwok, Stephen; Kappes, Alexander James; Mayberry Dianne; Schrobback, Peggy; Herrero Acosta, Mario; Stacey, Deborah A.; Huntington, Benjamin; Bruce, Mieghan; Knight-Jones, Theodore J.D.; Rushton, Jonathan
The heterogeneity that exists across the global spectrum of livestock production means that livestock productivity, efficiency, health expenditure and health outcomes vary across production systems. To ensure that burden of disease estimates are specific to the represented livestock population and people reliant upon them, livestock populations need to be systematically classified into different types of production system, reflective of the heterogeneity across production systems. This paper explores the data currently available of livestock production system classifications and animal health through a scoping review as a foundation for the development of a framework that facilitates more specific estimates of livestock disease burdens. A top-down framework to classification is outlined based on a systematic review of existing classification methods and provides a basis for simple grouping of livestock at global scale. The proposed top-down classification framework, which is dominated by commodity focus of production along with intensity of resource use, may have less relevance at the sub-national level in some jurisdictions and will need to be informed and adapted with information on how countries themselves categorize livestock and their production systems. The findings in this study provide a foundation for analysing animal health burdens across a broad level of production systems. The developed framework will fill a major gap in how livestock production and health are currently approached and analysed.
Attributing Ethiopian animal health losses to high-level causes using expert elicitation
(Journal Article, 2023-12) Larkins, A.; Temesgen, Wudu; Chaters, G.; Bari, C. di; Kwok, S.; Knight-Jones, Theodore J.D.; Rushton, J.; Bruce, M.
The Global Burden of Animal Diseases programme is currently working to estimate the burden of animal health loss in Ethiopia. As part of this work, structured expert elicitation has been trialled to attribute the proportion of animal health losses due to three independent and exhaustive high-level causes (infectious, non-infectious, and external). Separate in-person workshops were conducted with eight cattle, nine small ruminant, and eight chicken experts. Following the Investigate-Discuss-Estimate-Aggregate protocol for structured expert elicitation, estimates were obtained for the proportion of animal health loss due to high-level causes in different combinations of health loss, species, age-sex class, and production system. Three-point questions were used to inform beta-pert distributions and capture uncertainty in estimates. Individual expert estimates were aggregated by quantile mean to produce average distributions. Random samples from these average distributions estimated that infectious causes inflict the highest proportion of health loss in Ethiopia, with at least 40% of health losses estimated to be due to infectious causes in all categories. This study provides a rapid, simple, and engaging method to attribute the burden of animal health loss at a high-level. Results are informative, however will become increasingly useful once they can be compared with results from more sophisticated, data-driven models.

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