Objectives Antimicrobial resistance is a major global health threat, with antimicrobial use recognized as a key driver. The post-weaning period is one of the most antimicrobial-intensive phases in pig production. This study assessed the impact on production costs of feed-based and immunomodulatory interventions designed to reduce antimicrobial use in European pig production. Materials and methods Within the EU-funded AVANT project, we evaluated feed-based strategies (alfalfa diets and high-fibre/low-protein 'secure' feed) and immunomodulatory interventions (faecal filtrate transplantation and vaccination against Shiga-producing Escherichia coli). Using data from field trials and observational studies conducted in Denmark, the Netherlands and France, we estimated the additional production costs per kilogram of pigmeat associated with each intervention. Cost and production parameters were derived from InterPIG and EU datasets (2019-2023) and adjusted under alternative mortality scenarios (6%-24%). Results Feed-based interventions for piglets accounted for a small share of total feed costs and increased production costs by <0.2% at EU level. Vaccination against Shiga-producing E. coli increased production costs by <1%. By contrast, faecal filtrate transplantation resulted in substantially higher costs under trial conditions, increasing production costs by 9%-11% depending on mortality assumptions. None of the interventions negatively affected pig performance metrics in the trials. Conclusions Feed-based strategies and vaccination represent accessible and affordable options to reduce antimicrobial use in pig production in Europe. More innovative approaches such as faecal filtrate transplantation remain costly under experimental conditions but may become economically viable through regulatory approval, market development and economies of scale.

There is limited empirical evidence on the quantitative economic contribution of donkeys to livelihoods, leading to their undervaluation and exclusion from policy. Here an enterprise budget analysis is embedded within a stochastic dynamic population model for three production systems in Ethiopia to evaluate system inputs, outputs and the economic contribution of donkeys. The model was parameterised using data from household surveys, focus group discussions and key informant interviews, supplemented by literature. The economic value of donkeys' (unpaid) homestead and agricultural services was estimated in terms of both monetary savings and conserved human labour hours. The benefits of donkey ownership significantly exceed the costs, with an average net return of USD 567 (95% PI: 479-660) per household per year. Donkeys provide essential unpaid labour, particularly in domestic agricultural and pastoral systems. Households saved an average of USD 498 (95% PI: 437-564) a year by utilising their own donkeys. Additionally, they reduce household labour demands by up to 16.5 hours per week, easing the workload on women and enabling children to attend school. In agriculture, donkeys support all production stages, providing an average of 53 days of work per year. This study demonstrates the importance of donkeys across Ethiopia's production systems and the need for investment in donkey health and welfare to sustain these benefits. Donkeys provide essential economic services, helping marginalised households with limited resources to significantly enhance their well-being and financial circumstances.

Introduction African swine fever (ASF) poses a major threat to the U.S. pork sector, with potentially large spillovers through domestic markets and international trade. To inform preparedness and policy design, we quantify the economy-wide consequences of a hypothetical ASF outbreak under alternative scenarios of production losses and export restrictions.Methods We use a computable general equilibrium (CGE) model to simulate four hypothetical ASF scenarios that vary by outbreak size and export restrictions. The model endogenously captures adjustments in production, prices, bilateral trade flows, and welfare, and we assess robustness using systematic sensitivity analysis.Results Small outbreak scenarios generate limited sectoral disruption and no substantial GDP effects, with U.S. welfare losses of $310-$563 million. Large outbreak scenarios reduce U.S. hog production by 7.34%-8.57% and pork production by 7.25%-10.8%, increase U.S. hog producer prices by 41.6%-41.8% and pork prices by 6.5%, and reduce U.S. GDP by 0.05%. Corresponding U.S. welfare losses rise to $10.9-$11.4 billion. Globally, large outbreaks increase world hog and pork prices by 3.67%-3.69% and 1.20%-1.22%, respectively, and drive trade diversion toward alternative exporters.Discussion The results indicate that the economic costs of ASF increase substantially with outbreak size and are shaped by the severity of trade restrictions. Investments that prevent escalation (early detection, rapid containment) and strategies that preserve market access (credible regionalization/zoning arrangements) can substantially reduce welfare losses and global market disruption.

Respiratory disease remains highly prevalent in pig production and constitutes a major health and welfare challenge worldwide. However, most studies assessing pig welfare impairment from respiratory disease rely on isolated animal-based indicators, limiting integration across welfare domains. This study aimed to quantify welfare impairment from respiratory disease in fattening pigs (8–10 weeks of age) using indicators aligned with the Five Domains Model. A survey using adaptive conjoint analysis was conducted with animal welfare researchers (n = 32) and practising swine veterinarians (n = 22). Respondents completed pairwise comparisons of profiles defined by combinations of five welfare indicators—appetite, coughing, respiratory distress, play behaviour, and exploratory behaviour—each expressed at increasing severity levels. Based on respondents’ choices of which profile represented greater welfare impairment, indicator importance scores and level-specific contributions to pig welfare impairment from respiratory disease were estimated. Across respondent groups, severe respiratory distress was perceived as the largest contributor to pig welfare impairment from respiratory disease, with an estimated contribution of 29.8

This study, carried out in 2022-2023, quantified the financial burden of disease in cattle, sheep and goats in Ethiopia for the year 2021 using the animal health loss envelope (AHLE) metric. The AHLE measures all cause disease burden, avoidable and non-avoidable, as the difference in the financial performance of a livestock production system (e.g., gross margin) comparing a scenario where animals are in an ideal state of health to the current situation. A stochastic dynamic population model (DPM) was employed to calculate the gross margin for an average farm and for the national herd under these current and ideal health scenarios. Data for parametrizing the DPM were derived from secondary sources and expert elicitation. The stochastic DPM was simulated for10,000 iterations and results are reported as means with 95% percentile intervals (PI). The annual AHLE per average farm was estimated at USD 1,209 (95%PI:392-2,470) in cattle, USD 158 (95%PI:66-292) in sheep and USD 416 (95%PI:136-847) in goats. At national level, the annual AHLE in ruminants was USD 18.39 billion with USD 15.42 billion (95% PI:12.70-18.57) in cattle, USD 1.04 billion (95% PI:0.84-1.30) in sheep, and USD 1.93 billion (95% PI:1.64 - 2.25) in goats. Morbidity losses constituted the largest component of the AHLE, exceeding 50% across all species, while animal health expenditure represented the smallest component, accounting for less than 2% of AHLE in all species. This high disease burden, with minimal contribution from animal health expenditure, indicates significant opportunity for improvement through investment in animal health.

Lameness is a highly prevalent and economically important health problem in British dairy cattle. Previous studies have highlighted a delay between lameness onset and farmer detection. This lag, combined with the low sensitivity of clinical diagnosis, limits early intervention, thereby worsening both production and animal welfare outcomes. Notably, the negative effects of lameness can persist even after clinical recovery. Understanding the burden of health issues is essential for informed decision making at the farm level and beyond. This study quantifies the impact of hoof-health disorders on milk yield in British dairy cattle. Data were obtained from 6,050 cows across a nonrandom sample of 11 farms, including repeated daily milk yield records, totaling ∼2.1 million cow-days. A mixed linear model was developed to account for the time-dependent, correlated nature of milk yield data, using a first-order autoregressive correlation structure. An event study design allowed investigation of milk yield trajectories before and after clinical diagnosis. Farmer-reported data were used to identify hoof-related lameness events. After adjusting for mastitis, stage of lactation, parity, farm, season, and breed, cows with a hoof-health event produced on average 1.47 kg/d less milk than healthy cows. For severe cases, the average daily reduction reached 2.05 kg. The event study revealed that milk yield declines were detectable before clinical diagnosis and persisted after treatment. These findings underscore the impact of hoof-health disorders on dairy productivity and highlight the need for earlier detection as it could help farmers mitigate milk losses, reduce treatment costs, and enhance animal welfare.

Working donkeys play a critical role in transportation, agriculture and household resilience in low- and middle-income countries. Other animals that are kept for production purposes, such as cattle, are often grouped into broad production system classes, such as dairy or pastoral, for comparison between and better understanding of the needs and outputs of animals within specific sectors. Despite the importance of working donkeys for sustaining livelihoods there are no systematic classifications of these populations. The aim of this study was to classify and characterise donkey systems in Ethiopia using household-level questionnaire data which included donkey ownership, husbandry, use and local environment data, through multiple factor and hierarchical cluster analysis. Household questionnaire data from 241 donkey-owning households in three districts of Ethiopia were used. Three distinct clusters of donkey ownership were identified: 'Domestic-Pastoral'; 'Domestic-Agricultural' and 'Commercial'. Differences between systems are primarily influenced by donkey purpose, environmental (agro-ecological) factors, and husbandry practices. Constraints associated with donkey ownership varied across clusters: households in the commercial system reported higher incidence of injuries and welfare concerns, in the pastoral system the main constraints were drought and feed shortage, and domestic-agricultural households reported infectious diseases as the main challenge. This new classification of donkey systems provides a framework for analysing donkey health and welfare data, enabling more context-specific needs assessments and facilitating the design of targeted interventions to improve equid health and household livelihoods.

Gaining insight into the size and composition of national pig populations can support decisions on disease control, welfare, and environmental sustainability. However, if one needs to draw meaningful comparisons between the performance of various production systems or countries, a method for standardization is required. One approach to achieve this is by means of biomass estimation. The objective of this study was to develop a biomass estimation framework that can provide detailed and reliable estimates of fattening pig biomass disaggregated by pig life stage (suckling, weaning and fattening), while accounting for the dynamic nature of pig populations. The framework was developed on publicly accessible data pertaining to pig production in the Netherlands, and we additionally assessed availability of required data for several other European countries (Spain, Germany, and Great Britain). Three distinct life stages—suckling piglets, weaning pigs, and fattening pigs—are considered in the framework. Demographic and movement data, including yearly imports, exports, and slaughter numbers, along with standing populations, were collected from official governmental sources. Required production parameters were sourced from representative surveys, with missing parameters supplemented by private industry reports or expert elicitation. The results from the framework for the Netherlands yield insights into the Dutch pig sector. In 2020, 156 million kg, 552 million kg, and 1,654 million kg of biomass were produced in the suckling, weaning, and fattening stages, respectively. The evaluation against census data indicated the framework's reliability, with deviations mostly below 10%. Data availability assessments for Spain, Germany and Great Britain reveal variations in data completeness and underscore the importance of local contacts and language expertise when extending the framework to other countries. The framework's relevance was further demonstrated through an illustrative application, assessing the impact of porcine reproductive and respiratory syndrome on pig biomass in the Netherlands. In the most severe disease scenario, the produced biomass decreased by 13%, 17%, and 66% in the suckling, weaning, and fattening stages, respectively. Beyond disease burden estimation, the biomass estimates can be used as a denominator for various purposes to provide efficiency metrics, such as the amount of antibiotics used or the volume of greenhouse gases emitted per kilogram of pig biomass produced. While the framework could benefit from further refinement regarding resource use and economic values, its current iteration provides a robust and unique foundation for estimating biomass disaggregated by pig life stage, aiding decision-makers in the agricultural and veterinary sector.

Introduction:Livestock biomass is a denominator for a wide range of important production metrics, including productivity, environmental impact, greenhouse gas emissions, and antimicrobial usage. Accurate biomass estimates allow cross-sectoral and international comparisons for these important indices across a range of high-priority areas, which can then inform policy risk assessments and decision-making. Similarly, accurate estimates of the value of livestock are needed to monitor economic efficiency and productivity and understand the costs associated with animal health policy decisions. Previous methods to estimate biomass have relied on assigning an average liveweight for a given species and multiplying this by the number of individual animals of that species in a region. However, without taking into account the population's demographics and structure, these approaches cannot be relied upon to accurately represent the cattle population. Methods:Using data from the Irish cattle herd as a case study, this study developed liveweight and value models and applied these models to a cattle registration and movement database to estimate the biomass (kg) and economic stock value (€) of each animal and herd, aggregated by herd type based on a herd classification tree model, and explored trends in biomass and stock value over time. Results:The Irish cattle sector biomass increased from 2,924,800 tonnes in 2011 to 3,317,100 tonnes in 2021, and the cattle sector stock value increased from €6,323.7 m in 2011 to €8,792.3 m in 2021. Furthermore, this study demonstrated the biomass and stock value within-year and between years. Discussion:We illustrate a novel approach using real-time movement data for dynamic estimates of biomass and stock value at animal-, herd- and national-level that can be applied in countries with existing animal registration and movement tracing systems.

Objective:Foreign animal diseases (FADs) are nonnative to the US and threaten animal welfare and economy. During FAD outbreaks, reliance solely on laboratory-based tests challenges response due to cost and turnaround time. Validated point-of-care (POC) diagnostic tests enable early field detection, reduce economic impact, and protect animal welfare. This proposal recommends a national POC diagnostic testing framework for FADs, providing guidance on modifying existing tests and serving as a resource for laboratory diagnosticians. Methods:In 2022, at the American Association of Veterinary Laboratory Diagnosticians annual meeting, the National Animal Health Laboratory Network (NAHLN) Laboratory Directors Committee evaluated a draft POC testing process. In 2023, 27 stakeholders, including regulatory agencies, industry stakeholders, and diagnostic laboratories from 8 states, evaluated the draft process for distribution, use, and reporting and provided recommendations for validating POC testing. Results:The 6 steps of the POC testing framework were validated by 27 stakeholders. Recommendations for improving FAD response were submitted to the USDA APHIS Veterinary Services and NAHLN, focusing on validation, importation, licensing, test validity, deployment, communication of results, animal movement, and indemnity. Conclusions:Through stakeholder evaluation of testing framework, recommendations were provided to the USDA APHIS Veterinary Services and NAHLN for validating each step of POC testing framework, thereby reducing detection and response times during FAD outbreaks while making it cost efficient for producers and public. However, test performance and human behavior should be thoroughly evaluated to reduce variability of results. Clinical Relevance:Point-of-care testing to enable quick and cost-effective FAD response, rapid containment, reduced disease transmission, and improved efficiency motivated the development of a stakeholder-informed revision to the testing framework through qualitative evaluation and expert recommendations.

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.

Farmers, veterinarians and other animal health managers in the livestock sector are currently missing sufficient information on prevalence and burden of contagious endemic animal diseases. They need adequate tools for risk assessment and prioritization of control measures for these diseases. The DECIDE project develops data-driven decision-support tools, which present (i) robust and early signals of disease emergence and options for diagnostic confirmation; and (ii) options for controlling the disease along with their implications in terms of disease spread, economic burden and animal welfare. DECIDE focuses on respiratory and gastro-intestinal syndromes in the three most important terrestrial livestock species (pigs, poultry, cattle) and on reduced growth and mortality in two of the most important aquaculture species (salmon and trout). For each of these, we (i) identify the stakeholder needs; (ii) determine the burden of disease and costs of control measures; (iii) develop data sharing frameworks based on federated data access and meta-information sharing; (iv) build multivariate and multi-level models for creating early warning systems; and (v) rank interventions based on multiple criteria. Together, all of this forms decision-support tools to be integrated in existing farm management systems wherever possible and to be evaluated in several pilot implementations in farms across Europe. The results of DECIDE lead to improved use of surveillance data and evidence-based decisions on disease control. Improved disease control is essential for a sustainable food chain in Europe with increased animal health and welfare and that protects human health.

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.

Farmers, veterinarians and other animal health managers in the livestock sector are currently missing sufficient information on the prevalence and burden of contagious endemic animal diseases. They need adequate tools for risk assessment and prioritization of control measures for these diseases. The DECIDE project develops data-driven decision-support tools, which present (i) robust and early signals of disease emergence and options for diagnostic confirmation; and (ii) options for controlling the disease along with their implications in terms of disease spread, economic burden and animal welfare. DECIDE focuses on respiratory and gastro-intestinal syndromes in the three most important terrestrial livestock species (pigs, poultry, cattle) and on reduced growth and mortality in two of the most important aquaculture species (salmon and trout). For each of these, we (i) identify the stakeholder needs; (ii) determine the burden of disease and costs of control measures; (iii) develop data sharing frameworks based on federated data access and meta-information sharing; (iv) build multivariate and multi-level models for creating early warning systems; and (v) rank interventions based on multiple criteria. Together, all of this forms decision-support tools to be integrated in existing farm management systems wherever possible and to be evaluated in several pilot implementations in farms across Europe. The results of DECIDE lead to improved use of surveillance data and evidence-based decisions on disease control. Improved disease control is essential for a sustainable food chain in Europe with increased animal health and welfare and that protects human health.

Enterotoxigenic Escherichia coli (ETEC) is a significant cause of diarrhoea in livestock and humans. The epidemiology of ETEC in animals remains understudied, prompting an investigation into the virulence factors and associated adhesins of ETEC in livestock from Western Kenya. Also, there is limited evidence supporting the role of livestock as possible zoonotic reservoirs for ETEC. ETEC strains harbour colonization factors/adhesins and enterotoxins, with animal ETECs exhibiting various adhesins (F4, F5, F6, F17, F18 and F41). Enterotoxins include heat- labile (LT) and heat- stable (ST) toxins and are further divided into LT- I and LT- II and STa and STb, respectively. Additional toxin combinations occur, with ETEC and Shiga toxin- producing E. coli (STEC) hybrids garnering public health significance. Here, we analysed faecal and mesenteric lymph node samples from diverse livestock across three Western Kenyan counties (Busia, Bungoma and Kakamega), using whole- genome sequencing. In silico screening determined the presence of AB5 and A2B5- like toxin genes, including cytolethal distending toxin (cdtABC) along with associated adhesins. To broaden the screening panel, adhesin genes identified were further characterized to identify both known and novel alleles, particularly focusing on human- ETEC colonization factors. Two estA alleles (estA-4-06, estA-6-02) and six eltAB- II toxin alleles (eltAB-II-a2-01, eltAB-II-a3-01, eltAB-II-c1-02, eltAB-II-c6-03, eltAB-II-c6-04 and eltAB-II-c7-02) were identified in livestock. Hybrid ETECs identified were ETEC/STEC present in 6.7% (4/60) of ETEC strains and ETEC with cdtABC type I. An A2B5- like tripartite toxin, potentially resembling the typhoid toxin, was detected in 8.7% (4/46) of the eltAB-II-positive strains. It may have unique effects on enterocytes distinct from known toxins. These findings expand our understanding of ETEC pathogenicity and genetic diversity in animal reservoirs, while also highlighting potential zoonotic risks. They broaden the toxin repertoire, offer adhesin- based vaccine candidates for livestock and provide valuable insights for future vaccine development and public health strategies in the Lake Victoria Crescent ecosystem and beyond.

Ethiopia is a highly agrarian economy, though livestock's contribution falls below its potential. Women play a significant role in livestock production; however, the literature on gendered dynamics of livestock disease is limited, particularly at the intra-household level. This work marks the first gender-focused study within the Global Burden of Animal Disease programme. Its goal is to enhance the programme's aim of disaggregating the economic burden borne by humans due to animal disease. It explores the extent to which existing knowledge can be disaggregated by gender within households. A scoping review of the existing literature on the intra-household burden of animal disease in Ethiopia was conducted, with 143 articles screened. This was supplemented by seventeen key informant interviews consisting of individuals or knowledgeable representatives from organisations known to the authors for their work in Ethiopia and/or on gender, livestock production, and animal disease. Only one study directly addressed the intra-household gendered dimensions of animal disease burden in Ethiopia. Data were extracted in MS Excel. Adult men and women were found to be most impacted due to their roles in income generation and providing animal-sourced foods, and their need to compensate for losses during disease outbreaks. However, all household members contribute to disease transmission through gender-specific responsibilities. Key informant interviews were analysed in NVivo to determine themes in responses. Participants noted that household members engage in distinct transmission activities and face unequal consequences shaped by gendered norms and emphasised the need for gender-disaggregated data. We advocate for primary, contextually grounded data collection that routinely includes gender- and age-disaggregated measures of exposure, decision-making, empowerment, and economic outcomes, complemented by qualitative enquiry. This would enable the design of targeted interventions to reduce animal and human morbidity and mortality while protecting livelihoods and promoting equity. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by the Bill and Melinda Gates Foundation and the United Kingdom’s Foreign, Commonwealth and Development Office under Grant Agreement Investment ID: INV-005366 for the Global Burden of Animal Diseases (GBADs) program. (EB, SB-M, PRO, JR). This work was supported by CGIAR’s Sustainable Animal Productivity for Livelihoods, Nutrition, and Gender Inclusion (SAPLING) initiative, and continued under the Sustainable Animal and Aquatic Foods Program (SAAF), and the contributions of donors and organisations supporting these Research Programs through the CGIAR Trust Fund. (TK-J, WT). The included source of evidence (Gizaw et al., 2020) was funded in part by Global Affairs Canada (GAC) through support from the Livestock and Irrigation Value chains for Ethiopian Smallholders (LIVES) project of the International Livestock Research Institute (ILRI), as well as by the CGIAR Research Program on Livestock and Fish. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The International Livestock Research Institute Institutional Research Ethics Committee granted ethical approval to conduct key informant interviews and audio recording. The approval reference for this is ILRI-IREC2022-14/1. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The search strings were adapted using keywords relating to intra-household, gender, disease, impact, livestock and Ethiopia for use in each database, available in the OSF Registries at https://doi.org/10.17605/OSF.IO/K5JEC.

Background Bacterial antimicrobial resistance (AMR) is a global threat to both humans and livestock. Despite this, there is limited global consensus on data-informed, priority areas for intervention in both sectors. We compare current livestock AMR data collection efforts with other variables pertinent to human and livestock AMR to identify critical data gaps and mutual priorities. Methods We globally synthesized livestock AMR data from open-source surveillance reports and point prevalence surveys stratified for six pathogens ( Escherichia coli , Staphylococcus aureus , non-typhoidal Salmonella , Campylobacter spp., Enterococcus faecalis , Enterococcus faecium ) and eleven antimicrobial classes important in human and veterinary use, published between 2000 and 2020. We also included all livestock species represented in the data: cattle, chickens, pigs, sheep, turkeys, ducks, horses, buffaloes, and goats. We compared this data with intended priorities calculated from: disability-adjusted life years (DALYs), livestock antimicrobial usage (AMU), livestock biomass, and a global correlation exercise between livestock and human proportion of resistant isolates. Results Resistance to fluoroquinolones and macrolides in Staphylococcus aureus were identified as priorities in many countries but, less than 10% of these reported livestock AMR data. Resistance data for Escherichia coli specific to cattle, chickens, and pigs, which we prioritized, were also well collected. AMR data collection on non-typhoidal Salmonella and other livestock species were often not prioritized. Of 232 categories prioritized by at least one country, data were only collected for 48% (n = 112). Conclusions The lack of livestock AMR data globally for broad resistance in Staphylococcus aureus could underplay their zoonotic threat. Countries can bolster livestock AMR data collection, reporting, and intervention setting for Staphylococcus aureus as done for Escherichia coli . This framework can provide guidance on areas to strengthen AMR surveillance and decision-making for humans and livestock, and if done routinely, can adapt to resistance trends and priorities.