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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. DATA AVAILABILITY STATEMENT: The data can be obtained from the corresponding author upon request., Competing Interests: Declaration of Competing Interest A conflict of interest occurs when an individual’s objectivity is potentially compromised by a desire for financial gain, prominence, professional advancement or a successful outcome. ASJSUR Editors strive to ensure that what is published in the Journal is as balanced, objective and evidence-based as possible. Since it can be difficult to distinguish between an actual conflict of interest and a perceived conflict of interest, the Journal requires authors to disclose all and any potential conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

In addition to affecting animal health and production, antimicrobial resistance (AMR) in livestock can have far-reaching social and economic consequences, including on human health and the environment. Given the diversity of data needs and the absence of standardised methodologies, the scale of antimicrobial use (AMU) and AMR's social and economic burden on livestock is complex to gauge. Yet, quantifying this impact can be an essential input for farm-level decision-making and, more widely, for policy development, public awareness, resource allocation to interventions and research and development prioritisation, particularly in a One Health context. This work proposes a conceptual framework to guide the assessment of the burden of AMU and AMR in livestock using the Global Burden of Animal Diseases (GBADs) approach. Its development identified and mapped critical socio-economic concepts in AMU and AMR in livestock and their relationships. The Animal Health Loss Envelope (AHLE), a monetary metric that sets a boundary for overall losses from health hazards and allows an understanding of the relative importance of health problems in livestock, was used as the metric in which the concepts and data needs for the AMU and AMR assessment were anchored. The proposed framework identifies pathways for losses and data inputs needed to estimate the burden of AMU and AMR within this wider envelope of losses. These include information on health expenditure and mortality and morbidity effects related to AMR in livestock. This work highlights the need for improved health and production data collection in livestock production as an essential stepping stone to accurately producing AMU and AMR burden estimates., Competing Interests: None., (© 2024 The Authors. Published by Elsevier B.V.)

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., (© 2024. The Author(s).)

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.

The Global Burden of Animal Diseases (GBADs) programme's key objective â€" to provide a systematic approach to determine the burden of animal disease â€" is as relevant to aquatic as to terrestrial animal production systems. However, to date GBADs methods have mainly been applied to terrestrial animal production systems. The challenges in applying GBADs methods, notably the Animal Health Loss Envelope (AHLE), vary considerably by production system. The authors demonstrate how the AHLE can be calculated for rainbow trout production in England and Wales and acknowledge that its application to other systems (e.g. hatchery production, polyculture and no-feed mollusc production) is more complex. For example, in small scale tropical fish production the impact of suboptimal nutrition on production would need to be addressed. Recirculating aquaculture systems have inherent high levels of biosecurity and disease control, and thus low levels of disease. Removing the capital and running costs associated with biosecurity fundamentally changes the system and invalidates the AHLE calculation. Lack of data from many systems, notably small-scale tropical finfish farming, means that expert opinion will be needed to support the application of GBADs methods. While calculation of the AHLE is the focus of this article, it should be noted that attribution to causes and value chain modelling are needed to generate data on the wider societal impact of aquatic animal diseases (and possible interventions), which governments require to support decision-making about resource allocation.

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.

Targeted protein degradation (TPD) allows cells to maintain a functional proteome and to rapidly adapt to changing conditions. Methods that repurpose TPD for the deactivation of specific proteins have demonstrated significant potential in therapeutic and research applications. Most of these methods are based on proteolysis targeting chimaeras (PROTACs) which link the protein target to an E3 ubiquitin ligase, resulting in the ubiquitin-based degradation of the target protein. In this study, we introduce a method for ubiquitin-independent TPD based on nanobody-conjugated plant ubiquitin regulatory X domain-containing (PUX) adaptor proteins. We show that the P UX-based NA nobody D egraders (P-NADs) can unfold a target protein through the Arabidopsis and human orthologues of the CDC48 unfoldase without the need for ubiquitination or initiating motifs. We demonstrate that P-NAD plasmids can be transfected into a human cell line, where the produced P-NADs use the endogenous CDC48 machinery for ubiquitin-independent TPD of a 143 kDa multidomain protein. Thus, P-NADs pave the road for ubiquitin-independent therapeutic TPD approaches. In addition, the modular P-NAD design combined with in vitro and cellular assays provide a versatile platform for elucidating functional aspects of CDC48-based TPD in plants and animals., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

We use AlphaFold2 (AF2) to model the monomer and dimer structures of an intrinsically disordered protein (IDP), Nvjp-1, assisted by molecular dynamics (MD) simulations. We observe relatively rigid dimeric structures of Nvjp-1 when compared with the monomer structures. We suggest that protein conformations from multiple AF2 models and those from MD trajectories exhibit a coherent trend: the conformations of an IDP are deviated from each other and the conformations of a well-folded protein are consistent with each other. We use a residue-residue interaction network (RIN) derived from the contact map which show that the residue-residue interactions in Nvjp-1 are mainly transient; however, those in a well-folded protein are mainly persistent. Despite the variation in 3D shapes, we show that the AF2 models of both disordered and ordered proteins exhibit highly consistent profiles of the pLDDT (predicted local distance difference test) scores. These results indicate a potential protocol to justify the IDPs based on multiple AF2 models and MD simulations., Competing Interests: The authors declare no competing interests., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

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., Funding: Bill & Melinda Gates Foundation, the UK Foreign, Commonwealth and Development Office, EU Horizon 2020 Research and Innovation Programme., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

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 prioritzation 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 prioritzation 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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)