Revue Scientifique et Technique-Office International Des Epizooties最新文献

Quantifying the impact of poor animal health outcomes on human health represents a complex challenge. Using the disability-adjusted life year (DALY) metric as an endpoint, this article discusses how animal health outcomes can impact humans through three key processes: directly through zoonotic disease, indirectly via changes in yields and their impacts on nutrition and wealth, and finally, through indirect features associated with the agricultural industry, such as pharmaceuticals and climate change. For each process, the current state of the art and feasibility of global DALY-associated estimates are discussed. Existing frameworks for zoonoses already consider some key pathogens; ensuring completeness in the pathogens considered and consistency in methodological decisions is an important next step. For diet, risk factor frameworks enable a calculation of attributable DALYs; however, significant economic methodological developments are needed to ensure that local production changes are appropriately mapped to both local and global changes in dietary habits. Concerning wealth-related impacts, much work needs to be done on method development. Industry-related impacts require a focus on key research topics, such as attribution studies for animal antimicrobial resistance contributing to human outcomes. For climate change, a critical next step is identifying to what extent associated industry emissions are amenable to change should animal health outcomes improve. Allocation of finite funds to improve animal health must also consider the downstream impact on humans. Leveraging DALYs enables comparisons with other human health-related decisions and would represent a transformative way of approaching animal health decision-making should the obstacles in this article be addressed and new methods be developed.

Countries in the Americas play a vital role in global livestock and aquaculture production. With international trade of livestock and aquaculture products becoming an important source of income for countries, there has been an increased interest in using animal health economics for advocacy and allocation of resources. This article discusses the development of a new Collaborating Centre for the Economics of Animal Health and the applications of the Global Burden of Animal Diseases (GBADs) framework in the Americas region. Incentives for the increased use of economics in animal health decision-making and examples from the Americas region are examined. The article then discusses the newly formed World Organisation for Animal Health Collaborating Centre in the Americas region. Finally, it reviews two ongoing case studies that are implementing the GBADs framework in Peru and the United States of America.

The Global Burden of Animal Diseases (GBADs) programme aims to quantify the economic and broader societal costs of animal disease, providing information to policy-makers and other stakeholders to inform investments in animal health. Within this context, GBADs'Indonesian case study brings together a multidisciplinary and multi-national team to pilot the GBADs methodology in the Asiaâ€"Pacific region. This article describes the process of building a case study and, based on that experience, summarises key learnings to inform the development of future case studies and similar projects. Recommendations focus on the steps required to build successful partnerships to deliver a complex programme of work; the authors highlight the need to consider the local context in aligning project and country priorities, the importance of early engagement with a range of stakeholders, and the need for regular and clear communication within the project team.

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.

Attracting and sustaining investment in Veterinary Services and animal health programmes from national government budgets, development aid and grants, and philanthropic donors requires economic rationale using relevant, reliable and validated analytical approaches. The complex interwoven relationships between animal health, livestock husbandry systems, national food security, global health security and environmental sustainability emphasise the importance of improving data governance and stewardship and applying economic analysis to understand animal disease burdens. These efforts should enable prioritised investment of limited resources and effective monitoring of the impact of programmes over time. Data governance and stewardship capacities are fundamental to development, implementation and performance monitoring of evidence-based policies in animal health. There are challenges in data availability for national and subnational livestock populations in different sectors, for disease incidence and prevalence, and for animal health expenditure in support of optimised allocation of scarce resources, be they finance, land, labour, or management attention and policy focus. Animal health data systems governance and stewardship and economic analysis are core skills for Veterinary Services in developing and applying evidence-based policy, but capability probably varies among World Organisation for Animal Health (WOAH) Members. The WOAH Performance of Veterinary Services programme has several critical competencies that are relevant to economics of animal health and to data governance and stewardship, but these have not yet been targeted for coordinated capacity development. Implementation of publicâ€"private partnership approaches for animal health programmes creates increasing expectations of robust data and methods for prioritisation, options analysis, and assessing impacts and costs. Experience and examples from national systems in New Zealand, Australia, Ethiopia and Indonesia illustrate current challenges associated with prioritisation of animal health programmes using economic analysis. The Global Burden of Animal Diseases programme intends to support WOAH Members and partners to develop capacities for and standardise approaches to economic analysis and prioritisation in animal health programmes.

The Global Burden of Animal Diseases (GBADs) programme aims to assess the impact of animal health on agricultural animals, livestock production systems and associated communities worldwide. As part of the objectives of GBADs'Animal Health Ontology theme, the programme reviewed conceptual frameworks, ontologies and classification systems in biomedical science. The focus was on data requirements in animal health and the connections between animal health and human and environmental health. In May 2023, the team conducted searches of recognised repositories of biomedical ontologies, including BioPortal, Open Biological and Biomedical Ontology Foundry, and Ontology Lookup Service, to identify animal and livestock ontologies and those containing relevant concepts. Sixteen ontologies were found, covering topics such as surveillance, anatomy and genetics. Notable examples include the Animal Trait Ontology for Livestock, the Animal Health Surveillance Ontology, the National Center for Biotechnology Information Taxonomy and the Uberon Multi-Species Anatomy Ontology. However, some ontologies lacked class definitions for a significant portion of their classes. The review highlights the need for domain evidence to support proposed models, critical appraisal of external ontologies before reuse, and external expert reviews along with statistical tests of agreements. The findings from this review informed the structural framework, concepts and rationales of the animal health ontology for GBADs. This animal health ontology aims to increase the interoperability and transparency of GBADs data, thereby enabling estimates of the impacts of animal diseases on agriculture, livestock production systems and associated communities globally.

Misuse and overuse of antimicrobials in livestock production are identified as drivers for antimicrobial resistance (AMR). To improve decision-making concerning livestock health, it is important to understand the impact of AMR in livestock and aquaculture, within and beyond farm level, as well as expenditure on antimicrobial use (AMU). Such understanding provides grounds for systematic disease prioritisation and establishes a baseline for understanding the value of different strategies to mitigate animal health problems and for the monitoring and evaluation of the impact of those strategies. Yet limited data availability and quality surrounding AMU and AMR create barriers to furthering the knowledge of such impact. These data constraints are also more prevalent in contexts that lack the necessary resources to develop and maintain systematic and centralised data collection and collation systems. Even in regions with robust AMU and AMR monitoring systems in place, data limitations remain, such that the expenditure on antimicrobials and impacts of AMR remain unclear. Additionally, the current research funding strategies have been less focused on primary data collection, adding further barriers to filling the data void and reducing the global AMU/AMR knowledge gap. To work around the data scarcity and leverage previous and ongoing research efforts, it is vital to gain comprehensive knowledge of the people, projects and research consortia dedicated to the topic of AMU/AMR.