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

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 estimation of the global burden of animal diseases requires the integration of multidisciplinary models: economic, statistical, mathematical and conceptual. The output of one model often serves as input for another; therefore, consistency of the model components is critical. The Global Burden of Animal Diseases (GBADs) Informatics team aims to strengthen the scientific foundations of modelling by creating tools that address challenges related to reproducibility, as well as model, data and metadata interoperability. Aligning with these aims, several tools are under development: a) GBADs'Trusted Animal Information Portal (TAIL) is a data acquisition platform that enhances the discoverability of data and literature and improves the user experience of acquiring data. TAIL leverages advanced semantic enrichment techniques (natural language processing and ontologies) and graph databases to provide users with a comprehensive repository of livestock data and literature resources. b) The interoperability of GBADs'models is being improved through the development of an R-based modelling package and standardisation of parameter formats. This initiative aims to foster reproducibility, facilitate data sharing and enable seamless collaboration among stakeholders. c) The GBADs Knowledge Engine is being built to foster an inclusive and dynamic user community by offering data in multiple formats and providing user-friendly mechanisms to garner feedback from the community. These initiatives are critical in addressing complex challenges in animal health and underscore the importance of combining scientific rigour with user-friendly interfaces to empower global efforts in safeguarding animal populations and public health.

This article focuses on identifying the loss of production and costs (or lack thereof) associated with livestock health as well as animal disease externalities, with the intent to estimate economy-wide burden. It limits its scope to terrestrial livestock and aquaculture, wherein economic burden is predominately determined by market forces. Losses and costs are delineated into both direct losses and costs and indirect losses and costs, as well as ex post costs and ex ante costs. These costs include not only private expenditures but also public expenditures related to the prevention of, treatment of, and response to livestock disease. This distinction is important because a primary role of government is to mitigate externalities. The article then discusses market impacts and investments. Finally, it provides selected examples and illustrative observations and discusses future directions for research and application.

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.

Senegal is a West African country with both extensive animal production systems, representative of the environmental, economic and animal health constraints specific to the Sahel region, and thriving commercial poultry and dairy production. An exploratory study was conducted in Senegal between 2021 and 2022 as a prelude to a case study of the Global Burden of Animal Diseases (GBADs) programme. An overview of existing animal production systems as well as the main priorities and issues in animal health on a national level was developed. A national workshop gathering representatives from the livestock production and academic sectors took place in Dakar in June 2022 with the objective of jointly developing a case study. The participants prioritised pastoralist production systems for cattle and agropastoral systems for small ruminants for the application of the GBADs programme. Through a series of activities, the participants highlighted the health, environmental, economic and socio-political challenges surrounding these systems, all of which limit their contribution to the well-being of pastoralist households, consumers and other stakeholders. While Senegal has in the past hosted a large number of research and cooperative projects on these two livestock systems, participants noted difficulties in obtaining, centralising and harmonising the existing data. This exploratory study led to the funding of a focused case study of the agropastoral small-ruminant sector that was carried out in 2023 in partnership with national and international organisations.

The Global Burden of Animal Diseases (GBADs) programme follows a multistage process to produce disease burden estimates in livestock and farmed aquatic animal production systems. The GBADs programme has broad goals of inclusivity, transparency and rigour. Meeting those goals means providing users of all levels of technical expertise with a clear explanation of the programme's output. In this way, the meaning and limitations of those results are clearly communicated, minimising the risk of misinterpretation. The first published estimates of disease burden have been calculated at farm level using a new metric called the Animal Health Loss Envelope. This metric estimates the cost of lost productivity and expenditure on disease control for profit-maximising producers by comparing current system performance to a hypothetical ‘ideal health'scenario. This ideal is a farm-specific concept and is critically different from an ideal health state when physiologically defined. The metric and its key concepts are described in this article.

Assessing the economic value of livestock such as cattle, goats, sheep, pigs, chickens and fish can offer information about their financial performance and economic importance at farm, national and global scale. Such information is needed for decision-making surrounding livestock finance, investment and strategic development. The aim of this study was to provide an overview of the key livestock valuation methods and associated data requirements. The study was conducted using a literature review. Five key livestock valuation methods were identified and described: historical costs, net current market value, replacement costs, net present value and cost of production. The findings of this study may be of interest to livestock scientists, veterinarians, policy-makers and other stakeholders who aim to assess the economic value of livestock herds. The Global Burden of Animal Diseases programme relied on the outcomes of this study to identify methods for the estimation of the economic value of livestock at the global scale and for its Ethiopia and Indonesia case studies.

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.

Estimates of livestock biomass can be used as denominators in disease burden estimates, in addition to informing assessments of resource use and environmental impacts. This article explores the challenges of accurately estimating biomass across different scales and data ecosystems, with a particular focus on the use of biomass in the Global Burden of Animal Diseases programme. The greatest of these challenges is a lack of subgroup (breed, age, sex)-specific data on populations and liveweights at national and subnational level. This can be overcome by using global datasets and generic estimates of liveweight for each species, though this approach fails to account for the diversity of livestock systems.

The presence of transmissible disease in livestock has a major impact on welfare and economics in animal and public health. A lack of data enables the spread of diseases due to misinformed decision-making on prevention and control. Low-resource settings face challenges in providing data, turning data availability into a development issue. For this study, a large dataset (n = 997) was collected on prevalence and seroprevalence estimates on viral (n = 224), bacterial (n = 83) and parasitic (n = 690) diseases in backyard chickens in low- and middle-income countries (LMICs). These estimates originate from 306 studies identified during the screening phase of a systematic literature review. An attempt was made to classify the studies according to the Food and Agriculture Organization of the United Nations'classification system for family poultry production systems. Of the studies, 98.7% (302/306) focused on a single poultry production system, while 1.3% (4/306) targeted two different production systems. Within the group of studies that covered one production system, 85.4% (258/302) were classified as ‘small extensive scavenging or extensive scavenging,'‘small extensive scavenging'and/or ‘extensive scavenging'. In addition, 52% (159/306) of the studies did not report information on chicken breed type. No data were found on any relevant disease for 56.9% (78/137) of LMICs, signifying a potential data gap. Of the estimates on viral and bacterial diseases, 71.0% (218/307) corresponded to diseases notifiable to the World Organisation for Animal Health, highlighting a tendency to measure disease occurrence for diseases relevant to trade. The latter might not necessarily be priority diseases for the producers, however. Furthermore, 72.3% (222/307) of the estimates originate from random samples and could be used to estimate prevalence in backyard chickens using imputation methods, thus bridging the data gap.