Current and potential use of animal disease data by stakeholders in the global south and north

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.

Per- and polyfluoroalkyl substances (PFAS) in livestock and game species: A review

Per- and polyfluoroalkyl substances (PFAS) are synthetic, organic chemicals that resist environmental breakdown. The properties that made PFAS into an industrial success also led to their persistence and bioaccumulation. As PFAS were widely used for many decades their presence is evident globally, and their persistence and potential for toxicity create concern for human, animal and environmental health. Following the precautionary principle, a reduction in human exposure is generally recommended. The most significant source of human exposure to PFAS is dietary intake (food and water) with additional exposure via dust. As PFAS concentrations have been more frequently studied in aquatic food sources, there is less understanding of exposure via terrestrial animals. To further define human exposure via animal products, it is necessary to determine PFAS concentrations and persistence in terrestrial livestock and game species. Studies assessing ambient concentrations of PFAS have noted that, aside from point sources of contamination, there is generally low input of PFAS into terrestrial agricultural food chains. However, livestock and game species may be exposed to PFAS via contaminated water, soil, substrate, air or food, and the contribution of these exposures to PFAS concentrations in food products is less well studied. This review focuses on perfluoroalkyl substances (PFAAs) and compiles information from terrestrial livestock and game species as a source of dietary exposure in humans, and discusses toxicokinetics and health effects in animals, while identifying future focus areas. Publications describing the transfer of PFAAs to farmed and hunted animals are scarce, and demonstrate large variability in distribution and elimination. We outline several relatively small, short-term studies in cattle, sheep, pigs and poultry. While negative effects have not been noted, the poultry investigations were the only studies to explicitly assess health effects. Comparative information is presented on PFAA concentrations in livestock products and edible tissues of game animals.

Short communication: Identifying key parameters for modelling the impacts of livestock health conditions on greenhouse gas emissions

Improved animal health can reduce greenhouse gas (GHG) emissions intensity in livestock systems while increasing productivity. Integrated modelling of disease impacts on farm-scale emissions is important in identifying effective health strategies to reduce emissions. However, it requires that modellers understand the pathways linking animal health to emissions and how these might be incorporated into models. A key barrier to meeting this need has been the lack of a framework to facilitate effective exchange of knowledge and data between animal health experts and emissions modellers. Here, these two communities engaged in workshops, online exchanges and a survey to i) identify a comprehensive list of disease-related model parameters and ii) test its application to evaluating models. Fifty-six parameters were identified and proved effective in assessing the potential of farm-scale models to characterise livestock disease impacts on GHG emissions. Easy wins for the emissions models surveyed include characterising disease impacts related to feeding.