Using economic and social data to improve veterinary vaccine development: Learning lessons from human vaccinology

The drivers of vaccine development are many and varied. They include, for example, recognition of the burden of a vaccine-targeted disease, prioritisation of the multiple problems associated with a disease, consideration of the differing socio-economic situations under which vaccines are used, the influence of advocacy groups, and assessment of the feasibility of large-scale vaccine manufacture and distribution. In the field of human health, data-driven development of vaccines is becoming increasingly common through the availability of reliable information on the Global Burden of Disease (GBD) and stringent evaluations of vaccination programmes utilising empirical data on costing and effectiveness, and standardised cost-effectiveness thresholds. The data generated from such analyses allow policymakers, implementing partners, industries and researchers to make decisions based on the best, and most contextually relevant, available evidence. In this paper, we wish to explore the current use of economic and social data for the development of veterinary vaccines. Through comparison with the development of human vaccines, we will look for opportunities in animal health sciences to better integrate socio-economic data and analyses into the process of veterinary vaccine selection, development, and field implementation. We believe that more robust animal health impact assessments could add value to veterinary vaccine development by improving resource allocation and animal disease management

Re-thinking public health: Towards a new scientific logic of routine animal health care in European industrial farming

From Springer Nature via Jisc Publications RouterHistory: received 2020-11-03, accepted 2021-08-19, registration 2021-09-02, pub-electronic 2021-09-20, online 2021-09-20, collection 2021-12Publication status: PublishedAbstract: This study makes the case for a new scientific logic of routine animal health care in industrial farming in Europe. We argue that the social regime underpinning scientific research and development on chronic animal disease management (CADM) in Europe stifles innovation and sustains a productivist model of animal husbandry that facilitates and maintains chronic animal diseases rather than eliminating them. Drawing on documentary analysis and qualitative interviews, the study explores the science of CADM in the broiler, cattle and pig sectors of the European food industry. Our findings show that in these major sectors, research and development on CADM is largely orientated towards a logic of growth, profitability and control rather than a recognition of the interconnection between chronic animal diseases, the food industry, and people (especially consumers) as advocated by the One Health approach. The study contributes to the literature on medical humanities and science and technology studies within One Health and public health in two ways: First, we draw new focus towards chronic animal diseases that are non-transmissible to humans and argue that while these are not zoonoses, they are equally worthy of attention for managing the emergence of new pathogens and diseases. Second, we expand the conceptualisation of One Health to include chronic animal health conditions. Our argument is that public health as an outcome of the One Health approach should be a term of reference that applies to humans and nonhumans alike whether they be farmed animals, practitioners or consumers

Ensemble preconditioning for Markov chain Monte Carlo simulation

We describe parallel Markov chain Monte Carlo methods that propagate a collective ensemble of paths, with local covariance information calculated from neighboring replicas. The use of collective dynamics eliminates multiplicative noise and stabilizes the dynamics thus providing a practical approach to difficult anisotropic sampling problems in high dimensions. Numerical experiments with model problems demonstrate that dramatic potential speedups, compared to various alternative schemes, are attainable

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Successes and Problems with Measuring Water Consumption in Beef Systems

Beef production is considered to have a large water footprint, with values ranging from 3.3 to 75,000 L H20/kg. The water consumption in beef production is primarily associated with feed, estimated to be about 98%, with other requirements representing less than 1%. However, beef production is a complex system where cattle are often raised in different areas using a range of resources over their lifetime. This complexity is demonstrated using three countries with very different environments and production systems, namely Australia, Brazil, and Kenya. To achieve efficient water use in beef systems, and food systems more generally, a classification system that reflects how animals are managed, slaughtered, and processed is required. Methods for assessing water use in livestock systems, from production to consumption, need to be standardized, whilst also including the alternative uses, multiple uses, and benefits of a certain resource in a specific location.</p

Relationship between Material Properties and Transparent Heater Performance for Both Bulk-like and Percolative Nanostructured Networks

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Relationship between Material Properties and Transparent Heater Performance for Both Bulk-like and Percolative Nanostructured Networks

Transparent heaters are important for many applications and in the future are likely to be fabricated from thin, conducting, nanostructured networks. However, the electrical properties of such networks are almost always controlled by percolative effects. The impact of percolation on heating effects has not been considered, and the material parameter combinations that lead to efficient performance are not known. In fact, figures of merit for transparent heaters have not been elucidated, either in bulk-like or percolative systems. Here, we develop a simple yet comprehensive model describing the operation of transparent heaters. By considering the balance of Joule heating <i>versus</i> power dissipated by both convection and radiation, we derive an expression for the time-dependent heater temperature as a function of both electrical and thermal parameters. This equation can be modified to describe the relationship between temperature, optical transmittance, and electrical/thermal parameters in both bulk-like and percolative systems. By performing experiments on silver nanowire networks, systems known to display both bulk-like and percolative regimes, we show the model to describe real systems extremely well. This work shows the performance of transparent heaters in the percolative regime to be significantly less efficient compared to the bulk-like regime, implying the diameter of the nanowires making up the network to be critical. The model allows the identification of figures of merit for networks in both bulk-like and percolative regimes. We show that metallic nanowire networks are most promising, closely followed by CVD graphene, with networks of solution-processed graphene and carbon nanotubes being much less efficient