Behavioural indicators of welfare in farmed fish

Behaviour represents a reaction to the environment as fish perceive it and is therefore a key element of fish welfare. This review summarises the main findings on how behavioural changes have been used to assess welfare in farmed fish, using both functional and feeling-based approaches. Changes in foraging behaviour, ventilatory activity, aggression, individual and group swimming behaviour, stereotypic and abnormal behaviour have been linked with acute and chronic stressors in aquaculture and can therefore be regarded as likely indicators of poor welfare. On the contrary, measurements of exploratory behaviour, feed anticipatory activity and reward-related operant behaviour are beginning to be considered as indicators of positive emotions and welfare in fish. Despite the lack of scientific agreement about the existence of sentience in fish, the possibility that they are capable of both positive and negative emotions may contribute to the development of new strategies (e. g. environmental enrichment) to promote good welfare. Numerous studies that use behavioural indicators of welfare show that behavioural changes can be interpreted as either good or poor welfare depending on the fish species. It is therefore essential to understand the species-specific biology before drawing any conclusions in relation to welfare. In addition, different individuals within the same species may exhibit divergent coping strategies towards stressors, and what is tolerated by some individuals may be detrimental to others. Therefore, the assessment of welfare in a few individuals may not represent the average welfare of a group and vice versa. This underlines the need to develop on-farm, operational behavioural welfare indicators that can be easily used to assess not only the individual welfare but also the welfare of the whole group (e. g. spatial distribution). With the ongoing development of video technology and image processing, the on-farm surveillance of behaviour may in the near future represent a low-cost, noninvasive tool to assess the welfare of farmed fish.Fundação para a Ciência e Tecnologia, Portugal [SFRH/BPD/42015/2007]info:eu-repo/semantics/publishedVersio

Which health technologies should be funded? A prioritization framework based explicitly on value for money

<p>Abstract</p> <p>Background</p> <p>Deciding which health technologies to fund involves confronting some of the most difficult choices in medicine. As for other countries, the Israeli health system is faced each year with having to make these difficult decisions. The Public National Advisory Committee, known as ‘the Basket Committee’, selects new technologies for the basic list of health care that all Israelis are entitled to access, known as the ‘health basket’. We introduce a framework for health technology prioritization based explicitly on value for money that enables the main variables considered by decision-makers to be explicitly included. Although the framework’s exposition is in terms of the Basket Committee selecting new technologies for Israel’s health basket, we believe that the framework would also work well for other countries.</p> <p>Methods</p> <p>Our proposed prioritization framework involves comparing four main variables for each technology: 1. Incremental benefits, including ‘equity benefits’, to Israel’s population; 2. Incremental total cost to Israel’s health system; 3. Quality of evidence; and 4. Any additional ‘X-factors’ not elsewhere included, such as strategic or legal factors, etc. Applying methodology from multi-criteria decision analysis, the multiple dimensions comprising the first variable are aggregated via a points system.</p> <p>Results</p> <p>The four variables are combined for each technology and compared across the technologies in the ‘Value for Money (VfM) Chart’. The VfM Chart can be used to identify technologies that are good value for money, and, given a budget constraint, to select technologies that should be funded. This is demonstrated using 18 illustrative technologies.</p> <p>Conclusions</p> <p>The VfM Chart is an intuitively appealing decision-support tool for helping decision-makers to focus on the inherent tradeoffs involved in health technology prioritization. Such deliberations can be performed in a systematic and transparent fashion that can also be easily communicated to stakeholders, including the general public. Possible future research includes pilot-testing the VfM Chart using real-world data. Ideally, this would involve working with the Basket Committee. Likewise, the framework could be tested and applied by health technology prioritization agencies in other countries.</p

Application of biomonitoring and support vector machine in water quality assessment*

The behavior of schools of zebrafish (Danio rerio) was studied in acute toxicity environments. Behavioral features were extracted and a method for water quality assessment using support vector machine (SVM) was developed. The behavioral parameters of fish were recorded and analyzed during one hour in an environment of a 24-h half-lethal concentration (LC50) of a pollutant. The data were used to develop a method to evaluate water quality, so as to give an early indication of toxicity. Four kinds of metal ions (Cu2+, Hg2+, Cr6+, and Cd2+) were used for toxicity testing. To enhance the efficiency and accuracy of assessment, a method combining SVM and a genetic algorithm (GA) was used. The results showed that the average prediction accuracy of the method was over 80% and the time cost was acceptable. The method gave satisfactory results for a variety of metal pollutants, demonstrating that this is an effective approach to the classification of water quality