Decision analysis approach to risk/benefit evaluation in the ethical review of controlled human infection studies

Risks and benefit evaluation for controlled human infection studies, where healthy volunteers are deliberately exposed to infectious agents to evaluate vaccine efficacy, should be explicit, systematic, thorough, and non-arbitrary. Decision analysis promotes these qualities using four steps: (1) determining explicit criteria and measures for evaluation, (2) identifying alternatives to the study, (3) defining the models used to estimate the measures for each alternative, and (4) running the models to produce the estimates and compare the alternatives. In this paper, we describe how decision analysis might be applied by funders and regulators, as well as by others contemplating the use of novel controlled human infection studies for vaccine development and evaluation.     

多种天敌控制多种害虫的模糊数学模型

从生态经济学的原理出发，利用模糊集理论，探讨如何评价天敌控制多种害虫的为害作用，提出了多种天敌控制多种害虫的模糊数学模型。同时又得到了天敌对害虫的控制能力C，影响率G，影响强度H，及权数ω(x)的计算公式，以及在天敌作用下安全度的讨论与分析。     

Playing it safe? Solitary vervet monkeys (Chlorocebus pygerythrus) choose high‐quality foods more than those in competition

An important goal in foraging ecology is to determine how biotic and abiotic variables impact the foraging decisions of wild animals and how they move throughout their multidimensional landscape. However, the interaction of food quality and feeding competition on foraging decisions is largely unknown. Here we examine the importance of food quality in a patch on the foraging decisions of wild vervet monkeys (Chlorocebus pygerythrus) at Lake Nabugabo, Uganda using a multidestination platform array. The overall nutritional composition of the vervet diet was assessed and found to be low in sodium and lipids, thus we conducted a series of experimental manipulations in which the array was varied in salt and oil content. Although vervets prioritized platforms containing key nutrients (i.e., sodium and lipids) overall, we found that solitary vervets prioritized nutrient‐dense platforms more strongly than competing vervets. This finding was opposite to those in a similar experiment that manipulated food site quantity, suggesting that large, salient rewards may be worth competing over but slight differences in nutritional density may be only chosen when there are no potentially negative social consequences (i.e., aggression received). We also found that vervets chose platforms baited with oil‐only, and oil combined with salt, but not salt‐only, suggesting that energy was an important factor in food choice. Our findings demonstrate that when wild vervets detect differences in feeding patches that reflect nutritional composition, they factor these differences into their navigational and foraging decisions. In addition, our findings suggest that these nutritional differences may be considered alongside social variables, ultimately leading to the complex strategies we observed in this study.     

Nearest Neighbor Classification Rule for Mixtures of Discrete and Continuous Random Variables

In this paper very simple nonparametric classification rule for mixtures of discrete and continuous random variables is described. It is based on the method of nearest neighbor proposed by Cover and Hart (1967). The bounds on the limit of the nearest neighbor rule risks are given. Both lower and upper bound depend on the Bayes risk and the loss function. Finally the method is compared with other existing methods on some practical data set.     

Effects of a participatory approach,with systematic impact matrix analysis in herd health planning in organic dairy cattle herds

The animal health and welfare status in European organic dairy production does not in all aspects meet the organic principles and consumers’ expectations and needs to be improved. To achieve this, tailored herd health planning, targeted to the specific situation of individual farms could be of use. The aim of this study was to apply herd health planning in a structured participatory approach, with impact matrix analysis, not previously used in this context, in European organic dairy farms and to assess changes in animal health and welfare. Herd health planning farm visits were conducted on 122 organic dairy farms in France, Germany and Sweden. The farmer, the herd veterinarian and/or an advisor took part in the farm discussions. The researcher served as facilitator. Baseline data on the animal health status of the individual farm, collected from national milk recording schemes, were presented as an input for the discussion. Thereafter a systematic impact matrix analysis was performed. This was to capture the complexity of individual farms with the aim to identify the farm-specific factors that could have a strong impact on animal health. The participants (i.e. farmer, veterinarian and advisor) jointly identified areas in need of improvement, taking the health status and the interconnected farm system components into account, and appropriate actions were jointly identified. The researcher took minutes during the discussions, and these were shared with the participants. No intervention was made by the researcher, and further actions were left with the participants. The number of actions per farm ranged from 0 to 22. The change in mortality, metabolic diseases, reproductive performance and udder health was assessed at two time points, and potential determinators of the change were evaluated with linear regression models. A significant association was seen between change in udder health, as measured by the somatic cell count, and country. At the first follow-up, a significant association was also found between change in the proportion of prolonged calving interval and the farmers’ desire to improve reproductive health as well as with an increase in herd size, but this was not seen at the second follow-up. The degree of implementation of the actions was good (median 67%, lower quartile 40%, upper quartile 83%). To conclude, the degree of implementation was quite high, improvement of animal health could not be linked to the herd health planning approach. However, the approach was highly appreciated by the participants and deserves further study.     

Against autonomy: How proposed solutions to the problems of living wills forgot its underlying principle

Significant criticisms have been raised regarding the ethical and psychological basis of living wills. Various solutions to address these criticisms have been advanced, such as the use of surrogate decision makers alone or data science-driven algorithms. These proposals share a fundamental weakness: they focus on resolving the problems of living wills, and, in the process, lose sight of the underlying ethical principle of advance care planning, autonomy. By suggesting that the same sweeping solutions, without opportunities for choice, be applied to all, individual patients are treated as population-level groups—as a theoretical patient who represents a population, not the specific patient crafting his or her individualized future care plans. Instead, advance care planning can be improved through a multimodal approach that both mitigates cognitive biases and allows for customization of the decision-making process by allowing for the incorporation of a variety of methods of advance care planning.     

Atlas versus range maps: robustness of chorological relationships to distribution data types in European mammals

Aim Chorological relationships describe the patterns of distributional overlap among species. In addition to revealing biogeographical structure, the resulting clusters of species with similar geographical distributions can serve as natural units in conservation planning. Here, we assess the extent to which temporal, methodological and taxonomical differences in the source of species’ distribution data can affect the relationships that are found. Location Western Europe. Methods We used two data sets – the Atlas of European mammals and polygon range maps from the IUCN Global Mammal Assessment – both as presence–absence data for UTM 50 km × 50 km squares. We performed pairwise comparisons among 156 species for each data set to build matrices of the similarity in distribution across species, using both Jaccard’s and Baroni‐Urbani & Buser’s indices. We then compared these similarity matrices (chorological relationships), as well as the species richness and occurrence patterns from the two data sets. Results As expected, range maps increased both the mean prevalence per species and mean species richness per grid cell in comparison to atlas data, reflecting the general view that these data types respectively over‐ and underestimate species occurrence. However, species richness and occurrence patterns in atlas and range map data were positively associated and, most importantly, the chorological relationships underlying the two data sets were highly similar. Main conclusions Despite many methodological, temporal and taxonomical differences between atlas data and range maps, the chorological relationships encountered between species were similar for both data sets. Chorological analyses can thus be robust to the data source used and provide a solid basis for analytical biogeographical studies, even over broad spatial scales.     

Comparing multiple correspondence and principal component analyses with biomechanical signals. Example with turning the steering wheel

The purpose of this article is to compare Principal Component Analysis (PCA) and a much less used method, i.e. MCA (Multiple Correspondence Analysis) with data being first changed into membership values to fuzzy space windows. For such a comparison, data from an experimental study about turning the steering wheel is used. In a didactic perspective, this article only considers one multidimensional signal with 5 components: 3 linked to the steering wheel angle and hand positions and 2 to hand effort variables. A discussion weighs out the pros and the cons of both methods with criteria such as the possibility to show complex relational phenomena, the analysis/computing time or the information loss inherent to the averaging stage (in the perspective to analyze several hundreds of large multidimensional signals).