26 research outputs found
Concepts for risk-based surveillance in the field of veterinary medicine and veterinary public health: Review of current approaches
Get PDFBACKGROUND: Emerging animal and zoonotic diseases and increasing international trade have resulted in an increased demand for veterinary surveillance systems. However, human and financial resources available to support government veterinary services are becoming more and more limited in many countries world-wide. Intuitively, issues that present higher risks merit higher priority for surveillance resources as investments will yield higher benefit-cost ratios. The rapid rate of acceptance of this core concept of risk-based surveillance has outpaced the development of its theoretical and practical bases. DISCUSSION: The principal objectives of risk-based veterinary surveillance are to identify surveillance needs to protect the health of livestock and consumers, to set priorities, and to allocate resources effectively and efficiently. An important goal is to achieve a higher benefit-cost ratio with existing or reduced resources. We propose to define risk-based surveillance systems as those that apply risk assessment methods in different steps of traditional surveillance design for early detection and management of diseases or hazards. In risk-based designs, public health, economic and trade consequences of diseases play an important role in selection of diseases or hazards. Furthermore, certain strata of the population of interest have a higher probability to be sampled for detection of diseases or hazards. Evaluation of risk-based surveillance systems shall prove that the efficacy of risk-based systems is equal or higher than traditional systems; however, the efficiency (benefit-cost ratio) shall be higher in risk-based surveillance systems. SUMMARY: Risk-based surveillance considerations are useful to support both strategic and operational decision making. This article highlights applications of risk-based surveillance systems in the veterinary field including food safety. Examples are provided for risk-based hazard selection, risk-based selection of sampling strata as well as sample size calculation based on risk considerations
HSCC2024.zip
No full textThe artifact supports all involved experimental data of the manuscript “A Sample-Driven Solving Procedure for the Repeated Reachability of Quantum Continuous-Time Markov Chains”, which implements the prototypes of an isolation-based algorithm and a sample-driven one for solving the repeated reachability problem over quantum continuous-time Markov chains. Some easy-to-use shell scripts are provided to manipulate the artifact for reproducing the data of Table 4 and Figure 4 in the manuscript. Random signals can be generated by single commands to validate the effectiveness of both the sample-driven algorithm and the isolation-based one. Furthermore, the artifact adopts a modular design, divided into three parts “Methods”, “Model” and “Experimental Instances” to facilitate extension and reuse.</p
Data and code for: Discrimination between the facial gestures of vocalizing and non-vocalizing lemurs and small apes using deep learning.
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