Test data generated by ~60 accredited member laboratories of the American Association of Veterinary Laboratory Diagnosticians (AAVLD) is of exceptional quality. These data are captured by 1 of 13 laboratory information management systems (LIMSs) developed specifically for veterinary diagnostic laboratories (VDLs). Beginning ~2000, the National Animal Health Laboratory Network (NAHLN) developed an electronic messaging system for LIMS to automatically send standardized data streams for 14 select agents to a national repository. This messaging enables the U.S. Department of Agriculture to track and respond to high-consequence animal disease outbreaks such as highly pathogenic avian influenza. Because of the lack of standardized data collection in the LIMSs used at VDLs, there is, to date, no means of summarizing VDL large data streams for multi-state and national animal health studies or for providing near-real-time tracking for hundreds of other important animal diseases in the United States that are detected routinely by VDLs. Further, VDLs are the only state and federal resources that can provide early detection and identification of endemic and emerging zoonotic diseases. Zoonotic diseases are estimated to be responsible for 2.5 billion cases of human illness and 2.7 million deaths worldwide every year. The economic and health impact of the SARS-CoV-2 pandemic is self-evident. We review here the history and progress of data management in VDLs and discuss ways of seizing unexplored opportunities to advance data leveraging to better serve animal health, public health, and One Health. 相似文献
It is assumed that Agent-Based Modeling is a useful technique for water management issues. In particular, it may provide a suitable framework for representing irrigated systems. The objective of this paper is to demonstrate its potential for a specific use: research on irrigated systems’ viability in the Senegal River Valley. The main assumption to be verified is that Multi-Agent Systems constitute a suitable architecture to study theoretically irrigated systems’ viability using simulations. By using Multi-Agent Systems, virtual irrigated systems can be designed that might then be used as virtual laboratories. These virtual labs constitute an alternative when real labs cannot exist for some reason.
In this paper we report on experiments we have conducted using such virtual labs for exploring an Agent-Based Model through the simulation of scenarios. A scenario is defined as a triplet: an environment, a set of individual rules, a set of collective rules. It is evaluated according to the longevity of the irrigated system. An index is defined, based on the ratio of long-enduring simulations among a set of repetitions of a given scenario. Even if simulation results display significant diversity for a given scenario due to random factors in the processes simulated, the ratio of long-enduring simulations is repeatable. This entails to explore the overall behavior of the virtual irrigated system and to build theories concerning the viability of Senegalese irrigated systems. An example is given showing the need for strong coherence for a given environment among individual rules and collective rules. 相似文献