• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Construction and evaluation of epidemiologic simulation models for the within- and among-unit spread and control of infectious diseases of livestock and poultry.
【24h】

Construction and evaluation of epidemiologic simulation models for the within- and among-unit spread and control of infectious diseases of livestock and poultry.

机译：畜禽传染病在单位内和单位间传播与控制的流行病学模拟模型的构建和评估。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Epidemiologic modeling is an increasingly common method of estimating the potential impact of outbreaks of highly contagious diseases, such as foot-and-mouth disease (FMD) and highly pathogenic avian influenza (HPAI), in populations of domesticated animals. Disease models are also used to inform policy decisions regarding disease control methods and outbreak response plans, to estimate the possible magnitude of an outbreak, and to estimate the resources needed for outbreak response. Although disease models are computationally sophisticated, the quality of the results of modeling studies depends on the quality and accuracy of the data on which they are based, and on the conceptual soundness and validity of the models themselves. For such models to be credibly applied, they should realistically represent the systems they are intended to reflect, should be based to as great an extent as possible on valid data, and should be subjected to careful and ongoing scrutiny.;Two key steps in the evaluation of epidemiologic models are model verification and model validation. Verification is the demonstration that a computer-driven model is operating correctly, and conforms to its intended design. Validation refers to the process of determining how well a model corresponds to the system that it intended to represent. For a veterinary epidemiologic model, validation would address issues such as how well the model represents the dynamics of the disease in question in a population to which the model is applied, and how well the model represents the application of different measures for disease control. Among the steps that can be taken by epidemiologic modelers to facilitate the processes of model verification and validation are to clearly state the purpose, assumptions, and limitations of a model; to provide a detailed description of the conceptual model for use by everyone who might be tasked with evaluation of a model; document steps already taken to test the model; and thoroughly describe the data sources and the process used to produce model input parameters from data.;The realistic representation of the dynamics of spread of disease within individual herds or flocks can have important implications for disease detection and surveillance, as well as for disease transmission between herds or flocks. We have developed a simulation model of within-unit (within-herd or within-flock) disease spread that operates at the level of the individual animal, and fully incorporates sources of individual-level variation such as variability in the durations of incubating and infectious periods, the stochastic nature of disease spread among individuals, and the effects of vaccination. We describe this stochastic model, along with the processes employed for verification and validation. The incorporation of this approach to modeling of within-unit disease dynamics into models of between-unit disease spread should improve the utility of these models for emergency preparedness and response planning by making it possible to assess the value of different approaches to disease detection and surveillance, in populations with or without some existing level of vaccine immunity.;Models rely not only on realistic representations of the systems of interest, but also on valid and realistic information. For spatially explicit models of the spread and control of disease in populations of livestock and poultry, this means a heavy reliance upon valid spatial representations of the populations of interest, including such characteristics as the geographic locations of farms and their proximity to others in the population. In the United States, limited information regarding the locations of actual farm premises is available, and modeling work often makes use of artificially generated population datasets. In order to evaluate the accuracy and validity of the use of such artificially generated datasets, we compared the outcomes of mechanistic epidemiologic simulation models that were run using an empirical population dataset to those of models that made use of several different synthetic population datasets. Although we found generally good qualitative agreement among models run using various population datasets, the quantitative differences in model outcomes could be substantial. When quantitative outcomes from epidemiologic models are desired or required, care should be taken to adequately capture or describe the uncertainty in model-based outcomes due to the use of synthetic population datasets.
机译：流行病学建模是一种越来越普遍的方法，用于评估高传染性疾病（如口蹄疫（FMD）和高致病性禽流感（HPAI））对家畜的爆发所产生的潜在影响。疾病模型还用于为有关疾病控制方法和疫情应对计划的政策决策提供信息，以估算可能的疫情规模，并估算疫情应对所需的资源。尽管疾病模型计算复杂，但是建模研究结果的质量取决于其所基于数据的质量和准确性，以及模型本身的概念健全性和有效性。为了使此类模型得到可靠的应用，它们应现实地表示它们打算反映的系统，应在很大程度上以有效数据为基础，并应进行认真且持续的审查。流行病学模型的评估是模型验证和模型验证。验证是计算机驱动的模型正确运行并符合其预期设计的演示。验证是指确定模型与要表示的系统的对应程度的过程。对于兽医流行病学模型，验证将解决以下问题，例如，该模型在应用该模型的人群中如何很好地代表了所讨论疾病的动态，以及该模型在某种程度上代表了疾病控制的不同措施的应用。流行病学建模人员可以采取的促进模型验证和确认过程的步骤包括清楚地说明模型的目的，假设和局限性。提供概念模型的详细描述，以供可能负责模型评估的每个人使用；记录已经采取的测试模型的步骤；并彻底描述数据源和用于从数据中产生模型输入参数的过程。真实地表示个体畜群或鸡群中疾病传播动态的过程，对于疾病的检测和监测以及疾病的传播都具有重要的意义。在畜群或羊群之间。我们已经开发了在个体动物水平上运行的单位内（群内或群内）疾病传播的模拟模型，并充分考虑了个体水平变异的来源，例如潜伏期和传染性的可变性在此期间，疾病的随机性会在个人之间传播，并且还会接种疫苗。我们描述了这种随机模型，以及用于验证和确认的过程。将这种对单位内疾病动态建模的方法结合到单位间疾病传播的模型中，应该可以通过评估疾病检测和监测的不同方法的价值来提高这些模型在应急准备和响应计划中的效用。在具有或不具有某种现有水平的疫苗免疫性的人群中；模型不仅依赖于感兴趣系统的真实表示，而且依赖于有效而现实的信息。对于在牲畜和家禽种群中疾病传播和控制的空间明确模型，这意味着严重依赖目标种群的有效空间表示，包括诸如农场的地理位置及其与种群中其他种群的邻近度等特征。 。在美国，关于实际农场场所的位置的信息有限，并且建模工作通常使用人工生成的人口数据集。为了评估使用这种人工生成的数据集的准确性和有效性，我们将使用经验人口数据集运行的机械流行病学模拟模型的结果与使用几个不同的综合人口数据集的模型进行了比较。尽管我们发现使用各种人口数据集运行的模型之间通常具有良好的定性一致性，但模型结果的数量差异可能很大。当期望或需要流行病学模型的定量结果时，应注意充分捕获或描述由于使用合成人群数据集而导致的基于模型的结果中的不确定性。

著录项

  • 作者

    Reeves, Aaron.;

  • 作者单位

    Colorado State University.;

  • 授予单位 Colorado State University.;
  • 学科 Health Sciences Epidemiology.;Biology Veterinary Science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 168 p.
  • 总页数 168
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号