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Characterizing epidemics in metapopulation cattle systems through analytic models and estimation methods for data-driven model inputs.

机译：通过分析模型和数据驱动的模型输入的估计方法来表征后代牛系统中的流行病。

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摘要

We have analytically discovered the existence of two global epidemic invasion thresholds in a directed meta-population network model of the United States cattle industry. The first threshold describes the outbreak of disease first within the core of the livestock system while the second threshold describes the invasion of the epidemic into a second class of locations where the disease would pose a risk for contamination of meat production. Both thresholds have been verified through extensive numerical simulations. We have further derived the relationship between the pair of thresholds and discovered a unique dependence on the network topology through the fractional compositions and the in-degree distributions of the transit and sink nodes.;We then addressed a major challenge for epidemiologists and their efforts to model disease outbreaks in cattle. There is a critical shortfall in the availability of large-scale livestock movement data for the United States. We meet this challenge by developing a method to estimate cattle movement parameters from publicly available data. Across 10 Central States of the US, we formulated a large, convex optimization problem to predict the cattle movement parameters which, having minimal assumptions, provide the best fit to the US Department of Agriculture's Census database and follow constraints defined by scientists and cattle experts. Our estimated parameters can produce distributions of cattle shipments by head which compare well with shipment distributions also provided by the US Department of Agriculture.;This dissertation concludes with a brief incorporation of the analytic models and the parameter estimation. We approximated the critical movement rates defined by the global invasion thresholds and compared them with the average estimated cattle movement rates to find a significant opportunity for epidemics to spread through US cattle populations.
机译：我们已经分析性地发现了美国养牛业的定向元人口网络模型中存在两个全球流行病入侵阈值。第一个阈值首先描述了牲畜系统核心内的疾病暴发，而第二个阈值描述了该流行病向第二类场所的入侵，在这种情况下，该疾病会造成肉类生产受到污染的风险。这两个阈值已通过广泛的数值模拟得到验证。我们进一步推导了这对阈值之间的关系，并通过传输和汇聚节点的分数组成以及度内分布发现了对网络拓扑的独特依赖性。牛疾病暴发的模型。美国大规模牲畜移动数据的可用性严重不足。我们通过开发一种根据公开数据估算牛的运动参数的方法来应对这一挑战。在美国的10个中部州，我们制定了一个大的凸优化问题来预测牛的运动参数，该假设具有最小的假设，可以最适合美国农业部的人口普查数据库，并遵循科学家和牛专家定义的约束。我们估计的参数可以产生按人头计算的牛运输量分布，与美国农业部也提供的运输量分布相比较。;本文最后简要分析了分析模型和参数估计。我们估算了由全球入侵阈值定义的临界运动速度，并将其与估计的牛平均运动速度进行比较，以发现流行病在美国牛群中传播的重要机会。

著录项

  • 作者

    Schumm, Phillip Raymond Brooke.;

  • 作者单位

    Kansas State University.;

  • 授予单位 Kansas State University.;
  • 学科 Health Sciences Epidemiology.;Engineering Electronics and Electrical.;Applied Mathematics.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 193 p.
  • 总页数 193
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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