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Model-Based Statistical Methods for Public Health Surveillance Subject to Imperfect Observations.

机译：不完善观察结果下基于模型的公共卫生监测统计方法。

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摘要

We examine statistical modeling issues in three areas of public health surveillance: estimation of vaccination coverage, linking local observations and remotely sensed covariates, and adjustment for zero inflation due to underreporting.;When the proportion of the vaccinated population is an unknown value less than 100%, we explore application of logistic growth models, namely the standard logistic growth model and a reparameterization naturally constraining vaccination coverage parameter estimates. We compare the performance of three methods of estimation for each model (nonlinear least squares, maximum likelihood estimation, and Bayesian estimation).;Buruli ulcer is a neglected tropical disease affecting Australia and West Africa. We examine both on-site local water characteristics and broad scale remotely sensed environmental attributes with respect to the presence of the causative pathogen, Mycobacterium ulcerans. Our findings support hypotheses regarding conditions suitable for M. ulcerans growth, but diverge from other published results regarding the distribution of and factors related to Buruli ulcer disease. In addition, our findings suggest locations of reported cases and pathogen presence need not coincide, supporting the notion that human interaction with the environment plays a role in transmission.;In Buruli ulcer surveillance, districts which do not report cases are programmatically treated as districts without cases but are not actually confirmed as disease-free districts. Moreover, there is substantial reason to believe that some non-reporting districts actually have cases; consequently, our data are subject to 'false' zeros. We evaluate the performance of the zero inflated Poisson model in the presence of false zeros, as well as propose a hierarchical zero inflated Poisson model with the ability to estimate an observation's conditional probability of being a false zero given that a zero was observed.
机译：我们研究了公共卫生监测的三个方面的统计模型问题：估计疫苗接种覆盖率，将本地观察结果与遥感协变量联系起来以及由于漏报导致的零通货膨胀调整;当接种人群的比例未知值小于100时％，我们探索逻辑增长模型的应用，即标准逻辑增长模型和自然约束接种疫苗覆盖率参数估计值的重新参数化。我们比较每种模型的三种估计方法的性能（非线性最小二乘，最大似然估计和贝叶斯估计）。Buruli溃疡是一种影响澳大利亚和西非的被忽视的热带病。我们针对致病性病原体溃疡分枝杆菌的存在，研究了当地的局部水特征和大规模的遥感环境属性。我们的发现支持关于适于溃疡分枝杆菌生长的条件的假说，但与关于布鲁氏溃疡病的分布和相关因素的其他已发表结果不同。此外，我们的发现表明报告病例的位置和病原体的存在不必重合，从而支持了人类与环境的相互作用在传播中起作用的观点;在布鲁里溃疡监测中，未报告病例的地区被程序性地视为没有病例的地区。病例，但实际上并未被确认为无病区。此外，有充分的理由相信某些非报告地区确实有案件。因此，我们的数据为“假”零。我们评估存在虚假零的零膨胀泊松模型的性能，并提出一个分层零膨胀泊松模型，该模型能够估计观察到的条件值为假零的条件概率（假设已观察到零）。

著录项

  • 作者

    McClintock, Shannon Katherine.;

  • 作者单位

    Emory University.;

  • 授予单位 Emory University.;
  • 学科 Statistics.;Public health.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 160 p.
  • 总页数 160
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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