论文标题
对罕见和聚类疾病的基于人群采样的顺序自适应策略
Sequential adaptive strategy for population-based sampling of a rare and clustered disease
论文作者
论文摘要
提出了一种创新的抽样策略，该策略适用于针对罕见性状的大规模基于人群的调查，该调查不均匀地遍及感兴趣的地理领域。我们的建议的特征是能够根据手头调查的特定功能和挑战来量身定制数据收集。它基于将自适应组件整合到一个顺序选择中，该组件旨在在利用空间聚类的情况下加强对阳性案例的检测，并为管理物流和预算约束提供灵活的框架。为了说明选择偏差，提供了一个现成的加权系统，以释放公正和准确的估计。结核病患病率调查中说明了经验证据，这些调查在许多国家 /地区建议，并由世卫组织（WHO）作为象征性的典范，以改进的采样设计。还给出了仿真结果，以说明有关传统横截面采样方面提出的采样策略的优势和劣势。
An innovative sampling strategy is proposed, which applies to large-scale population-based surveys targeting a rare trait that is unevenly spread over a geographical area of interest. Our proposal is characterised by the ability to tailor the data collection to specific features and challenges of the survey at hand. It is based on integrating an adaptive component into a sequential selection, which aims to both intensify detection of positive cases, upon exploiting the spatial clusterisation, and provide a flexible framework for managing logistical and budget constraints. To account for the selection bias, a ready-to-implement weighting system is provided to release unbiased and accurate estimates. Empirical evidence is illustrated from tuberculosis prevalence surveys, which are recommended in many countries and supported by the WHO as an emblematic example of the need for an improved sampling design. Simulation results are also given to illustrate strengths and weaknesses of the proposed sampling strategy with respect to traditional cross-sectional sampling.
