基于住户调查数据的疫苗接种覆盖率估计的建模与呈现
Modeling and presentation of vaccination coverage estimates using data from household surveys
AI总结：
本文探讨利用住户调查数据生成疫苗接种覆盖率地图时的建模与呈现问题，强调考虑调查设计和分层，提出控制地图不确定性的新呈现方法，并以尼日利亚麻疹数据为例。
摘要：
通过将贝叶斯地质统计模型拟合至住户调查数据来生成高分辨率疫苗接种覆盖率地图的做法日益流行。通常，此类调查采用分层整群抽样设计。我们讨论了地图生成过程中两个关键方面的若干重要选择：建模中对调查设计的考量，以及估计值及其不确定性的适当呈现。具体而言，我们考虑了在拟合地质统计模型时，对调查分层和整群层面非空间超额变异进行说明的重要性。我们还讨论了基于模型的估计值在地理尺度与精度之间的权衡，并展示了强调结果概率解释的制图与排序可视化方法。我们提出了一种新的覆盖率地图呈现方法，以允许对整体地图不确定性水平进行比较和控制。我们以尼日利亚的麻疹疫苗接种覆盖率作为激励性示例，并使用2018年尼日利亚人口与健康调查的数据来说明不同问题。
英文摘要：
It is becoming increasingly popular to produce high-resolution maps of vaccination coverage by fitting Bayesian geostatistical models to data from household surveys. Often, the surveys adopt a stratified cluster sampling design. We discuss a number of crucial choices with respect to two key aspects of the map production process: the acknowledgment of the survey design in modeling, and the appropriate presentation of estimates and their uncertainties. Specifically, we consider the importance of accounting for survey stratification and cluster-level non-spatial excess variation in survey outcomes when fitting geostatistical models. We also discuss the trade-off between the geographical scale and precision of model-based estimates, and demonstrate visualization methods for mapping and ranking that emphasize the probabilistic interpretation of results. A novel approach to coverage map presentation is proposed to allow comparison and control of the overall map uncertainty level. We use measles vaccination coverage in Nigeria as a motivating example and illustrate the different issues using data from the 2018 Nigeria Demographic and Health Survey.
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