Geographical Analysis in Vaccine Efficacy Trials: Spatial Confounders, Effect Modifiers, and Herd Immunity Measurement

这一研究项目将开发和试验用于疫苗试验的空间分析方法，因为现有方法限制了结果的外推，有时有效性值得怀疑。它将使用空间方法来控制异质性疾病暴露（空间效应调节剂）和疾病结果的空间偏差（空间混杂因素）。1985年，在孟加拉国的Matlab进行了以社区为基础的个体随机口服霍乱疫苗试验。这项双盲试验测量了两种疫苗的效力，即B亚单位灭活全细胞（BS-WC）和全细胞灭活疫苗（WC）。15岁及以上的女性和2至15岁的儿童是试验的目标群体。为了确定研究地区的霍乱病例，调查人员在一家医院和两个社区治疗中心进行了被动监测。在5年的随访中，BS-WC组的保护效能为49%，WC组的保护效能为47%。被动监测可能会引入偏见，因为前往治疗中心的机会通常是距离的函数，会影响求医行为。此外，由于社会环境环境和疾病暴露水平在空间上有所不同，研究区域不同地区的疗效可能有所不同。本研究将使用地理信息系统（GIS）确定：(1)霍乱疫苗效力在研究区域的空间差异；(2)哪些生态社会环境变量与霍乱疫苗效力相关（即哪些变量是效果调节剂）；(3)保护效果如何随治疗设施的可及性而变化（即可及性是否为空间混杂因素）；(4)安慰剂组的霍乱发病率是否与疫苗覆盖率相关（即群体免疫是否重要）。我们将使用研究者已经收集的三个数据集，包括：(1)一个大型霍乱疫苗试验数据库，(2)一个综合的纵向人口统计数据库，其中选择了疫苗试验参与者的农村人口约20万，以及(3)同一研究区域人口的准确家庭级空间数据库。该空间数据库与人口和疫苗数据集一起，将有助于为所有三个数据集增加一个综合、全面和准确的空间组成部分。这项研究的更广泛的影响是理论和方法。它将以疾病生态学的医学地理理论为基础，表明卫生干预（例如疫苗）的效果受到空间上分布不均的变量复合体（即效果修饰因子）的影响。它将表明，由于现有方法中的空间偏见，空间视角是必要的。它还将展示如何利用空间视角为迄今无法测量的事物（即群体免疫）开发新的方法。从空间角度理解人与环境的相互作用是地理学的核心概念之一，本项目将拓展这一理论领域。它将具体建立在现有的医学地理疾病生态学理论的基础上，并将其置于生物复杂性等现代科学框架中。它还将作为方法学案例研究，描述如何在疫苗试验中使用地理方法。

This research project will develop and test spatial analytical methods for vaccine trials because existing methods limit the extrapolation of results and are sometimes of questionable validity. It will use spatial methods to control for heterogeneous disease exposures (spatial effect modifiers) and spatial bias in disease outcomes (spatial confounders). In 1985, a community-based, individually-randomized oral cholera vaccine trial was conducted in Matlab, Bangladesh. The double-blind trial measured the efficacy of two vaccines, the B subunit-killed whole cell (BS-WC) and the killed whole cell only (WC) vaccine. Females aged 15 years and older, and children aged 2 to 15 were the target group in the trial. To identify the cholera cases from the study area, the investigators conducted a passive surveillance at one hospital and two community-based treatment centers. During 5 years of follow-up, the protective efficacy for the BS-WC group was 49% and for the WC group it was 47%. Passive surveillance can introduce bias because access to treatment centers, which is usually a function of distance, influences health-seeking behavior. Also, efficacy might differ in different parts of the study area because socio-environmental circumstances and therefore disease exposure levels vary in space. This study will use a geographic information system (GIS) to determine: (1) how cholera vaccine efficacy varies spatially in the study area; (2) what ecological socio-environmental variables are related to cholera vaccine efficacy (i.e., which variables are effect modifiers); (3) how protective efficacy varies with access to treatment facilities (i.e., whether access is a spatial confounder; and (4) whether cholera incidence in the placebo group is related to vaccine coverage rates (i.e., is herd immunity important). We will use three data sets, already collected by the investigators, including: (1) a large cholera vaccine trial database, (2) a comprehensive longitudinal demographic database of the rural population of approximately 200,000 from which the vaccine trial participants were selected, and (3) an accurate household-level spatial database of the same study area population. This spatial database, in conjunction with the demographic and vaccine datasets, will facilitate adding an integrated, comprehensive, and accurate spatial component to all three datasets. The broader impacts of this study are both theoretical and methodological. It will build on the medical geographic theory of disease ecology by showing that the effect of a health intervention (e.g., a vaccine) is modified by spatially heterogeneously distributed complexes of variables (i.e., effect modifiers). It will show that a spatial perspective is necessary because of spatial bias in existing methodologies. It will also show how a spatial perspective can be used to develop new methodologies for something that has until now been impossible to measure (i.e., herd immunity). Understanding human-environment interaction from a spatial perspective is one of the core concepts of geography and this project will expand this theoretical area. It will specifically build on existing medical geographic disease ecology theory and place it within modern scientific frameworks such as biocomplexity. It will also serve as a methodological case study that describes how geographical methods can be used in vaccine trials.