Health, Poverty and Place: Modeling Inequalities in Accra Using RS and GIS

描述(申请人提供)：该项目通过详细分析加纳阿克拉的健康空间差异，旨在为解释贫穷国家城市中的城市健康不平等提供一个模式。使用加纳的阿克拉，我们将产生一些方法，我们希望这些方法将成为与发展中世界其他主要城市进行比较分析的模板。该项目将以政府和负责改善整体健康和减少健康不平等的发展机构可立即获得的格式，制作城市地区健康和死亡率差异的地理概要；绘制城市贫困(收入和财富)分布图，并评估其与选定的健康和死亡结果的空间联系；利用遥感和地理信息系统技术，衡量不利的健康和死亡结果与邻里生态的关系，包括与从多光谱高空间分辨率卫星图像可见的自然特征和建筑结构观察得出的空间测量的联系；并评估社区一级的变量，包括社会组织和机构，在扣除个人特征后，对造成健康和死亡率不平等的额外贡献。我们的研究涉及以下主要步骤：(I)使用人口普查和调查数据以及来自遥感图像的信息，在空间和时间上应用新的方法来定义城市社区；(2)在阿克拉社区的有目的的样本中，利用实地评估验证数据得出的社区定义、属性和边界；(3)根据导出的社区定义以及现有和更新的图像和地理层，收集现有的基于普查、基于调查和基于重要统计的社区层面的发病率和死亡率测量；(4)重新访谈(2008年)2003年阿克拉妇女健康调查的受访者，以产生社区一级健康结果的新衡量标准以及这些结果的变化；(5)采用空间分析、多变量和多水平分析来预测阿克拉社区之间和社区内的健康结果的不平等；(6)开发模型，以WHS和国土安全部的数据为基础，结合图像预测社区的健康结果；(7)将建模算法应用于两个关键资源--人口与健康调查和遥感图像--以预测阿克拉社区一级健康结果的变异性(不平等)；以及(8)将阿克拉当地的结果用于卫生政策和规划目的，并使用数据相对丰富的阿克拉的结果来开发模型，这些模型随后可用于估计撒哈拉以南非洲数据贫乏城市的卫生空间变异性。

DESCRIPTION (provided by applicant): This project, through a detailed analysis of spatial disparities in health in Accra, Ghana, aims to provide a model for the interpretation of urban health inequalities in cities in poor countries. Using Accra in Ghana, we will generate methods that we hope will serve as templates for comparative analyses of other major cities in the developing world. The project will produce a geographical synopsis of the differentials in health and mortality within the urban area in a format immediately accessible to government and the development agencies tasked with the improvement of health overall and with the reduction of health inequalities; map the distribution of poverty (both income and wealth) in the city and assess its spatial association with selected health and mortality outcomes; using remote sensing and GIS technology, measure the association of adverse health and mortality outcomes with neighborhood ecology, including the association with spatial measures derived from observations of physical features and built structures visible from multi-spectral high spatial resolution satellite imagery; and assess the additional contribution of community-level variables including social organization and institutions to the production of inequalities in health and mortality, net of individual-level characteristics. Our research involves the following major steps: (i) apply new methods of defining urban neighborhoods across space and time using census and survey data and information from remotely sensed imagery; (2) validate data-derived neighborhood definitions, attributes, and boundaries with field assessments in a purposive sample of Accra neighborhoods; (3) assemble existing census-based, survey-based, and vital statistics-based measures of morbidity and mortality at the neighborhood level, based on the derived neighborhood definitions, as well as existing and updated imagery and geographic layers; (4) re-interview (in 2008) the respondents to the 2003 Accra Women's Health Survey to generate new measures of neighborhood-level health outcomes and changes in those outcomes; (5) employ spatial analytic, multivariate and multi-level analyses to predict the inequalities in health outcomes between and within neighborhoods of Accra; (6) develop models that build on the WHS and DHS data in combination with the imagery to predict health outcomes by neighborhood; (7) apply the modeling algorithms to two key resources-the Demographic and Health Survey and remotely sensed imagery-to predict the variability (inequality) in neighborhood level health outcomes in Accra; and (8) employ the results locally in Accra for health policy and planning purposes, and use the results from relatively data-rich Accra to develop models that can subsequently be used to estimate the spatial variability in health in data-poorer cities in sub-Saharan Africa.