RAISE: Neighborhood Environments as Socio-Techno-bio Systems

这个跨学科RAISE奖是由文化人类学项目、环境工程项目、生物人类学项目、科学、技术和社会项目、综合活动办公室、社会、行为和经济科学理事会和工程理事会共同资助的。总体目标是开发方法工具，以理解通过社会经济条件、环境和人类生物轨迹之间的反馈回路连接的复杂、动态的社会技术生物系统。这将通过一个由环境工程师、人类学家和流行病学家组成的团队，对水资源信托进行多方面的案例研究来完成。研究人员选择水信任作为开发这些综合方法的重点，因为环境工程师发现，在决定人们是否获得安全用水方面，对水信任的恶化可能与水质一样重要。然而，要理解为什么会这样，需要结合环境、人类学和健康研究。这将建立一种适用于其他地点和其他系统的方法模型，这将有助于对工程、社会和生命科学中相互关联的复杂系统有更全面的了解。研究人员将收集水资源信任、实时水质、社区环境、不平等和健康之间联系的数据。这项研究将在墨西哥城的15个社区进行，这是一个合适的研究地点，因为那里的社区有不同的特征，研究人员可以获得居民健康轨迹的纵向数据。此外，由于墨西哥城面临着许多水资源方面的挑战，因此它是一个很好的试验台，可以在社区系统层面探索技术、社会和生物的相互作用和反馈。研究人员将从15个社区的家庭样本中收集数据。数据将包括：定性人种学数据（用水、对水质的信任、供水结构、社会凝聚力、安全、食物环境和建筑环境）；使用社区评估量表的定量社会经济数据；环境工程数据，包括抓取采样以测量与人类生物变化相关的水质特征（如毒物、病毒、微量有机物和抗生素抗性基因）；实时高分辨率传感器测量基本水质参数（温度、压力、浊度和氯残留）。他们还将收集所有住户的尿液样本，以监测污染物在住户体内的流动；通过短信告知水质、系统故障和可用性，让居民成为公民科学家；并利用现有的纵向分子流行病学数据，以前收集在这些社区的母亲/孩子/对。这些数据将被汇编成人类行为、建筑环境和生物过程之间相互联系和反馈关系的模型，以建立水信任。

This inter-disciplinary RAISE award is jointly funded by the Cultural Anthropology Program, the Environmental Engineering Program, the Biological Anthropology Program, the Science, Technology, and Society Program, the Office of Integrative Activities, the Social, Behavioral, and Economic Sciences Directorate, and the Engineering Directorate. The overarching goal is to develop methodological tools for understanding complex, dynamic socio-techno-biological systems connected through feedback loops between socio-economic conditions, environments, and human biological trajectories. This will be done by engaging a team of environmental engineers, anthropologists, and epidemiologists in a multi-faceted case study of water trust. The researchers have chosen water trust as a focus for developing these integrative methodologies because environmental engineers have found that the deterioration of trust in water can be as important as water quality in determining whether people access safe water. However, understanding why this is so requires combining environmental, anthropological, and health research. This will model an approach amenable to use in other locations and with other systems, which will contribute to a more general understanding of linked complex systems across engineering and the social and life sciences. The researchers will collect data on linkages between water trust, real-time water quality, neighborhood environments, inequality, and health. The research will be carried out in fifteen neighborhoods in Mexico City, which is an appropriate site for the research because neighborhoods there have distinct identities and the researchers have access to longitudinal data on residents' health trajectories. Also, because it has many water challenges, Mexico City is a good testbed for probing technical, social, and biological interactions and feedbacks at a neighborhood-systems level. The researchers will collect data In a sample of households in 15 neighborhoods. Data will include: qualitative ethnographic data (water use, trust in water quality, water provisioning structures, social cohesion, security, food environments, and built environments); quantitative socio-economic data using a neighborhood assessment scale; environmental engineering data, including, grab sampling to measure water quality characteristics (such as toxicants, viruses, trace organics, and antibiotic resistance genes) that are linked to biological alterations in humans; and real-time high-resolution sensor measurements of basic water quality parameters (temperature, pressure, turbidity, and chlorine residue). They will also collect urine samples from all household residents to monitor movement of contaminants through residents' bodies; engage residents as citizen scientists through text messaging about water quality, system breakdowns, and availability; and leverage existing longitudinal molecular epidemiological data previously collected on mother child/pairs in these neighborhoods. These data will be compiled to model the interlinked and feedback relationships between human behaviors, built environments, and biological processes in the creation of water trust.