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Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

机译:墨西哥湾地区社区健康观测系统的框架:为未来的灾害做准备

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The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop.
机译:墨西哥湾(GOM)地区易患灾害,包括经常性的石油泄漏,飓风,洪水,工业事故,有害的藻类盛开,以及当前的Covid-19大流行。 GOM和U.S.的其他地区缺乏足够的基线健康信息,以识别,属性,减轻和促进预防灾害的主要健康影响。发展能力评估未来灾害的不良人体健康后果需要建立一个全面,持续的社区卫生观察系统,类似于广泛且成熟的环境观测系统。我们提出了一个组合六个水平的健康数据领域的系统,从三个现有,国家调查和研究开始加上三个新的嵌套,纵向队列研究。后者是系统的独特和最重要的部分,并专注于五个GOM州的沿海地区。提出了一个统计的参与者样本,为新的队列研究提出了分类,以确保城市和农村人口的比例包容,并根据需要额外招聘,以便从特别脆弱或代表性的群体中注册参与者。诸如思虑监视系统,电子健康记录,国家社区调查,环境曝光数据库,社交媒体和遥感的辅助数据来源将为主要数据的集合提供信息。主要数据源将通过问卷调查,精神和身体健康,收购生物标本和可穿戴健康监测设备的参与者提供的信息。一套生物标志物可以来自生物标记,用于健康评估,包括计算近静压负荷,累积应力的量度。该框架还解决了数据管理和共享,参与者保留和系统治理。观察系统旨在无限期地继续,以确保收集和维护灾后的预期,和灾后的健康数据。它还可以提供一种用于有效的健康观察的模型/载体,其与Covid-19如Covid-19等传染病淫亵性。为了我们的知识,没有全面,令人灾害的健康观察系统,例如当前在此处存在或计划在其他地方的存在。 GOM社区卫生观察系统(CHOS)的重大优势是其纵向队列和随着需求所需的迅速适应能力,并且新技术发展。

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