Sandifer Paul, Knapp Landon, Lichtveld Maureen, Manley Ruth, Abramson David, Caffey Rex, Cochran David, Collier Tracy, Ebi Kristie, Engel Lawrence, Farrington John, Finucane Melissa, Hale Christine, Halpern David, Harville Emily, Hart Leslie, Hswen Yulin, Kirkpatrick Barbara, McEwen Bruce, Morris Glenn, Orbach Raymond, Palinkas Lawrence, Partyka Melissa, Porter Dwayne, Prather Aric A, Rowles Teresa, Scott Geoffrey, Seeman Teresa, Solo-Gabriele Helena, Svendsen Erik, Tincher Terry, Trtanj Juli, Walker Ann Hayward, Yehuda Rachel, Yip Fuyuen, Yoskowitz David, Singer Burton
Center for Coastal Environmental and Human Health, College of Charleston, Charleston, SC, United States.
School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States.
Front Public Health. 2020 Oct 15;8:578463. doi: 10.3389/fpubh.2020.578463. eCollection 2020.
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.
墨西哥湾（GoM）地区容易遭受各种灾害，包括反复发生的石油泄漏、飓风、洪水、工业事故、有害藻华，以及当前的新冠疫情。墨西哥湾和美国其他地区缺乏足够的基线健康信息，以识别、归因、减轻并促进预防灾害对健康造成的重大影响。要发展评估未来灾害对人类健康产生的不利后果的能力，需要建立一个全面、持续的社区健康观测系统，类似于广泛且成熟的环境观测系统。我们提议建立一个系统，该系统结合六个层次的健康数据领域，首先是三项现有的全国性调查和研究，再加上三项新的嵌套纵向队列研究。后者是该系统独特且最重要的部分，重点关注墨西哥湾五个州的沿海地区。提议为新的队列研究选取具有统计学代表性的参与者样本，并进行分层，以确保城市和农村人口按比例纳入，必要时额外招募，以纳入特别脆弱或代表性不足群体的参与者。诸如症状监测系统、电子健康记录、全国社区调查、环境暴露数据库、社交媒体和遥感等二手数据源将为主要数据的收集提供信息并加以补充。主要数据源将包括参与者通过问卷提供的信息、身心健康的临床测量、生物样本采集以及可穿戴健康监测设备。可以从生物样本中获取一套生物标志物用于健康评估，包括计算应激负荷，这是一种累积压力的测量方法。该框架还涉及数据管理与共享、参与者留存以及系统治理。该观测系统旨在无限期持续运行，以确保收集并保存灾害前、灾害期间和灾害后的基本健康数据。它还可以为与新冠疫情等传染病大流行相关的有效健康观测提供一个模式/载体。据我们所知，目前不存在或其他地方也未计划建立像这里提议的这样一个全面的、以灾害为重点的健康观测系统。墨西哥湾社区健康观测系统（CHOS）的显著优势在于其纵向队列以及能够根据需求和新技术发展迅速适应的能力。
