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

被引：17

作者：

Sandifer, Paul ^{[1
]}

Knapp, Landon ^{[1
]}

Lichtveld, Maureen ^{[2
]}

Manley, Ruth ^{[3
]}

Abramson, David ^{[4
]}

Caffey, Rex ^{[5
]}

Cochran, David ^{[6
]}

Collier, Tracy ^{[7
]}

Ebi, Kristie ^{[8
]}

Engel, Lawrence ^{[9
]}

Farrington, John ^{[10
]}

Finucane, Melissa ^{[11
]}

Hale, Christine ^{[12
]}

Halpern, David ^{[13
]}

Harville, Emily ^{[2
]}

Hart, Leslie ^{[14
]}

Hswen, Yulin ^{[15
,16
]}

Kirkpatrick, Barbara ^{[17
]}

McEwen, Bruce ^{[18
]}

Morris, Glenn ^{[19
]}

Orbach, Raymond ^{[20
]}

Palinkas, Lawrence ^{[21
]}

Partyka, Melissa ^{[22
]}

Porter, Dwayne ^{[23
]}

Prather, Aric A. ^{[24
]}

Rowles, Teresa ^{[25
]}

Scott, Geoffrey ^{[23
]}

Seeman, Teresa ^{[26
]}

Solo-Gabriele, Helena ^{[27
]}

Svendsen, Erik ^{[28
]}

Tincher, Terry ^{[28
]}

Trtanj, Juli ^{[29
]}

Walker, Ann Hayward ^{[30
]}

Yehuda, Rachel ^{[31
]}

Yip, Fuyuen ^{[28
]}

Yoskowitz, David ^{[12
]}

Singer, Burton ^{[19
]}

机构：

[1] Coll Charleston, Ctr Coastal Environm & Human Hlth, Charleston, SC 29401 USA

[2] Tulane Univ, Sch Publ Hlth & Trop Med, New Orleans, LA 70118 USA

[3] Coll Charleston, Masters Program Environm & Sustainabil Studies, Charleston, SC 29401 USA

[4] NYU, Sch Global Publ Hlth, New York, NY USA

[5] Louisiana State Univ, Dept Agr Econ & Agribusiness, Baton Rouge, LA 70803 USA

[6] Univ Southern Mississippi, Sch Biol Environm & Earth Sci, Hattiesburg, MS 39406 USA

[7] Western Washington Univ, Huxley Coll Environm, Bellingham, WA 98225 USA

[8] Univ Washington, Dept Global Hlth, Seattle, WA 98195 USA

[9] Univ N Carolina, Gillings Sch Global Publ Hlth, Chapel Hill, NC 27515 USA

[10] Woods Hole Oceanog Inst, Woods Hole, MA 02543 USA

[11] Rand Corp, Pittsburgh, PA USA

[12] Texas A&M Univ Corpus Christi, Harte Res Inst, Corpus Christi, TX USA

[13] Scripps Inst Oceanog, La Jolla, CA USA

[14] Coll Charleston, Dept Hlth & Human Performance, Charleston, SC 29401 USA

[15] Harvard Med Sch, Computat Epidemiol Lab, Boston, MA 02115 USA

[16] Univ Calif San Francisco, Dept Epidemiol & Biostat, Bakar Computat Hlth Sci Inst, San Francisco, CA USA

[17] Texas A&M Univ, Gulf Mexico Coastal Ocean Observing Syst, College Stn, TX USA

[18] Rockefeller Univ, Lab Neuroendocrinol, 1230 York Ave, New York, NY 10021 USA

[19] Univ Florida, Emerging Pathogens Inst, Gainesville, FL USA

[20] Univ Texas Austin, Dept Mech Engn, Austin, TX 78712 USA

[21] Univ Southern Calif, Suzanne Dworak Peck Sch Social Work, Los Angeles, CA 90007 USA

[22] Mississippi Alabama Sea Grant Consortium, Mobile, AL USA

[23] Univ South Carolina, Arnold Sch Publ Hlth, Columbia, SC 29208 USA

[24] Univ Calif San Francisco, Dept Psychiat & Behav Sci, San Francisco, CA 94143 USA

[25] NOAA, Natl Marine Fisheries Serv, Silver Spring, MD USA

[26] Univ Calif Los Angeles, David Geffen Sch Med, Los Angeles, CA 90095 USA

[27] Univ Miami, Dept Civil Architectural & Environm Engn, Coral Gables, FL 33124 USA

[28] Ctr Dis Control, Div Environm Hlth Sci & Practice, Natl Ctr Environm Hlth, Atlanta, GA USA

[29] NOAA, Off Ocean & Atmospher Res, Silver Spring, MD USA

[30] Sea Consulting Grp, Cape Charles, VA USA

[31] Icahn Sch Med Mt Sinai, Bronx, NY USA

来源：

FRONTIERS IN PUBLIC HEALTH | 2020年 / 8卷

关键词：

health observing system; disasters; Gulf of Mexico; cohort studies; stress; COVID-19; allostatic load; health surveillance; OIL-SPILL; CLIMATE-CHANGE; SYNDROMIC SURVEILLANCE; NATURAL DISASTERS; EXXON-VALDEZ; STRESS; RECOVERY; COHORT; IMPACT; INVESTIGATE;

D O I：

10.3389/fpubh.2020.578463

中图分类号：

R1 [预防医学、卫生学];

学科分类号：

1004 ; 120402 ;

摘要：

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.

引用

页数：18

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