Despite growing threats from sea level rise and other accelerating climate and environmental change-associated factors, there has been no noticeable diminution in the numbers of people living in coastal areas, and in fact coastal populations may be increasing (1, 2). Depending on region, roughly one-third to one-half of the global population lives on a relatively narrow ribbon of coastal land adjacent to oceans, seas, estuaries, major rivers, and very large lakes (3), and many more people work and recreate there.

Coastal zones and their urban and rural areas are particularly exposed to and affected by numerous climate change factors as a result of their high population densities (in the US, coastal shoreline and watershed counties have 3–4 times the population density as inland counties), frequent high proportion of older adults, and usually low elevation, and they play significant roles in national economies due to tourism, fishing, ports, and other industries (1, 4, 5). Note that here coastal shoreline counties refers to those that are adjacent to the ocean or another large water body while coastal watershed counties lie immediately behind the shoreline counties. Other coastal areas of the world, particularly in Asia and Africa, have or are expected to have large population segments exposed to climate change-associated risks from coastal flooding (6). Eight of the world’s 10 most populous cities, along with many other important urban areas, are coastal (7), and virtually all of these are at risk from climate change. In Europe alone, over 200 million people live in coastal or river-front cities (8).

Living, working in, or visiting coastal areas can affect one’s health, both positively and negatively. White et al. (9) reviewed numerous studies, most from developed countries, that found associations between better self-reported health and coastal residency and even visits to coastal areas, especially for mental health. Whether these associations hold in more resource-constrained areas is poorly known, particularly in the global South and Asia. However a recent study in Indonesia demonstrated that access to blue space for recreation had positive mental health effects (10). Overall, the weight of evidence for a positive effect of coastal exposure on health is substantial (9, 11–13).

At the same time, health-related exposures that may occur as a result of coastal residence or visits also include a variety of health hazards such as harmful algal blooms (HABs) and their toxins, infectious disease organisms (e.g., naturally-occurring Vibrio bacteria and microbes associated with sewage pollution), oil spills, chemicals of known and unknown toxicity in air, water, soil, and seafood, and risks of injury and drowning caused by storms, floods, and rip currents. With sea level rise and extreme weather events, there is increasing evidence of stress-associated psychological and physiological disorders caused by disruption to and/or loss of livelihoods and ways of life, damage to or destruction of housing and treasured places, and disturbance of social and familial networks resulting from coastal disasters (14–18). Some of the health- threatening and health-supporting effects of coastal and ocean environments are the primary foci of Oceans and Human Health (OHH) research programs in the US and EU (19–21).

Millions of people around the world rely on weather forecasts, and to a lesser but growing extent, projections of future climatic conditions. These forecasts are increasingly important as people make decisions about daily life activities, places to live, business, investments, travel, recreation, and protection of life and property. The foundation sources for weather and climate forecasts are environmental observing systems that operate on a continuous basis collecting information on atmospheric, oceanic, weather and climate conditions.

These environmental observing systems, and the computer-based numerical models used to process the resulting data, underpin critical, time-sensitive warnings for tropical cyclones and other significant storms, extreme precipitation events, heatwaves, droughts, other major hazards, and longer-term risks from climate change. In part because of the widespread availability of such warnings, the death toll from weather- and climate-related disasters has decreased markedly over the past several decades, even as the number and severity of such events increased (22).

Unfortunately, similar comprehensive, continuous data collection and analysis systems to monitor human health conditions and enable robust predictions and alerts are not widely available, especially in areas exposed to multiple significant health risks. This lack of baseline health information in the disaster-prone US Gulf of Mexico (GoM) region inspired the development of a framework for a community health observing system (16, 23). The COVID-19 pandemic further exposed the need for more comprehensive health surveillance, particularly in areas with combined human health and environmental vulnerabilities (24–27).

Among recommendations for improving interactions between OHH programs and the public health community, Fleming et al. (28, p. 810) included “design and support implementation of dedicated OHH indicators, data streams, and repositories.” Similarly, the European Marine Board (EMB) (29) in the H2020 Seas Oceans and Public Health in Europe (SOPHIE) Project identified a need to determine what available environmental and health data are likely to be most useful in an OHH context. And, among recommendations for US contributions to the UN Decade of the Ocean, the National Academies of Science, Engineering, and Medicine included an “Oceans of Data” theme. This theme envisions not only the collection of much new data but also the open accessibility of existing data and improvements in their usability for diverse audiences (30).

The purpose of the present paper is to elaborate on the potential to link coastal and ocean environmental observations to periodic and ongoing health assessments for people residing in coastal areas, with a view toward improving their health by better identifying and characterizing health benefits and threats to maximize the former and mitigate the latter. The timeliness of this work, at least in the US, is reflected in the recent workshop report from the US National Academies of Science, Engineering, and Medicine (NASEM) about integrating public and ecosystem health programs to foster resilience and the Biden-Harris Administration’s commitment to a “whole-of-government approach to valuing the connections between human and ecosystem health” (31, pp. 2–3).

A schematic diagram of components of a hypothetical Coastal Environmental and Human Health Observing System is provided in Figure 2. While certainly not all inclusive, this is an exemplar of the kinds of environmental and health information that could be accumulated and linked for human health assessments. In addition to the items listed, information on supporting resources, e.g., health care facilities and services, community food pantries, emergency response, and others also could be included, where possible using interactive geospatial mapping frameworks [for example see (35)]. The proposed elements would go a long way to providing a more comprehensive view of coastal exposures likely to have positive or negative health consequences. The types of information encompassed by each “bubble” are described briefly following Figure 2.

Similar to the proposed GoM health observing system framework, background and comparative data could be provided by national health surveys already described for the US (16) or similar surveys in other countries (e.g., (36–39) and numerous others). These types of studies provide regional-to-national level data on general health characteristics of populations that can be used for comparison with results from more focused studies. While useful for comparative purposes in some contexts, these data sources have a variety of weaknesses, including issues related to their geographic and temporal scales.

Cross-sectional studies generally do not assess the health of the same individuals over time but use statistically based sampling methods to choose different participants each time the study or survey is conducted (e.g., annually). Unfortunately, while cross-sectional studies can identify associations between factors and observed health characteristics, they are not able to determine cause-and-effect relationships. Identification of causation requires knowledge that an exposure or behavior preceded the health outcome, while accounting for other potential driving variables. Modern molecular and statistical tools can improve epidemiologists’ ability to use certain cross-sectional data to infer causation (40), but long-running longitudinal cohort studies are the “gold standard” for linking cause and effect. However, cohort studies are expensive and difficult to establish and maintain. Although cohort studies would be preferred elements of the observing system, even if cohorts are absent, all the information gathered could be used by individuals, families, and communities for their own health-monitoring. Here, individuals and cohorts are shown in the center of the framework schematic, and each of the elements in the surrounding “bubbles” is elaborated by reference number in the following sections.

A cohort (#1 in Figure 2) is a group of people each of whom agree to participate in periodic health assessments over a relatively long period of time or indefinitely. Depending on the objectives for a given cohort study, individual participants may be chosen to represent a defined population or specific characteristics such as gender, ethnicity, behaviors (e.g., smokers vs. non-smokers), or health status.

For the US, the Health Insurance Portability and Accountability Act of 1996 (HIPAA) spells out patients’ rights to privacy and to control access to and use of their health data (41). Based on HIPAA, the concept of “informed consent” is an essential requirement for cohort and individual health studies. It refers to communication between a physician, other health-care professional or researcher and a patient or study participant which results in clear understanding by the patient/participant of what a specific intervention or study would entail. It culminates in written authorization by the patient/participant for their participation and the use of any data and/or samples derived from the individual (42). The informed consent process defines what data and/or biological specimens would be collected, managed, protected, and used. However, while cohort studies are the preferred basis for long-term health monitoring, researchers and health care personnel may experience considerable difficulties in recruiting and retaining sufficient volunteers (43, 44). These and other difficulties must be considered when planning recruitment efforts. One frequently used method to engage with communities and solicit volunteer input to identify health indicators, data sources, and other information is through carefully designed and facilitated workshops and community meetings (16, 45, 46). It is likely that this approach also could be used to identify willing participants. In the absence of cohorts, data can be accumulated for individuals, families, or small communities over whatever time period is possible. The key will be to enroll sufficient numbers of volunteer participants, whether acting as individuals or as members of a cohort, who will continue to provide health data over a period of time to develop an ongoing baseline against which future health data can be compared.

Personally provided information (PPI) (#2) is derived from detailed questionnaires completed by volunteer participants online or digitally on computers, tablets, or phones, or on paper (not preferred unless the paper records can quickly be digitized), and with or without a trained interviewer to assist with any questions. Desired information includes: demographic and socio-economic information, personal health status, personal and family health and trauma history, behavioral factors such as smoking and sleep habits, health care access, medications, housing status, known exposures to toxic or infectious agents, adverse childhood experiences, social connections, marginalization and/or discrimination, and feeling secure or insecure in one’s home and neighborhood. Similar kinds of health questionnaires are utilized in many national health surveys. Completed digital PPI questionnaires provide a wealth of health-related background information that can be stored, managed, shared and analyzed readily (16). For example, the US Centers for Disease Control and Prevention (CDC) has managed such data from the BRFSS and NHANES surverys for decades, and the data have been used in many studies by academic as well as government scientists.

Mental and physical health assessments (#3) are typically carried out in-clinic using a variety of psychological evaluation instruments and measurements of physical factors (e.g., blood pressure, pulse rate, height, weight, body mass index) and information derived from biological samples (e.g., blood, urine, nasal swabs, and saliva) (16). However, in certain situations such as emergencies, pandemics, or in rural areas where clinic visits may be difficult, telemedicine or telehealth approaches can be used for some assessments and the completion of questionnaires. Both telemedicine and telehealth refer to the provision of medical services via electronic means, typically video conferencing between patients and health care providers. Its use and acceptance by health professionals and the public have grown substantially over the last several years, especially during the COVID-19 pandemic (47–50).

In-clinic health assessments may also incorporate measurements of cumulative and harmful psychosocial and physiological stress (i.e., allostatic load) via specially designed psychological questionnaires and physiological biomarkers derived from biological specimens (51). Biological specimens collected would be deposited in a secure biobank for use, with all necessary and appropriate safeguards and standardization of methods (Figure 3).

Mobile health data (#4) are those that can be collected via use of personal smartphone apps and/or wearable health devices that can monitor, record, and in some cases transmit data for parameters such as heart rate and heart rate variability, activity (e.g., walking), sleep, blood pressure, respiration, glucose levels, and others (16). A variety of wearable health devices are already available with many improvements and new devices in the pipeline (52). Mobile devices selected for use in this context should be readily accepted, affordable, willingly used by people, robust in a wide range of environmental conditions, and have dependable and long-lasting power sources.

Mobile phones are the most ubiquitous of mobile devices, and they would likely be the primary target for a coastal health observing system. In the US, ~96% of adults have a cell phone (53). At the global level, ~92% of people have a mobile phone, and 84% of these (6.64 billion) have a smartphone (54). Estimates of the number of health-related apps for smartphones range from ~85,000 to 259,000 (55, 56), with more being developed.

Pairing of smartphones and smartwatches or other devices can make possible continuous monitoring of certain health parameters, along with data on location and the physical environment (temperature, humidity, wind, etc.). Mobile devices also can be adapted to include periodic responses regarding psychological status (57) while experiencing a coastal environment for example or for short self-report surveys, such as reactions in the presence of a HAB event, oil spill, hurricane, etc. (43, 58, 59).

Electronic health records (EHRs) (#5) are digital files maintained for individual patients by health care providers and hospitals and subject to strong privacy protections. An EHR is a continuously running summary of an individual’s health information, as determined via in-person and telehealth visits, prescriptions, questionnaires, etc. and is considered a basic repository of patient data. It is effectively a longitudinal record of an individual’s health information. Data derived for individuals participating in cohort studies can be linked to their EHRs with informed consent of the participant. These data can then be integrated with all the individual’s other health information to allow health-care professionals and/or the individual to develop a more comprehensive assessment of one’s health status and health risks. For example, if HAB exposures and associated illness could be better documented in EHRs, they could be linked to other health data over an individual’s life course and thus allow for monitoring of long long-term health effects of such exposures, which are poorly known at present (60). This could be particularly important for children and other vulnerable populations. Some organizations have developed EHR sharing programs, with consent of the participating individuals (61, 62). Development of a secure sharing platform for EHRs would be an important step for cohort studies and for communities interested in undertaking their own community-wide health monitoring effort (Figure 3).

Syndromic Surveillance (SyS) (#6) is a public health early warning system in US states where digital health information about certain diseases can be gathered rapidly, usually from hospital or other emergency departments, and used for early detection of disease outbreaks. These are commonly used to identify and track outbreaks of infectious diseases such as influenza (63) as well as other hazards (64, 65). However, they are lacking in some important respects, including reporting of mental health issues (16).

From a coastal perspective, SyS has been used to identify Ciguatera poisoning outbreaks caused by harmful algae in Florida (66) and for assessing other HAB-associated illnesses across the US (60). Lavery et al. (60) highlighted the potential value of SyS and EHRs for improved documentation of HAB illnesses. Similarly, more robust SyS linked to EHRs could be used to identify Vibrio- and pollution-associated illnesses or other kinds of exposures in coastal areas.

Vulnerability (#7) refers to factors that increase susceptibility of individuals and communities to adverse effects from stressors and exposures (67–69). Basically, vulnerable population segments, groups, or individuals are those who have a higher risk of or susceptibility to injury, illness, death, or loss than the average for the population as whole. Such higher risk may arise from demographic and related characteristics such as age (the very young and the older adult/adults), gender (female), pregnancy, minority race or ethnicity, lower socio-economic and/or educational status, poverty, deprivation, being a refugee, sexual identity and orientation, physical or mental impairment, presence of chronic disease, being institutionalized, incarcerated, or marginalized by language or other factors. Vulnerability also may be defined in terms of proximity to a hazard (e.g., being in the path of a hurricane, tornado, or tsunami or living near highly polluted areas, dangerous industrial sites, or major transportation arteries with their associated pollution, or living or recreating near a large HAB). Here, vulnerability includes those who are at risk due to personal and socio-economic characteristics and/or hazard proximity.

Resiliency is defined in numerous ways, so much so that eventually dissimilar fields may even describe it differently (70). It is probably most often used in reference to the ability of a person or community to resist/absorb stressor impacts and recover rapidly (14). In an attempt to reconcile terms such as adaptability, sustainability, resilience and others in relation to systems facing threats, Galaitsi et al. (71, p. 7) offered the following similar definition: resiliency is the “capacity to recover critical functions and adapt following a disruptive event.” And in the context of social-ecological systems, Reyers et al. (72, p. 269) considered resilience as “the ability of people, communities, societies, or cultures to live and develop with changes and with ever-changing environments. It is about cultivating the capacity to continue to develop in the face of change, incremental and abrupt, expected and surprising.” Relative vulnerability and resiliency can be assessed for both individuals and communities and the information included in EHRs and other health records.

As used here, community data (#8) refers to detailed information about a given community or group of communities, including socio-economic and demographic characteristics, population conditions and health status, resilience, availability and condition of housing, and numerous others. Examples of robust sources of community data in the US are the ACS (73), the General Social Survey (74), and county health data (75). Summers et al. (76) developed a human wellbeing index for the US based on social, economic, and environmental data from secondary sources. Like vulnerability information, these data provide context and help identity factors that may predispose a given individual or group to certain health conditions, positive or negative. Relative indices of resilience to acute weather events at county and regional levels are also available (77, 78). In addition to these secondary sources, community data also encompass local, traditional, and indigenous knowledge brought forth by community members about their environment, health, and interconnections between them. The observing system should include mechanisms for collection of such information and its integration with geospatial and other data derived via scientific approaches (79–82).

Social media (#9) typically refers to websites and applications that enable users to create and share content or participate in social networking (Oxford Language). Common examples include Facebook, Instagram, Twitter, TikTok, WhatsApp, and YouTube. Social media can be used to assess mental and physical health and pollution issues in communities or other geographic areas at specific times, depending on the extent to which the social media data reflects characteristics of a given community (83–85), and to distribute helpful information. However, social media also can be used to marginalize or demonize certain ethnic groups (86) and to spread harmful disinformation, such as occurred during the COVID-19 pandemic (23). In addition, social media can help people establish and maintain social and family networks and friendships, which can exert positive influences on health. For example, people with higher levels of social contact and social capital tend to feel healthier, mentally and physically (87), although social capital may not be protective of physical health in all cases (88). Because social media can be both helpful and harmful, care must be taken in its use for observing and reporting health information. Importantly, social media users may not include proportionate representation of particularly vulnerable populations, such as older adults.

Weather warnings (#10) are used here as an abbreviation to encompass atmospheric, meteorological, oceanographic, and climate observations and warnings. Common examples include weather forecasts, extreme heat, cold and humidity alerts and warnings, and forecasts of tropical cyclones and other major storms, floods, tornados, tsunamis, droughts, and high wave and rip current warnings.

Weather forecasts and other weather and climate-related services are provided by a variety of organizations, including at international [e.g., (89–91)] and national levels [e.g., (92, 93)], and by a plethora of private sector companies, with some tailored to very specific audiences (e.g., farmers, beachgoers, surfers). In the US, Americans consulted weather forecasts approximately 300 billion times per year, illustrating their high value to the public (94).

Beach and water warnings (#11) are advisories and forecasts such as for the presence of HABs and their toxins, sewage pollution, other contaminants, and high concentrations of Vibrio bacteria in recreational waters and drinking water supplies. Multiple modeling tools are available for forecasting HABs and Vibrios and the accuracy and coverage of these systems are increasing rapidly (95–98). In addition, the US CDC supports the One Health Harmful Algal Bloom System (OHHABS), a voluntary reporting system for states and territories to contribute information on incidences of HABs and associated illnesses in humans and animals (99, 100). While this system typically does not provide data in real or near-real time, it does enable discovery of major HAB events and associated health impacts in a variety of states. It is worth noting, however, that the majority of HAB reports in the system come from freshwater.

The “How’s the Beach” app (101) is one example of internet-based tools that provide beachgoers with information to judge whether a particular day might be a good day to go to a specific beach in terms of conditions that might affect health. This product pulls together weather information (temperature, UV conditions), beach conditions (tides, surf, waves, rip currents), likelihood of exposure to E. coli or other pollution-associated disease organisms or HABs, and other relevant data and makes it available in near-real time to consumers via their mobile phones, tablets, or computers.

Exposure (#12) is a catch-all for detection of potential contacts with noxious, toxic, and infectious agents in air (e.g., aerosolized HAB toxins, fine particulate matter) and water (infectious disease organisms, chemical pollution, oil spills, pesticides, herbicides) using direct sampling and remote sensing techniques. Concentrations of the agent(s) of concern and duration of exposure are of particular importance as is the cumulative total exposures (termed the “exposome”) over a lifetime (102).

In addition to exposure data collected locally in coastal areas by environmental agencies, researchers, and citizan scientists, there are numerous other sources of data on water- and airborne exposures [e.g., (103–106)]. In the US, the National Institute of Environmental Health Sciences (NIEHS) maintains the Human Health Exposure Analysis Resource (107) that provides detailed resources for researchers to use in assessing pollution exposure impacts on health. Other important exposure resources are poison control centers located across the US and in other countries (108).

Seafood advisories (#13) are assessments of the likely healthful or harmful status of specific seafood in terms of nutritional quality (e.g., promoting cardiovascular health and safe pregnancies) and/or contaminant burden (heavy metals, HAB toxins and chemical pollutants, Vibrios and other infectious microbes) that carry increased risks for a variety of adverse health outcomes, including cancer and birth defects. These notices are often promulgated by health agencies with notices in public media and may cover species harvested in recreational, subsistence, and commercial fisheries and distributed via informal networks or commercial markets (109, 110).

Exposure to “green,” “blue,” and biodiverse landscapes (#14) is widely recognized to have health-promoting effects, especially for mental health (e.g., alleviation of anxiety and depression). Green spaces include forests, parks, tree-lined streets, and other areas relatively rich in trees and natural biota in urban as well as rural areas. “Blue” spaces refer to large water features, especially coastal areas but also large lakes and rivers. While mechanisms of action for health-promoting effects of green and blue spaces are largely unknown, recent studies point to positive effects on immune system function (111), improved mental health and decreased exposure to pollution (112), and increased physical activity and restoration (referring to “recovery from depleted attentional capacity or stress”) (9, 113). In addition, while adverse childhood experiences are known to negatively affect health later in life (114), blue space exposure in childhood has been shown to positively influence adult subjective wellbeing (115). Reduction in COVID-related mortality and racial disparities in COVID infection rates also were reported in association with green spaces (116–118).

A variety of remote sensing data can be used to assess greenness, including the Normalized Difference Vegetative Index (NDVI), Leaf Area Index (LAI), and Land Use- Land Cover (LULC) data. Labib et al. (119) used all these to develop a composite Greenspace Availability Exposure Index (GAVI). Amounts and proximity of blue spaces can also be determined with aerial and satellite imagery. Zaldo-Aubanell et al. (120) make a strong case for linking environmental information such as LULC data with health information maintained in individual EHRs.

Monitoring of sentinel organisms (#15) such as filter-feeding mollusks that often capture pathogens, chemical contaminants, and HAB toxins and marine mammals that breathe the air just above the surface of the water and feed on the same or similar species that humans consume, can provide excellent indicators of the condition of marine and coastal environments and of potential health risks for humans (121, 122). Created in 1986, NOAA’s Mussel Watch program is the longest continuously running program using molluscan shellfish to monitor chemical contaminants in US and Great Lakes coastal waters (123). The program spread internationally (124) and has provided a rich and consistent database on chemical pollution in coastal waters in numerous countries for nearly five decades. Similarly, marine mammal health studies provide valuable insight into effects of chemical contaminants including oil and HAB toxins on organs and life processes as well as on distributions of pathogenic organisms in response to climate change. Observed health effects may indicate how similar exposures could affect humans (125). As one example, reports of illnesses and deaths among livestock, dogs, and fish exposed to HABs can provide useful information about human health risks if shared with public health and clinical practitioners (126). Such reports can be found in the OHHABS system previously mentioned and should be included in health and environmental surveillance systems (126).

Missing from the coastal health observing system schematic (Figure 2) is a means for assimilating, linking, integrating, and maintaining data and associated metadata from all the information streams. While a secure data management system will be an essential element of a coastal health observing system, design of a data warehouse and management system is beyond the scope of the present paper. However, one option would be to establish a secure data repository similar to that employed in the NIH All of Us national health study (127) and proposed for the GoM Community Health Observing System (Figure 3) (16). Such a third-party repository could provide data quality control, storage and archiving, integration, and controlled access. The repository would limit access to protected data only to participants and pre-qualified researchers and health care professionals under strict use protocols. Individual participants could access their specific health data as well as the publicly available environmental data to gain a better understanding of their various exposures and potential associated positive or adverse health effects.

The data repository should also include a “biobank,” that is, protected frozen storage for biological specimens collected from volunteer participants. Utilization of specimens for analysis for biomarkers and other purposes would be limited to authorized persons only, and all privacy requirements for use of the biological materials and all data derived from them would be followed. Some other models for secure systems for storing and managing health information and its use include the UK Biobank (128), My Clinical Outcomes (129), the Opal Project (130), the University College of London’s Data Safe Haven (131), and Data Shield (132).

Because the Coastal Environmental and Health Observing System is just a proposal at this time and lacks a confirmed home and implementation strategy for start-up and operations, governance and decision-making responsibilities can be described only in general terms. Detailed design and implementation of the system will likely require commitment of at least one lead sponsoring agency or entity, perhaps accompanied by establishment of a consortium of several institutional partners to serve as principal funders and as an oversight or managing body. However structured, the managing body would need to take responsibility for final system design and implementation, financial administration, and data management including establishment of data and metadata standards, data sharing agreements, data access and use, as illustrated in Figure 3. It would also be responsible for creating and sustaining scientific and community advisory committees and arranging for necessary periodic reviews and audits.

Coastal areas remain attractive places to live, work, and recreate, even in the face of growing threats from climate and other environmental change. Because so many people are attracted to coasts worldwide, at any given time a significant portion of the human population is exposed to positive and negative health effects associated with coastal location.

More older people are moving to coastal locations. Climate Central (133) reported that the numbers of people >65 years old living in US coastal areas grew by 89% between 1970 and 2010, reflecting at least in part the attraction of coastal areas for retirees. Further, the EPA (134) estimated that, in the US, those 65 and older had a 9% higher chance of living in areas of potential high impact from coastal flooding. This trend of a “graying” coastline is not limited to the US, but also reported in the UK (135) and Mediterranean Europe (136), and it is probably occurring elsewhere. Older people may be able to benefit from coastal health-promoting factors while also likely being more vulnerable to coastal health risks.

Reported health benefits of coastal living are beginning to be explored systematically (137, 138), although mechanisms of action remain poorly understood. Similarly, while many health risks that may accompany coastal residence are well known, their contributions to morbidity and mortality are not, nor are most people even aware of their exposures to potential health threats when at or near the coast.

As examples, human illnesses caused by HABs and infectious Vibrios, either via consumption of contaminated food or contact with water or aerosols containing toxins or microbes, have been recognized for decades (139, 140). Such negative effects appear to be increasing in response to climate change-associated rising water temperatures, salinity changes in coastal areas, and interactions of microbes and HABs with nutrients, heavy metals, antibiotics, and microplastics (1, 20, 141). Yet these adverse health outcomes remain under-reported, frequently misdiagnosed, and poorly recognized by medical and public health professionals, as well as by coastal managers, residents, and visitors. For instance, HAB-related illnesses are believed to be at least 10-fold more prevalent than reported (142), while ciguatera poisonings in Florida are estimated to be 55–87 times higher (143). Vibrio-associated illnesses are also severely underreported, and in one instance V. vulnificus infections were estimated to be 142 times higher than reported (20).

Raising awareness among medical professionals and the public will help in this regard as will improvements in diagnoses and reporting systems and in ecological forecasts that provide early warnings of likely problems (19, 28, 139). Among the most important needs are collection and wide dissemination of information about the occurrence of specific risk factors (e.g., microbial and chemical pollution, HABs, Vibrios) and potential human exposures to them. A coastal health observing framework such as proposed here could help fill this gap by bringing attention to environmental and other conditions that can significantly affect people’s health and wellbeing.

These recommendations are solely those of the author and do not reflect any discussions with or agreement by any other persons or entities.

Recommendations 1 and 2 are for action at a high governmental level and would likely require some time for results to present. Recommendation 3 could be accomplished more quickly if there is interest in the agencies identified. Recommendation 4 is for a grassroots effort to bring attention to the need and to develop support in the US Congress and Federal and State agencies over time.

Recommendation 1: The Secretary of the US Department of Health and Human Services (HHS) or other Cabinet level leader designated by the President, could convene directors of HHS agencies (e.g., the NIH and CDC), and request participation of administrators of other Federal agencies with interests in the area including the Department of Defense (DoD), EPA, NOAA, and the National Science Foundation (NSF), plus representatives of State, County, and local public health and environmental agencies to develop and implement a national strategy for integrating available health and environmental condition data and collecting additional data as may be required. Such effort should include standardization of data collection, management and sharing; data quality improvement; engagement of diverse communities and interested collaborators including philanthropic organizations and underserved communities; and funding options. As a first step, the assembled agencies or a subset could commission a consensus study to be conducted via the National Academies of Science, Engineering, and Medicine. Results of the consensus study could be used as guidance for initiating the observing system [Note this recommendation is somewhat similar to Recommendation 3-1 in (82)].

Recommendation 2: The European Marine Board (EMB), could address similar issues as those noted above, with a goal to develop a pan-Europe coastal environmental and health observing strategy. The EMB has been a strong supporter of OHH research since at least 2013 (173), and this might be a logical next step. Similar actions could be taken wherever else in the world there may be governmental interest.

Recommendation 3: The Administrator of NOAA, working with Directors/Administrators of EPA, NIH, and NSF, could direct senior staff to explore options to incorporate health and health-relevant environmental data into the Integrated Ocean Observing System as suggested here. As first steps, one or more pilot projects could be designed and implemented by interested IOOS Regional Associations.

Recommendation 4: Individual scientists, groups of scientists, or scientific organizations could organize community input through development and dissemination of a comprehensive “white paper” or publication that could serve as a vehicle for engaging with governmental funding agencies, legislative bodies, non-governmental organizations, and the private sector. This kind of process can provide significant impetus for initiating program development.

Notwithstanding the discouraging array of barriers and impediments to integrating environmental and human health data via an observing system, we need to begin somewhere. Coastal areas seem to be a good starting place since they are especially vulnerable to climate change, have high population levels, significant environmental observation resources, particularly for some environmental factors that directly affect human health (e.g., water pollution, HABs, major storms, rip currents), and expose people to both health promoting and health threatening factors. The coastal human health observing system described here would link a variety of coastal environmental observations and health data for individuals, communities, and where possible cohorts. Over time, establishment of a network of such studies focused on residents of coastal areas could provide powerful tools for understanding the health effects of coastal living, good and bad, and lead to better health protections and enhanced wellbeing. While only aspirational at this time, an interconnected system of coastal human health observatories could provide significant benefits to coastal residents, including those in environmental justice and other disadvantaged communities. The basic elements for a coastal health observing system exist but need to be connected, integrated, supported, and implemented. Significant progress could be made in incremental fashion by adding a few health observations to some well-established and environmental observing systems and by augmenting existing health monitoring programs with some environmental observations.

Publicly available datasets were analyzed in this study. No new data were collected and no existing data were analyzed. The paper is a thought study based on literature and experience.

The author confirms being the sole contributor of this work and has approved it for publication.

Partial support for this study was provided by the National Institute of Environmental Health Sciences (NIEHS) under award number P01ES028942 to the University of South Carolina and a sub-award to the College of Charleston.

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.