Climate and Health Workshop
A Vision for a Workshop on Climate Change and Human Health to Assess the Climate Information Gap
The public health community realizes that weather and climate have an impact on human health in numerous ways, and that climate change has the potential to create major challenges. The climate community has a large amount of data and understanding concerning past and future climates. Current activities linking climate and health commonly demonstrate that the creation of useful knowledge requires a closer collaboration between the two communities. This must be fostered through cooperation at all stages in the information generation process, from problem definition to results dissemination. The September 22-24, 2009 workshop on “Climate Change and Human Health: Assessing the Climate Information Gap” is designed to bring together a small number of experts from both the climate and health communities, representing various stages of information generation and utilization, to explore in depth those areas where cooperation is possible and where it is likely to be most fruitful. The anticipated output is a realistic action plan for future work, including specific recommendations for projects and proposals where collaboration can lead to near-term gains in understanding and application to the public well-being.
Climate change is the biggest threat to human health in the 21st century (Costello et al., 2009). The complexity of the climate change-human health problem is outlined in the schematic in Figure 1. In broad terms, human health can be thought of as existing at the intersection of the natural environment and the human environment (Comrie, 2007). Thus, the state of human health for a given population depends on the complex interplay between human behavior (particularly with regard to decision-making), vulnerability, exposure, and the physical environment. Climate change has a synergistic effect on both human behavior and the physical environment, and is therefore tied to human health. The ultimate success of adaptation and mitigation strategies in response to climate change and human health will depend on the depth of understanding of the mechanistic links between climate change and the complex components of human health.
In the past few years, members of the public health community have taken on a number of initiatives aimed at improving our understanding of the links between climate change and human health. These include the expansion of health databases, improvements in epidemiological modeling, and the development of public health surveillance networks. One of the next steps is to determine the most practical applications of climate data to aid in improving coordination and collaboration among climate and health specialists. This involves not just an assessment of what data are currently available, but what specialized climate resources, datasets, products, and services can be implemented or developed to better address issues related to climate change and human health. Additionally, improving coordination among climate and health specialists will require finding a systematic way of organizing and disseminating information, resources, and expertise.
The human health sector encompasses a wide variety of agencies and organizations. These groups represent both front-end (e.g., surveillance, research) and back-end (e.g., administration, funding) interests in public health. Determining the proper mitigation and adaptation strategies involves integration of climate data, information, and expertise within all aspects of the human health sector. The primary goal of this workshop is to survey the specialized needs for climate information of many of the major groups involved in various aspects of human health. To facilitate this, workshop sessions will be divided into panels representing various agencies, organizations, and academic fields with interests in climate change and human health. These panels include topics related to: 1) climate products; 2) federal health; 3) inputs for health sector research; 4) inputs for other organizations; and 5) climate-health research results. A list of groups and organizations represented at the workshop is found in a companion document. These preliminary materials are meant to serve as a starting point for panel discussions on current and future needs of climate data within these groups to address human health problems.
Using Weather and Climate Information to Address Human Health and Disease
Based on a review of some of the more recent public health literature, we identified the following as the primary themes and interests in the health community with regard to climate change:
- Modeling of the ecological and dynamical aspects of disease; separating causation from correlation to understand the mechanisms and processes that drive disease (e.g., detection and attribution)
- Dynamic modeling, simulation, and forecasting of disease incidence under various climate change scenarios
- Development and improvement of disease/health early warning systems
The most frequently used markers of human health are mortality and morbidity counts for various diseases and health conditions. In many epidemiological studies, this information serves as the dependent variable for statistical modeling to determine how well human health correlates with climate, which serves as the independent variable or series of independent variables (e.g., rainfall, temperature). To maximize robustness and statistical rigor, non-climatic confounders, such as population demographics, are typically incorporated into the model in a stepwise fashion. While these types of models can provide insight into the relative role of climate on human health, they are inadequate for relating climate to the internal dynamics of disease ecology. This is especially true for diseases with significant epidemiological complexity, such as those which require a biological vector to transport pathogens from one susceptible host to another (e.g., West Nile Virus). While some statistical models have been successful in predicting disease epidemics in vulnerable populations (e.g., Malaria outbreaks in Botswana, Thomson et al., 2005), other models fail to capture the full range of – and sometimes contradictory – conditions and circumstances that may lead to a disease outbreak (e.g., both drought and heavy rainfall contributing to water-borne disease in the southwest U.S., Patz et al., 2005). It is believed that a more complete understanding of the role of climate in disease ecology and dynamics may help explain a greater amount of the variability observed in mortality and morbidity.
The role of climate in disease ecology and dynamics may be illustrated in a variety of ways and with varying levels of complexity. The most complete models include environmental, social, economic, and health system conditions and the direct and indirect effects they have on human health (e.g., Figure 8.1 of the Fourth Assessment Report of the IPCC). While we recognize the complexity of the climate change-human health problem, the full scope of these conditions is beyond the immediate focus of this workshop. As a means of emphasizing the climate component of human health, we adopt a diagrammatical construct from the field of Epidemiology – the Triangle of Disease (Figure 2; Timmerick, 2002). The vertices of the triangle represent the major components of disease ecology while the arms of the triangle represent the dynamic processes, conditions, and pathways that facilitate disease from the perspective of climate and climate change effects. It is important to note that the exact components and pathways of the triangle often vary depending on its use or the nature of the health condition being studied. The example in Figure 2 illustrates the disease ecology for vector-borne disease. Using this construct, the influence of climate on the specific components of disease ecology can be explored:
- Climate <--> Pathogen: How will climate change affect the reproduction and survival of the disease pathogen in the environment?
- Climate <--> Vector: How will climate change affect the reproduction (density) and survival (longevity) of the disease vector in the environment? How will climate change affect the behavior and migration patterns of the disease vector?
- Climate <--> Host: How will climate change affect the susceptibility (immunity) and vulnerability of the host?
For infectious diseases, vectors and pathogens are vital components of their ecology. For other types of health conditions, such as respiratory ailments and trauma associated with hazardous weather events, the primary epidemiological component is the susceptibility or vulnerability of the individual or population. Though subtle, there are important distinctions between susceptibility and vulnerability in the context of human health (Balbus and Malina, 2009). Susceptibility, or sensitivity, is defined as the biological responsiveness of an individual to a given exposure (e.g., does the host lack the biological resistance to fight off an infectious agent?). This relates to the physiological condition of the host. Vulnerability involves both risk and protective factors that ultimately determine whether a population or individual will experience an adverse health outcome (e.g., are they at risk for injury or death based on location, timing, and various behavioral patterns and decisions?). Morbidity and mortality related to temperature extremes (heat waves and cold spells) is likely contingent upon both circumstantial and physiological conditions.
Referring back to the Triangle of Disease example in Figure 2 (vector-borne), the arms of the triangle, which represent the complex processes and pathways of disease ecology, are what maintain the cycles of disease. By “breaking” one or more of the arms, the cycle may stop and the burden of disease eliminated (Timmerick, 2002). Other preventative measures, such as mosquito nets and vaccinations, may break one or more of the arms, as could environmental actions, such as climate change mitigation. Thus, the influence of climate on the complex processes and pathways of disease ecology (the arms of the triangle) should be explored further:
- Pathogen <--> Vector: How will climate change affect the rate of pathogen replication in the vector? How will climate change affect the competence of the vector to serve as a host of the pathogen?
- Host <--> Vector: How will climate change affect the transmission of disease between vector and host? How will climate change affect the degree of exposure to disease vectors?
Using climate information to address the complexity of disease ecology is a major priority for epidemiological research. Results from this work can then be used to address the second primary theme: dynamic modeling of disease incidence under various climate change scenarios. This will require more sophisticated climate datasets, a deeper level understanding of atmospheric thermodynamics at sufficiently large scales, and closer collaboration with climate and computer modelers. Finally, by combining knowledge gained on climate and disease ecology with more sophisticated models, those at the “front-end” of the public health sector can develop and implement more reliable and timely early warning systems.
Assessing the Current Needs of the Health Community
To gauge the current needs for specialized climate data and information within the health community, a literature review was conducted. Both research-based and review articles were considered, with a focus on articles published within the past five years. For research-based articles, the literature review targeted the following information: topical area, author’s field of study, research questions, climate data, methods, caveats, scale of analysis, major research findings, confidence, and recommendations. For review articles, the focus shifted towards identifying what is currently known, what the major research gaps are, what is needed in terms of capacities, skills, knowledge, and expertise, and in what capacity climate specialists can contribute to addressing issues of human health. Topically, the literature review addressed the following health and disease categories:
- Water-borne and food-borne disease (e.g., water quality, harmful algal blooms)
- Vector-borne and zoonotic disease (e.g., mosquitoes, ticks, rodents)
- Temperature variability (e.g., heat waves, cold spells)
- Airborne and air-related disease (e.g., toxins, particulate matter, allergens, spores)
- Weather hazards and extreme events (e.g., floods, hurricanes, lightning)
Since the focus of this workshop is on assessing the climate information gap, the remainder of this section will provide context for addressing the following questions: What types of climate data, products, and indicators have been used? What types of uncertainties accompany them? What are the major research gaps with regards to climate information? In what capacity can climate specialists contribute to addressing these gaps? For brevity, this information is summarized in a table.
Summary and Workshop Directives
This workshop will provide participants with numerous opportunities to engage in dialogue regarding the current use of climate data in addressing human health and the future needs of specialized climate data within various sectors of human and public health. The anticipated output is a realistic action plan for future work, including specific recommendations for projects and proposals where collaboration can lead to near-term gains in understanding and application to the public well-being. There are many questions that could be asked regarding the current and future uses of climate data; however, in an attempt to facilitate effective and critical dialogue, we offer some specific, targeted questions:
• What is your top priority consideration when you utilize climate data in your research/application?
• What is the greatest difficulty you face when you utilize climate data in your research/application?
• Where do you get your climate data/information?
• What climate information do you currently use and what additional climate information do you need?
• How do you use climate information and is your use mostly restricted to seasonal forecasts?
• Can you utilize short term (one day to a few days) weather outlooks (e.g., daily air mass variables)?
• Can you utilize longer term climate outlooks/forecasts?
• Do your research needs for climate information extend beyond the use of standard historic data (daily/weekly/monthly/seasonal temperature, precipitation, relative humidity, highs and lows, etc.)?
• Do you prefer to use large-scale indicators of climate change (e.g., an ENSO index) or are you more interested in assessing the weather/climate “outcomes” (e.g., heavy rainfall/flooding, heat waves, cold spells, etc.) of changes in large-scale climate?
• How important are geographic scale and spatial resolution in your use of climate information?
• How important are global climate models in your research?
• What type of climate information would be most useful for incorporation in your health model simulations/forecasts/surveillance/monitoring efforts?
• How do you handle/address degrees of uncertainty in both climate and health data in developing predictive models?
Other questions to consider include:
• Have we covered the full scope of problems related to climate change and human health?
• How can we use available climate data and expertise to address on-going studies of detection and attribution with regards to the climate change effects on human health?
• Does the payoff for investing in these problems increase with better, more sophisticated climate information?
• Are there advantages to looking holistically at improving the quality of life rather than narrowly focusing on specific diseases and conditions?
In addition to the questions posed above, we provide the following as possible directives and topics, as well as output products:
• Establishment of a climate-health portal, or “clearinghouse”: This may serve as a repository for climate and health information and literature, as well as provide the services necessary to solve climate-human health problems (e.g., contacts, expertise, consulting). It may also serve to monitor the current research and data needs in the field, as well as inform the health community of newly available data and assess the educational needs of the health community
• Develop climate-health models that can be implemented into the National Climate Impact Indicators program at NCDC. Indicators are important communication tools for monitoring and surveillance (see English et al., 2009).
• Address the application and interpretation of global climate models for health research
• Improve the integration of analytical tools from epidemiology (e.g., surveillance networks) and atmospheric science (e.g., remote sensing)
• Distinguish common climatic thresholds where individuals are at increased health risk (e.g., local threshold temperatures for photochemical smog production, thresholds for mosquito or tick survival, degree days and maximum temperature thresholds for heat waves). By establishing thresholds, the climate community can provide more precise monitoring and recording of data in a format more accessible to the health community.
• Explore the possibility of the creation of climatic products that integrate various thresholds for initiating a health response
• Assess the diversity of people and organizations who require climate-health information and improve educational strategies
• Share and learn from “success stories” (e.g., case studies of malaria forecasting and heat warning systems)
• Distinguish short-term “action items” from long-term “investments”. In other words, compare what we want to do with what we can do.
Balbus, J.M., and C. Malina, 2009: Identifying vulnerable subpopulations for climate change health effects in the United States. Journal of Occupational and Environmental Medicine, 51, 33-37.
Comrie, A., 2007: Climate change and human health. Geography Compass, 1/3, 325-339.
Costello, A., and co-authors, 2009: Managing the health effects of climate change. The Lancet, 373, 1693-1733.
English, P.B, and co-authors, 2009: Environmental health indicators of climate change for the United States: Findings from the State Environmental Health Indicator Collaborative. Environmental Health Perspectives, doi: 10.1289/ehp.0900708 (available at http://dx.doi.org/)
Patz, J.A., D. Campbell-Lendrum, T. Holloway, and J.A. Foley, 2005: Impact of regional climate change on human health. Nature Reviews, 438, 310-317.
Thomson, M.C., S.J. Mason, T. Phindela, and S.J. Connor, 2005: Use of rainfall and sea surface temperature monitoring for malaria early warning in Botswana. American Journal of Tropical Medicine and Hygiene, 73, 214-221. Timmerick,
T.C., 2002: An Introduction to Epidemiology. Boston, MA: Jones and Barlett. 321 p.