EPID: Focus on Surveillance
Integrating Climate Information into Surveillance Systems for Infectious Diseases:
New Opportunities for Improved Public Health Outcomes in a Changing Climate**
Madeleine C. Thomson, Ph.D.;
Gilma C. Mantilla, M.D.
International Research Institute for Climate and Society, Columbia University
Many infectious diseases are climate-sensitive: climate acting as an important driver of spatial and seasonal patterns, year-to-year variations (including epidemics), and longer-term trends. Although climate is only one of the many drivers of infectious diseases, public health policy makers and practitioners are increasingly concerned about the potential impact of climate change on the health of populations. Noticeable changes in average climate are already being observed (and are therefore likely to affect the spatial distribution of some diseases, such as malaria). It is also expected that extreme events that can have devastating socioeconomic, environmental, and health impacts (e.g., floods, droughts, and heat waves) are more likely to occur.
The global health system is in a period of rapid change, with global health surveillance receiving increasing recognition as a primary source of protection from newly emerging and re-emerging threats: infectious diseases, new cycles of pandemics, bioterrorism, as well as climate change. Here we propose the incorporation of climate information into routine epidemiological surveillance systems for climate-sensitive diseases. To achieve this requires new and innovative mechanisms for strengthening observations, data management and sharing, development of relevant climate services, intersectoral collaboration, training and capacity building; all within an enabling policy environment. Our premise is that improved management of health risks associated with climate variability (such as the heat early warning systems recently established in Europe and North America) increases adaptive capacity of the public health sector to longer-term climate change. Specifically, we propose that the epidemiological surveillance community: (1) Establish collaborative partnerships with climate/environmental research and service communities to overcome policy and institutional barriers and identify opportunities for the effective use of climate information in health policy and decision-making; (2) Build the capacity of health professionals to understand, use and demand appropriate climate information/environmental information through creation of nested training opportunities in epidemiology and related professional training; (3) Support the research and development of appropriate evidence-based climate/environment products and services for use in health policy and decision-making; and (4) Support national and global investments in routine observation of climate, environmental and health phenomena pertinent to decision-making for climate-sensitive diseases.
We live in an increasingly interconnected world. The 2003 SARS outbreak demonstrated the economic impact of not having an effective global public health surveillance system in place. The rapidly increasing movement of people, pathogens, vectors, food, goods, and capital, much of it driven by cross-border and intercontinental decision-making that characterizes globalization — together with global environmental and demographic trends — has changed the global public health landscape. Consequently, new regulations (e.g., the International Health Regulations) and new public health actors emerged. For example, in 2005, China rapidly began to expand its surveillance and response capacity through its Field Epidemiology Training Program (FETP), while Brazil, Argentina, and Eritrea chose to use World Bank loans to develop national surveillance capacity. In addition, support for the Millennium Development Goals (MDGs) and related international health priorities focused on the poor, have meant increasing donor support for infectious disease surveillance in endemic countries. For example, in the last five years the U.S. President’s Malaria Initiative spent $1.25 billion (U.S.) on malaria control in 15 African countries and the U.S. Agency for International Development (USAID) redesigned its surveillance strategy to focus on the use of data to improve public health interventions.
Preoccupied by these new concerns, some in the global health surveillance community have seen the rise of climate change on the political agenda as a detractor from achieving well-defined health objectives. Only recently has the community accepted the importance of climate change as an additional, potentially overwhelming, contributor to the global health burden. In 2008, the World Health Assembly recognized climate change as one of the defining challenges of the 21st century, and protecting health from its impacts is a priority for the public health community.
Climate-related health impacts are especially pronounced in poor communities, primarily in developing countries, where vulnerable people lack the basic infrastructure to cope with climate variability and change. In these countries, the livelihoods of millions of people are heavily dependent on rain-fed agriculture and seasonal water resources. These communities also bear the greatest burden of infectious diseases and disasters and have the least access to public health services. The devastation caused by Hurricane Katrina demonstrates that poor communities in wealthy countries are also particularly vulnerable to climate-related disasters. We observe that the voices of those most likely to suffer the ill health effects of climate change are rarely heard in international negotiations; the health consequences of climate variability and change are thus inextricably linked to global development choices, including issues of equity.
Scientific opportunities and challenges
Current approaches to incorporating climate into health planning and surveillance within climate change adaptation strategies are limited. Where found, they are often based on climate change scenarios developed from global climate models which focus on the long-term, commonly extending out to 2080 and beyond. We contend that, used alone, they are not appropriate for national adaptation policies for infectious disease prevention and control, as policy time horizons for the latter are much shorter (see Figure 1). We are concerned that a scientific area in its infancy is moving into public policy before appropriate tools, institutional arrangements, or best practices have been established. Most significantly, the science is entering public health policy making before public health actors are adequately trained to incorporate the new scientific understanding of climate variability and change into practical public policies and practices.
Climate is one of many drivers (e.g., social, political, economic, environmental, and technological factors) of infectious disease outcomes that is measured outside of the health sector. What makes it unique is the fact that it is measured systematically at a local and global scale using standardized methodologies, and its fundamental characteristics mean that it is ideally suited as an additional source of information in climate-sensitive infectious disease surveillance and forecasting. These characteristics include climatology, seasonality, diurnal rhythm, as well as predictability at multiple timescales (weather, season, decadal and climate change).
New opportunities exist for better management of climate-related health risks. These are made available through advances in climate science (e.g., predictability of El Niño events), satellite-based environmental monitoring technologies (e.g., routine information on the state of the environment provided globally, free of charge, from the MODIS satellite sensor), rapidly advancing communication technologies (impacting on data and knowledge sharing), and a new global focus on effective management and elimination/eradication of certain infectious diseases.
To make use of these new opportunities, we propose that the epidemiological surveillance community:
- Establish collaborative partnerships with climate/environment research and service communities to overcome policy and institutional barriers and identify opportunities for the effective use of climate information in health policy and decision-making. Climate and Health working groups have already been established in some countries which connect ministries of health, national meteorological agencies, and other public health partners around the development of climate services for the health sector. Other innovative partnership structures need to be established that are appropriate to individual settings.
- Build the capacity of health professionals to understand, use, and demand appropriate climate information/environmental information through creation of nested training opportunities in epidemiology and related professional training in schools of public health and other appropriate institutions, including incorporation of climate knowledge and information in field epidemiology training programs.
- Support the research and development of appropriate evidence-based climate products and services for use in health policy and decision-making within the context of the Global Framework for Climate Services “to strengthen production, availability, delivery, and application of science-based climate prediction and services.”
- Support national and global investments in routine observation of climate, environmental and health phenomena pertinent to decision-making for climate-sensitive diseases including the Global Climate Observing System (GCOS) and the Health Societal Benefits Area of Group on Observations (GEO) within the Global Environmental Observation System of Systems (GEOSS) framework, with a focus on data access, data management, and data transformation into information and services.
Ghrebreyesus, T.A. et al. (2008). Public health services and public weather services: increasing the usefulness of climate information in the health sector. Bulletin of the World Meteorological Organization. 57:136-39.
Kelly-Hope, L. and Thomson, M.C. (2008). Climate and infectious diseases. In: Seasonal Forecasts, Climatic Change and Human Health (Advances in Global Change Research). Eds M.C. Thomson, R.G Herrera and M. Beniston, Springer, pp. 31-70.
Nsubuga, P. et al., (2006) Public Health Surveillance: A tool for targeting and monitoring interventions. In: Disease Control Priorities in Developing Countries, 2nd edition. Eds Jamison, D.T., et al., (Washington DC): World Bank.
Variability v. long term changes in rainfall in the Sahel: a challenge to decision-makers.
This one graph indicates the challenge of thinking about managing climate sensitive health risks at multiple time scales. The black line represents the long-term trend in rainfall across the Sahel from 1900 to 2009. A significant downward trend is observed. This is the type of long-term trend that might be predictable in climate change models.
The spiked line represents the year-to-year variability in the same region of the Sahel. Clearly some years are much wetter or drier than others. This is the type of short-term variability that might be partially predicted through operational seasonal climate forecasts based on climate models and El Niño related phenomena.
The curved line represents slowly evolving shifts in rainfall across the Sahel over decadal (10-year) time scales. These shifts are considered as part of the natural cycle of climate variability and are particularly pronounced in the Sahel. Thus the 1970s and 1980s were particularly dry and contain the extreme drought years of 1973 and 1984. This is the type of slowly- evolving variability that is currently the focus of intense research. If it were predictable then many opportunities for better climate risk management would emerge.
Health policy and decision makers need to consider the nature of the climate challenge associated with specific health risks and the information available to respond to that challenge. For the control of infectious diseases the decision opportunities are likely to fall entirely within the year-to-year or decadal time frame.
** A policy position paper prepared for presentation at the conference on Emerging and Persistent Infectious Diseases (EPID): Focus on Surveillance convened by the Institute on Science for Global Policy (ISGP) Oct. 17-20, 2010, at Airlie Conference Center, Warrenton, Va.
The following summary is based on notes recorded by the ISGP staff during the not-for-attribution debate of the policy position paper prepared by Drs. Madeleine Thomson and Gilma Mantilla (see above). Dr. Thomson initiated the debate with a 5-minute statement of her views and then actively engaged the conference participants, including other authors, throughout the remainder of the 90-minute period. This Debate Summary represents the ISGP’s best effort to accurately capture the comments offered and questions posed by all participants, as well as those responses made by Dr. Thomson. Given the not-for-attribution format of the debate, the views comprising this summary do not necessarily represent the views of Drs. Thomson and Mantilla, as evidenced by their policy position paper. Rather, it is, and should be read as, an overview of the areas of agreement and disagreement that emerged from all those participating in the critical debate.
- While the relative importance of weather and climate as factors in the development and spread of infectious diseases is still debated, changing climatic conditions must be given consideration as potential drivers of disease. This information should accordingly be included in modeling, predicting, and operational decision-making for the control of infectious diseases.
- A cadre of public health professionals who are equipped with the skills and knowledge to integrate weather/climate into infectious disease surveillance is needed. Education and training on weather/climate should accordingly be integrated into public health studies.
- Improvements in evidence-based research and development of climate products/services are needed to make weather and climate information useful for decisions concerning health and infectious disease control.
- Collaborative partnerships and communication are needed among epidemiology, public health, climate, environment, and policy communities to appropriately integrate weather/climate and infectious disease surveillance data. In particular, the climate community must learn to demonstrate the value of weather and climate data for the surveillance and control of infectious diseases.
Historically, the relative importance of weather/climate in the development and spread of infectious diseases has been vigorously debated. While the relevance of weather and climate to infectious diseases in humans was acknowledged, diverse views were expressed concerning the degree to which both factors should be considered in the analysis of surveillance data, especially relative to other variables. Establishing clearer definitions of environmental factors for the public in general and policy makers specifically was deemed to be an important early step in conveying the value of these factors in modeling, particularly when distinguishing between “weather” and “climate.” Weather and climate are different, but related, phenomena. It was generally recognized that the term “weather” refers to point-sourced data measuring hourly/daily changes in parameters such as temperature and humidity/rain within specified locations, and that “climate” refers to average weather conditions at a particular place over a long period of time. The differences between weather and climate must be effectively communicated to both the public health community and policy makers.
Most public health experts have not acquired the skills required to accurately integrate weather and climate data into their research or policy recommendations, but more routinely rely on anecdotal information for decision-making. This is because course material focused on weather and/or climate is rarely emphasized in degree programs or professional training in public health. This knowledge base will be necessary for the weather/climate fields to adequately inform health issues, including infectious disease control.
The quantity and accuracy of weather/climate data have both increased dramatically during the past two decades. Tremendous investments have been made to develop and deploy methods and technologies for modeling increasingly detailed and precise meteorological data that are used to improve the accuracy and visual presentation of television weather reports and two-to-five-day forecasts. Additionally, computer-processed data are now available to predict conditions that affect air travel (e.g., wind), forecast snowstorm locations and timing, project typhoons in the Indian Ocean and South China Sea, track hurricanes in the Gulf of Mexico through mapping initiatives, and estimate climate changes worldwide months or years into the future. Such computer-processed data have been termed “climate services products.” As a result, the scientific community has a rapidly expanding bank of systematically recorded, temporal weather/climate data that can be incorporated into other studies, including those focused on health issues.
Weather/climate data and public health information, such as that relevant to infectious disease surveillance, are collected and stored in a wide range of formats. These technical issues make it difficult to blend the information obtained from these two fields for the purposes of prediction. Although it is possible to convert these data types into compatible formats, this work can be time-consuming and difficult for those who are not directly familiar with one field or the other. These technical difficulties have become significant barriers to incorporating weather/climate results into the analysis of disease surveillance data.
In wealthy countries, disease transmission is not nearly as dependent on weather/climate as it is in less-wealthy countries. This difference is due, in part, to the issues associated with the quality of building construction, the energy committed to intensive climate controls (e.g., air conditioning), and the resources available from highly industrialized economies. All of these variables reflect the degree of development in a given country.
Thus, while climate data may not be particularly useful in areas such as Europe, the same type of data may play a greater role in poorer, tropical countries where climate-related impacts are especially pronounced on an individual scale (e.g., where substandard housing and inadequate basic infrastructure provide insufficient protection from weather) and on an economic scale (e.g., where livelihoods are heavily dependent on rain-fed agriculture and seasonal water resources). However, the devastation caused by Hurricane Katrina demonstrated that poor communities in wealthy countries are also exceptionally vulnerable to the negative effects of weather events.
It has been recognized that weather variations are among several factors that influence infectious disease transmission and spread. For example, migratory birds carry viral organisms to new locations (e.g., West Nile virus), rainy seasons and standing water enlarge mosquito populations that infect humans (e.g., malaria, Rift Valley fever, dengue fever, yellow fever), and weather-related disasters such as droughts or floods may lead to the appearance and rapid spread of infectious diseases by ruining infrastructure and instigating mass migration (e.g., cholera and measles). Weather variations and extreme weather events, however, do not necessarily cause increases in disease incidence. For example, rainfall surges frequently cause malaria transmission spikes, yet because certain populations maintain a natural immunity to the disease, the incidence of disease does not always increase in proportion to the rate of transmission.
Since weather predictability is only accurate for short time scales (generally 5 to 10 days), its use in predictive models of longer-term phenomena is complicated at best. However, climate predictability does function reasonably well on seasonal scales because it is aligned with sea surface temperatures (e.g., El Niño and La Niña) and therefore, is more useful in predictive modeling including that used for disease surveillance.
Climate can dramatically influence the human food supply, not only through agriculture, but also through aquatic chains. Marine toxins are naturally occurring chemicals that can affect certain seafood. Infectious diseases, such as paralytic shellfish poisoning associated with certain types of seasonal algae blooms in coastal waters, are transmitted to humans when they eat contaminated seafood. These events can cause serious morbidity and mortality in humans.
Scientific opportunities and challenges
It was argued that while weather/climate changes are predictors of infectious disease incidence, they play a less significant role than other factors. For example, the worldwide movement of people (e.g., via air travel), as well as socioeconomic factors, was cited as potentially more significant drivers of infectious disease transmission. Understanding the relative importance of weather/climate, versus other variables, as drivers of disease remains the central issue to be resolved if a significant integration between weather/climate data and disease surveillance is to be made.
The existing scientific literature on climate and health is underdeveloped, primarily because the two communities generally work in parallel and do not sufficiently understand each other’s needs and functionality. Effective collaboration between climate and health groups remains an ongoing challenge, but opportunities for cooperation exist that need to be promoted.
The tremendous growth in meteorological data over the last 20 years has produced a large amount of information that can be used in tandem with infectious disease data. One advantage associated with creating this knowledge base is its potential for identifying new applications of meteorological information in disease studies. It also provides opportunities to identify practical applications for time-series and cross-geography research that would not necessarily be identified if these data were not available.
While the scientific community is generally adept at incorporating weather and climate information into its studies, the public health community is not widely experienced in this arena. While the public health community is beginning to incorporate weather/climate data into studies and decision-making processes, training this group to use weather/climate data effectively and appropriately remains a challenge due to a deficiency in opportunities for this form of targeted education.
It was evident that more discussion among the climate community, public health, and policy communities concerning how weather/climate surveillance data can be used to inform infectious disease control would be productive for all those engaged in identifying and controlling infectious disease outbreaks.
Despite conflicting viewpoints on the relative importance of weather/climate in the development and spread of infectious diseases, it was asserted that changing climatic conditions should nevertheless be considered in modeling, predicting, and operational decision-making for improving control of these diseases. Although it still is unclear whether other variables, such as socioeconomic status, are more important drivers, it was contended that each factor is an important component of the greater picture characterizing domestic and global changes in infectious diseases and that there is value in quantitatively determining more accurately the relative importance of various infectious disease drivers, including weather/climate.
Although some believed weather/climate factors do influence infectious diseases, it was not clear how weather/climate change information could influence operational prevention and control programs. Accordingly, it was suggested that funding that is currently used to prepare communities to adapt to climate change could be redirected into public health programs, including those programs that focus on infectious disease surveillance. This viewpoint was debated extensively, but without reaching a consensus as to whether funding should be redirected in this manner.
Weather and climate data are routinely and consistently collected, as well as widely available. Consequently, the cost of utilizing that data in health-related studies is relatively small compared with many other data sources. However, attention must be paid to ensuring that this information is appropriately used. Currently, when public health professionals do incorporate climate data into their research it is frequently done incorrectly. A cadre of public health professionals who are equipped with the skills and knowledge to integrate weather/climate into infectious disease studies is accordingly needed. Education and training on weather/climate should be integrated into public health studies, both via degree programs and continuing education modules.
It was noted that changing weather/climate patterns associated with climate change, and our present inability to halt these developments, have been used by some policy makers as an excuse for why infectious disease control and health interventions are not working. It was unanimously agreed that this rationalization is detrimental to positive change. Although most were unsure of how to stop these justifications, several suggested that better research to concretely support or refute these claims would be a step in the right direction.
It was widely expressed that the climate community needs to be able to demonstrate the value of climate surveillance information for infectious disease control to policy makers. Charts and diagrams may not be effective means to communicate the worth of weather/climate information to those in decision-making positions; rather, the climate community must demonstrate a return on investment and target areas where merging climate and infectious disease information has been a proven means of control. The climate community would be well served by demonstrating to policy makers how weather/climate data can be used to more effectively determine where resources should be targeted for the mitigation of infectious diseases.
Better integration of weather/climate data into infectious disease studies can lead to targeted interventions. For example, if it is found that an area is too dry, dams may be built or irrigation programs initiated. It is currently difficult, however, to obtain the political support needed to undertake these types of interventions. Education of policy makers on the importance of valid weather/climate outcomes is, therefore, important. Equally important is the ability of the climate and public health communities to effectively communicate these results to those in decision-making roles.
Copyright: Institute on Science for Global Policy