Innovative community-based data collection to understand and find solutions to rainfall-related diarrhoeal diseases in Ecuador
Tailored climate products are most frequently the result of partnerships that process and present climate data or information, either alone or in combination with other types of data or information, in such a way that makes the information usable for a specific purpose. Climate services, on the other hand, refer to the needs-driven processes that bring about the production and delivery of climate information relevant for managing climate-sensitive health risks.
The transformation and translation of climate information products to useful tailored climate-informed health decision tools often involves the development of a combination of separate but interlinked products, which are needed to forecast health risks or produce early warnings. Each product must have a sufficient degree of quality, reliability, usability, suitability and responsiveness to changing needs. The degree to which these criteria are met determines how, and if, the information can be further applied, and whether health decision-makers will trust the information enough to use it confidently for decision-making. Health decision tools which use climate information to understand and predict health risks commonly fall into the following categories and present characteristic advantages and challenges:
The technical development of tailored climate products and services is crucial. For product development and delivery to be effective, however, the activities conducted within the other five components must lead up to and support this stage.
Critically, almost all activities to develop health-tailored climate products and services must first begin with looking backwards and working with historical climate data to conduct a combined longitudinal analysis of epidemiological data (or a sensitivity analysis) to identify if climate signals exist, and can be further used to forecast or predict disease outbreaks or other health risks. Therefore, the data sharing policies for the access and use of national climate data should be immediately established as part of an enabling environment and in order to advance to developing applied services.
Both an enabling environment and sufficient capacity play a crucial role in ensuring the access, applicability and suitability of the climate products and service developed. Research findings are key to informing the necessary requirements and optimal conditions for further deployment. Evaluation will ensure that services meet the expected quality criteria, serve the functions they were designed for, and provide feedback from users to iteratively improve the product or service.
Categories of tailored products |
Example advantages |
Example challenges |
MONITORING SYSTEMS AND INTEGRATED SURVEILLANCE |
Provide comprehensive and real time detection of health risks.
Serve to trigger response plans.
Facilitate data sharing and access for relevant stakeholders.
Provide the basis for development of all other product categories.
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Poor data quality, availability and interoperability across systems.
Establishment of data sharing agreements between stakeholders.
Effective links between monitoring activities and response plans.
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CORE ANALYTICS |
Enable dynamic characterization of health risks across space and time.
Facilitate identification of vulnerable populations.
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Lack of analytical capacity to calculate thresholds and develop risk models.
Lack of fundamental research to inform the development of key analytics.
Absence of standard indicator definitions.
Limited availability of geo-coded information.
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RISK FORECASTS |
Anticipate the likelihood of when and where health impacts may occur.
Provide extended lead time for preparedness.
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Varied level of skill in weather and climate predictions across regions and seasons.
Lack of sufficiently reliable and long data sets.
Poor mechanistic understanding of health risk dynamics.
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EARLY WARNING SYSTEMS (EWS) |
Create awareness of prevention and preparedness needs and opportunities.
Provide authoritative and continuous source of information to guide risk management.
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Dependencies on quality of all the above product categories.
Limited availability of robust thresholds to trigger warnings.
Reliance on weather and climate forecasts with limited predictive ability.
High levels of institutional commitment and capacity to sustain the EWS and respond to warnings.
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PROJECTIONS AND SCENARIOS |
Enable foresight of future risks and alternative futures to inform mid- and long-term decision making.
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High levels of uncertainty in climate projections.
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Monitoring systems and integrated surveillance are foundational elements for most climate products and services, necessary to collect, compare, and manage data. Technical data and software requirements vary according to the respective goals of each initiative. Data quality, availability and compatibility are common challenges, and innovative data collection or data preparation techniques are frequently needed to enhance, transform or blend data to be usable.
For example, to compensate for the lack of, poor quality, or poor coverage of climate and environmental observation and monitoring systems, techniques that blend local meteorological or environmental observations with remotely sensed data are often used. Similarly, national health surveillance systems can be strengthened by integrating data sourced from sentinel sites, early disease detection or community-based disease surveillance systems in order to generate comprehensive datasets. Furthermore, in addition to climate and environmental variables, socioeconomic data or other data representing population vulnerability may also be needed for a more comprehensive understanding of the health problem.
Monitoring and integrated surveillance systems combine relevant health, climate and other socioeconomic data and are commonly presented through user-friendly interfaces that allow for data to be queried, visualized and downloaded according to desirable criteria (e.g. disease type, risk factors, time interval, future climate scenarios, etc.). To ensure these systems can support health decision inputs from the public health community, spatial and temporal data compatibility are essential. Health decisions are often made at a district/county level, requiring climate or weather forecasts, outlooks or projections to be downscaled to spatial units that are meaningful to health professionals. Climate and health data comparability can be increased when data is collected from meteorological and health stations located in close proximity.
Core analytics including indicators, thresholds, models and maps are generated from descriptive and statistical analyses. Indicators and thresholds are typically numerical indices against which health risks or impacts can be measured. Choosing appropriate indicators and thresholds is vital for triggering health alerts, such as air pollution indicators or UV indices. While
there are a wide variety of possible risk indicators that can be used, the main types of information used to construct such indicators are: climate or environmental hazard characteristics (such as severity, starting time, duration, etc.); climate and environment conditions (humidity, temperature, rainfall, etc.); population vulnerability and exposure factors (such as immunity, remoteness, malnutrition or poverty); and the socioeconomic context of a given population (such as conflict, agricultural practices or education level).
Risk models and maps help describe and illustrate the spatial and temporal dimensions of climate-related health risks to population health. Three main types of maps can support climate-smart health decision-making:
Risk forecasts can be used to anticipate when and where climate conditions may increase the likelihood for health impacts to occur. These risks can be estimated by integrating forecasts of weather, climate and other relevant conditions at different timescales into mathematical or statistical disease transmission or incidence models. The risk management of diverse health hazards may require weather and climate forecasts with different lead times. For example, initiatives addressing community heat-related health risks may use local weather forecasts with lead times of several days to anticipate heat stress risks for specific populations. Long-term climate projections can help anticipate the number of extreme hot days populations may be exposed to in the future.
Early warning systems use risk forecasting and thresholds to alert health professionals as well as the public of rapid-onset emergencies such as extreme weather or disease outbreaks. They are important to provide communities and professionals additional lead time for preparing and responding to the event. Hazard and exposure thresholds are set at different levels of estimated risks to trigger appropriate actions.
Communication strategies within these systems ensure the proper dissemination of warnings to health decision makers, emergency response teams, communities and especially to vulnerable populations. Strategies to disseminate warnings include formal partnerships and communication exchange protocols with key stakeholders and the assessment of the most popular and effective communication channels (such as social media and instant messaging platforms, television, radio or websites) to reach out to the greatest possible number of community members.
Projections and scenarios are risk models that generate projections of health risks up to several decades into the future, and are commonly based upon IPCC climate change scenarios and regional climate change projections. Risk models can go beyond generating estimations of future health risks of diseases, to incorporate evaluations of the effectiveness of different adaptation strategies in accordance with different climate scenarios.