DHIS2 supports the incorporation of climate, weather, and environmental data into programs in the health sector and beyond, as well as integration with specialized systems. Through existing features and functionality in development, we aim to facilitate spatial and temporal analysis of environmental factors in a variety of contexts
The DHIS2 platform is already able to collect and import data of various types for combined analysis. Through our new Climate & Health project, we are enhancing and expanding the functionalities of DHIS2 to support a range of use cases in this domain. These new developments include the DHIS2 Climate App for climate, weather, and environmental data integration and harmonization, and the DHIS2 Modeling App and Chap Modeling Platform for predictive modeling and forecasting of climate-sensitive diseases. Thanks to the combination of these new functionalities with the existing scope and scale of DHIS2 as a health information system, DHIS2 has been officially recognized as a Global Good for Climate and Health.
On this page, we provide examples of some climate and health use cases that we are exploring during the initial phases of our Wellcome-funded research project. We also list some of the core DHIS2 functionalities and tools that support these use cases. However, these lists are not exhaustive. If you have additional climate and health use cases that DHIS2 could support, including environmental factors beyond weather or climate (ie. air pollution), or additional DHIS2 functionalities that are required for your climate and health project, we encourage you to contact us at climate@dhis2.org
This use case builds on existing disease surveillance systems by integrating climate and weather data to improve early warning and response for climate-sensitive infectious diseases (vector, water, and food borne), such as malaria, dengue, diarrhea, zika, etc. Historical and current climate and health data are used to develop predictive models based on relationships between environmental factors and the corresponding likelihood of disease outbreaks in specific geographies, including the spread of diseases to new areas. Outputs from these systems can be used to:
This use case builds on existing nutrition and agriculture systems to support early warning and response to weather events, changing climate patterns, and seasonal variation that affect crop production and prevalence of malnutrition. Data from these systems can help improve nutrition programmes & food security by helping plan mitigation actions, outreach activities, and resource prioritization.
This use case incorporates early warning and response systems for heat waves, floods, or other extreme weather events into routine and emergency health programs. It builds on existing DHIS2 systems for routine service delivery and can expand DHIS2 systems for new data sources (NCD data, emergency response, etc.). Outputs from these systems can be used to:
Note: The video shown here is an illustrative example of incorporating updated satellite imagery into the DHIS2 Maps application. This functionality is still in development.
The DHIS2 platform provides a number of applications, features, and tools that can facilitate the integration and use of climate data in information systems:
The Climate App allows users to explore and import temperature, precipitation, elevation, and other environmental data into data elements of their DHIS2 instance. Values are automatically calculated for the organisation units users select. Import daily data that can be aggregated to other periods in DHIS2. The app uses various data sources, including ERA5-Land, which is considered the most accurate and complete climate dataset available with worldwide coverage. Users can either explore the data directly in this app, or through the DHIS2 analytics apps after importing. This will also allow for combining climate and health data in the same visualizations and dashboards.
A national DHIS2 system can host data from a variety of sources, allowing program managers to carry out and visualize composite analysis between health, climate, and other data sources in one place using customizable dashboards.
Data can be entered into DHIS2 via the web interface or on mobile devices, with robust offline support. Data entry forms are flexible and can be locally configured for a variety of data, reporting formats and tempos. Data can also be uploaded in bulk or integrated from other systems. This flexibility provides a large number of options for incorporating climate data into DHIS2.
The built-in Maps application in DHIS2 permits the import and use of geospatial datasets via the Google Earth Engine, including satellite data and climate services. These can be combined with programmatic data for geospatial and temporal analysis. Data from DHIS2 can also be exported to GIS programs for more advanced analysis.
DHIS2’s open and documented API and suite of integration tools facilitates interoperability with external software systems and data sources. Within Climate & Health implementations, this can allow DHIS2 systems to connect to purpose-built climate data systems and external software for complex predictive modeling.
DHIS2 is designed to allow for extending functionality through the use of custom applications, scripts, and widgets, which can help tailor the system to meet local needs for a C&H use case, as well as serving as a method for developing low-cost local innovations on top of the DHIS2 platform that can be shared with other users.
Several new DHIS2 features and applications are now available to support Climate & Health use cases:
DHIS2 app to explore daily and monthly temperature, precipitation and humidity data, and more. The app uses several data sources, including ERA5-Land, which is considered the most accurate and complete climate dataset available with worldwide coverage. Import weather, climate, elevation, and other environmental data into DHIS2 data elements. Values are aggregated to DHIS2 organisation units on Google Earth Engine.
Pilot app for DHIS2 that provides seamless integration with the Chap Modeling Platform, providing a user-friendly interface within DHIS2 for selecting data to use to generate predictions in Chap – including data from the DHIS2 Climate App – train predictive models, visualize predictions, and evaluate model accuracy.
This app is currently in testing. Visit the Chap wiki on Github for more information.
The Chap Modeling Platform is an open-source software platform for climate and health data harmonization and climate-sensitive disease forecasting that allows you to access, import, train, tune, run, assess, and share predictive models leveraging the power of machine learning/AI. Chap is developed by HISP to integrate seamlessly with DHIS2 via the Modeling App, but can also be used independently with other data sources.
If you are interested in learning more or getting involved in predictive modeling and disease forecasting with DHIS2, we invite you to connect with the Chap team.
