This community innovation has been accepted at the 2026 DHIS2 Annual Conference as a digital poster.
Air Quality Analysis with DHIS2 Climate Tools
Air pollution is a growing contributor to respiratory disease burden, yet environmental exposure data and routine health information are often managed in separate systems. This separation limits the ability of health programs to assess climate-related risks and respond proactively. Integrating air quality intelligence into national health information platforms can enable timely, evidence-based decision-making. To implement a scalable DHIS2-based workflow that integrates satellite-derived air quality data with routine morbidity records using DHIS2 Climate Tools to support climate–health surveillance and planning. Using DHIS2 Climate Tools and open-source workflows, satellite aerosol optical density and ground monitoring data were processed into bias-corrected 1 km gridded PM2.5 surfaces (NetCDF format). These data were aggregated to DHIS2 organizational units using both raw and population-weighted exposure estimates. De-identified hospital morbidity records were prepared as CSV files, filtered for respiratory diagnoses (ICD-10), mapped to facilities, and imported as events through the DHIS2 API. Automated scripts generated routine data imports and enabled integrated indicators, dashboards, and time-series analyses. The system enabled routine district-level comparison of PM2.5 exposure with respiratory admissions, revealing clear spatial and seasonal patterns. Population-weighted aggregation improved exposure estimation in densely populated areas. Automation reduced manual processing time and enabled regular updates. Analytics performed to identify high-risk districts, support preparedness actions, and inform policy discussions on air quality and climate resilience. DHIS2 Climate Tools can transform environmental datasets into actionable public health intelligence within existing national systems. This low-cost, open-source approach demonstrates a practical and replicable model for integrating climate and health data to strengthen surveillance, planning, and decision-making at scale.
Primary Author: Priyanga Senanayaka
Keywords:
DHIS2, Climate Tools, climate–health, air pollution, PM2.5, environmental health, satellite data, earth observation, health analytics, interoperability, surveillance, respiratory diseases, population-weighted exposure