In April 2024, Uganda joined nine other countries as a pilot site under the DHIS2 Climate and Health Initiative, supported by Wellcome Trust through the HISP Centre at the University of Oslo and local implementation partner HISP Uganda. This marked a significant step toward integrating environmental intelligence into national health systems. From the outset, the objective was clear: to leverage data for protecting populations against the increasing health risks associated with climate change and deteriorating air quality.
DHIS2 is a free and open-source platform developed and maintained by the HISP Centre at the University of Oslo in Norway, and recognized globally as a digital public good. Its implementation is locally owned, highly customizable, and can be extended through custom applications and web APIs. DHIS2 is currently used in over 80 countries for the collection, management, and analysis of health data, making it the world’s largest health management information system (HMIS) platform. In Uganda, the Ministry of Health has adopted DHIS2 as the national HMIS for the past 13 years. Today, over 7,000 health facilities across 146 districts report data into the system on a routine basis, forming the backbone of evidence-based health planning and monitoring in the country.
Uganda’s participation in this initiative aligns closely with the country’s commitment to the Health National Adaptation Plan (H-NAP) 2025–2030, which prioritizes the development of climate-informed health systems and early warning frameworks for climate-sensitive diseases. By integrating data on temperature, precipitation, humidity, heat stress, and air quality into DHIS2, Uganda is enhancing its capacity to predict, detect, and respond to environmental health threats in a timely and evidence-based manner.
What’s unique about this initiative is how familiar platforms like DHIS2 are being used in transformative ways. By layering climate and environmental data with routine health outcomes, Uganda is pioneering a scalable model for climate-resilient health planning.
Collaboration and National Ownership
Though still in a pilot phase, this initiative has been a remarkable journey of innovation and partnership, drawing together a broad spectrum of stakeholders committed to safeguarding Uganda’s health in the face of changing climatic conditions. At the center is the Ministry of Health, with key leadership from the Department of Environmental Health, which leads the implementation of H-NAP and coordinates broader climate-health initiatives. The Health Information Management Division (HIMD), as the national custodian of health data, has played a critical role in technically embedding climate intelligence into existing health reporting structures.
Figure 1: Inaugural stakeholders’ meeting in April 2024
Several technical health departments and divisions have been engaged, some of whom have shaped the design and implementation of climate-health use cases. These include the National Malaria Control Division (NMCD), Nutrition Division, Department of Integrated Epidemiology, Surveillance, and Public Health Emergencies, Department of Non-Communicable Diseases (NCDs), Maternal, Newborn, Child, and Adolescent Health (RMNCAH), and the Neglected Tropical Diseases (NTDs) Department, among others.
Equally, critical partnerships with the Ministry of Water and Environment, though still on the path to strengthening, particularly the Department of Meteorological Services, have already demonstrated their technical leadership in the use of climate data. Their support has included guiding Ministry of Health teams in sourcing, validating, and contextualizing climate datasets using both local and global sources.
Climate and Environmental Data Integration
A key innovation under this pilot has been the integration of climate and environmental health data into the national health information system. As illustrated in Figure 3, through the DHIS2 Climate App, a custom application developed by the HISP centre, daily aggregated district-level climate data, including temperature, precipitation, relative humidity, vegetation index, and heat stress, have been imported from global sources such as ERA5 and NASA. These global datasets have been validated through comparison with locally sampled climate data, ensuring contextual relevance and accuracy. Additionally, real-time air quality data (PM10 and PM2.5) from Makerere University’s AirQo Project has been integrated into DHIS2. This collaboration on air quality has enabled integration of data from over 70 fixed air quality monitors across Kampala, Uganda’s capital. This integration has paved the way for the co-development of analytical products in collaboration with health programs, resulting in use cases that are set to be deployed for both national and sub-national decision-making. The collaboration has also been enriched by the contributions of implementing partners, development agencies, and other government ministries, reinforcing Uganda’s commitment to mainstreaming climate resilience in health planning.
Figure 2: The Department of Meteorological Services takes the MOH team through climate data collection at a local weather station.
Figure 3: Integration of climate data (Courtesy of HISP Centre)
Translating Data into Action
The journey began with listening. Through extensive stakeholder engagement and co-design, three use cases were identified and built within DHIS2, each addressing a critical climate-sensitive health risk in Uganda as elucidated below;
- Towards Early Warning for Non-Communicable Diseases
In Kampala and other urban settings, health teams began to explore a critical question: Is rising air pollution worsening the burden of non-communicable diseases (NCDs)? Through a collaboration with Makerere University’s AirQo Project, real-time air quality data, specifically PM2.5 and PM10, were integrated with DHIS2-reported data on asthma and COPD, and layered alongside climate variables such as temperature and rainfall from ERA5 and CHIRPS. The analysis revealed that COPD exhibited strong associations with elevated PM2.5 levels and higher temperatures, particularly during the dry season. Similarly, asthma showed consistent positive correlations with both PM2.5 and PM10; however, interaction terms highlighted clear seasonal patterns, indicating the compounding effects of environmental stressors on NCD-related respiratory health.
Figure 4: Sample Monthly GLM coefficients that were visualized using radar charts, with red dots marking statistically significant months (p < 0.05)
- Malaria Risk Mapping: Forecasting Transmission Using Climate Data
With over 12 million malaria cases annually, Uganda is integrating climate-based prediction into its malaria prevention strategies. To support this, the team developed a composite risk score based on three key climate thresholds: monthly rainfall of at least 80 mm, temperature ranging between 18–32°C, and relative humidity of 60% or higher. These parameters were configured in DHIS2 using climate data from ERA5 and local meteorological stations, enabling the generation of real-time malaria risk maps. These tools now support timely planning for indoor residual spraying (IRS), stock pre-positioning, and targeted community messaging, well ahead of transmission peaks.
Figure 4: Sample Climatic Suitability for Malaria by District
- Predictive Mapping for Malnutrition: Using Machine Learning to Curb Malnutrition
With 3 in 10 children under five affected by undernutrition, Uganda applied machine learning models (Random Forest, XGBoost, KNN, Linear Regression) to historical SAM data, climate variables, malaria/pneumonia trends, and population estimates. The result was the generation of district-level SAM risk scores, trend visualizations, and feature importance plots in DHIS2, providing evidence that can be used for nutrition program prioritization and resource targeting.
Figure 5: Sample Predicted SAM Risk Scores by District
Looking Ahead: Building Resilience Through Digital Integration
Efforts are currently underway to build capacity and deploy these tools to support national and sub-national climate-informed planning. Notably, Uganda’s DHIS2 Climate and Health Pilot has demonstrated the transformative potential unlocked when data, technology, and cross-sector collaboration converge. By integrating environmental intelligence into the national health information system, the pilot is showing that DHIS2 can serve as a robust platform for climate-health analytics, delivering real-time insights that empower proactive public health action, shifting the paradigm from crisis response to prevention and preparedness.
The pilot also highlights the importance of contextualizing both local and global datasets, such as ERA5, CHIRPS, and AirQo air quality feeds, within Uganda’s epidemiological and operational landscape. When harmonized and visualized through DHIS2 dashboards, maps, and predictive tools, these datasets can empower health managers to make timely, evidence-informed decisions at national and sub-national levels.
More broadly, this work lays a strong foundation for climate-resilient health governance. It demonstrates how digital infrastructure can strengthen the country’s capacity to anticipate and respond to climate-sensitive health risks when strategically aligned with national adaptation priorities like those outlined in Uganda’s Health National Adaptation Plan (H-NAP). As Uganda looks ahead, the success of this pilot will position it as a model for scaling integrated climate-health surveillance systems across other regions and disease areas, offering vital lessons for countries facing similar climate-health vulnerabilities.