Expertise

Malaria

Malaria Data Systems for Smarter Surveillance & Optimized Campaigns

what we do

Data-driven digital tools that strengthen surveillance, intervention planning, and campaign performance

Our platforms improve data quality and enable adaptive responses — helping governments and partners tailor interventions based on real-time insights and geospatial intelligence.

National malaria data repositories and associated data products

Malaria risk stratification and subnational tailoring

Malaria campaign digitalization

Digital solutions for malaria surveillance, community health services, georegistries, and supply chain management

Challenge

Key Challenges in Managing Malaria Data Systems

Malaria control and elimination programs face critical obstacles due to fragmented and often unreliable malaria data. Improving malaria data systems is essential for better decision-making and more targeted interventions.

Insufficient surveillance and monitoring data

Limited digital tools hinder surveillance and routine monitoring of malaria control and elimination interventions.

Data fragmentation

Malaria surveillance, logistics, and campaign data are often siloed, limiting integration and insights.

Insufficient subnational tailoring

Outdated or incomplete malaria data reduces the accuracy of intervention planning.

Limited system integration

Campaigns and routine health services operate on separate data systems, creating inefficiencies.

Supply chain data gaps

Incomplete data on malaria commodities affects forecasting and stock management.

Solutions

Our solutions to optimize malaria control and elimination

We help national malaria programs and their partners optimize their data systems for malaria surveillance, intervention planning, monitoring and evaluation through a range of digital solutions, including the following:

National Malaria Data Repositories (NMDRs)

We support the development of centralized malaria data systems to improve visibility, coordination, and strategic decision-making. NMDRs unify fragmented data streams into a single platform, enabling comprehensive analysis and tailored planning at national and subnational levels.

Integration of malaria data from DHIS2, LMIS, campaign platforms, and a broad range of other sources and information systems into a unified repository
Interactive dashboards and automated bulletins for malaria data monitoring, analysis, and reporting
Climate, entomology and other data layers combined with advanced analytics via OpenHEXA
Customizable tools for subnational risk stratification and strategic intervention planning
Predictive models and automated alerting built on top of the unified repository
Genomic and molecular surveillance integration to track the evolution of treatment resistance

Predictive Analytics and Early Warning

We support national malaria programs in moving from retrospective reporting to proactive response. Building on unified data repositories, we help develop and operationalize predictive models that anticipate transmission surges and trigger automated alerts before outbreaks accelerate. This approach is deployed through PaluTrack, a malaria surveillance strengthening project supported by the Gates Foundation across six countries in West and Central Africa.

Predictive modeling built on unified national malaria data repositories that allow for combining rainfall, climate, and epidemiological data to anticipate case surges and optimize resource allocation
Acute fever hotspot detection algorithms integrated with WHO’s Early Warning, Alert and Response System (EWARS) to support rapid emergency operations activation
Automated surveillance alerts and cross-cutting analyses powered by OpenHEXA pipelines and Apache Superset dashboards

Risk Stratification and Local Tailoring

We support malaria programs in optimizing resource allocation through advanced risk analysis and data-driven planning. Our tools help prioritize interventions based on transmission patterns, seasonality, and health system capacity, ensuring smarter and more targeted responses.

Unified data processing through standardized OpenHEXA pipelines integrating global (DHS, MAP, ERA5, WorldPop) and local data sources (HMIS/NMDR).
AI-supported analytics and visualization of core stratification layers, including incidence, prevalence, mortality, seasonality, demographic indicators and care-seeking patterns.
Risk stratification and intervention planning in a geospatial web app, where composite risk strata and district-level intervention packages (LLINs, IRS, SMC, vaccines) are built and compared across scenarios — assisted by an AI chatbot that translates plain-language requests into reproducible layers.
Evidence-based decision-making combining integrated costing frameworks (PATH, CHAI) with imported epidemiological impact estimates from established modelling groups (IDM, Swiss TPH, AHADI, PATH), so risk, cost and impact are visible side by side.

Campaign Digitalization (LLIN, SMC, vaccine)

We enable the end-to-end digitalization of malaria campaign operations, from microplanning to supervision and reporting. By combining geo-based tools with real-time data flows, our solutions improve coverage, accountability, and operational efficiency across bednet (LLIN), seasonal malaria chemoprevention (SMC), and malaria vaccination campaigns.

Microplanning with IASO, leveraging georegistries for precise household targeting
Real-time tracking dashboards and supervision tools for community health workers (CHWs)
Integrated LQAS (Lot Quality Assurance Sampling) dashboards and performance monitoring modules
Seamless interoperability with DHIS2 and mobile payment systems for CHW incentives

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Collaboration

Who we support

Public authorities

Ministries of Health, Social and Environmental Programmes, etc.

International organizations

World Health organization, UN agencies, etc.

Non-Governmental Organizations (NGOs)

International and in-country organizations