Turning Malaria Surveillance Data into Timely Decisions in Nigeria
Published on
October 2026
Introduction
Leading a Solution to Transform Vector-Borne Disease Surveillance in Nigeria
Nigeria has invested in malaria surveillance systems that generate valuable information about mosquito populations, transmission patterns and insecticide resistance. However, much of this information remains difficult to access and analyse in time to inform critical public health decisions. By the time programme managers receive surveillance findings, conditions on the ground may have changed.
To address this challenge, Osun State University (UNIOSUN), one of the Nigerian awardees selected through the Umbrella Fund's GeoHealth Innovation Call, is developing GeoSmart Nigeria (GeoSmart), an integrated platform designed to bring real-time geospatial data into the surveillance, early warning and management of vector-borne diseases.
Based in Osogbo, Nigeria, UNIOSUN aims to bridge the gap between surveillance data collection and its practical use, enabling public health institutions to make more timely, informed decisions. The GeoHealth Innovation Call supports locally led solutions that improve how geospatial data is collected, analysed and used within public health systems.
The Problem
Nigeria carries the world's largest malaria burden, accounting for approximately 25% of global malaria cases and 31.9% of malaria deaths in 2024. These figures underscore the importance of strengthening malaria surveillance and programme planning, both for Nigeria and global malaria control efforts.
Nigeria has implemented several interventions to prevent malaria and reduce transmission, including seasonal malaria chemoprevention, insecticide-treated net distribution, indoor residual spraying, diagnosis, treatment and other vector-control activities. Effective delivery requires timely information about mosquito populations, transmission patterns, insecticide resistance, environmental conditions and areas facing the greatest risk.
The National Malaria Elimination Programme (NMEP) has already invested in surveillance systems to generate this information. Between 2020 and 2024, its national vector surveillance programme collected entomological data across 72 local government areas in 12 states, creating an important resource for understanding mosquito species, behaviour, distribution and resistance to insecticides.
However, much of this information still passes through paper-based records, separate spreadsheets and systems with limited interoperability. Cleaning and analysing entomological data can take several months, meaning that surveillance findings may no longer capture changing conditions by the time they reach programme managers.
These delays limit NMEP's ability to identify emerging risks, assess surveillance completeness, detect data-quality problems and adjust vector-control activities promptly. Reliance on specialist support for certain analyses further affects how quickly programme managers can interpret and act on the findings. During its engagement with UNIOSUN, NMEP identified real-time surveillance, improved data-quality detection and faster analysis as priority areas for improvement.
Similar challenges affect surveillance for neglected tropical diseases and other vector-borne diseases, where reliable systems are needed to connect field data collection, analysis, early warning and programme planning. Addressing these gaps in malaria surveillance could therefore provide a foundation for strengthening Nigeria's response to a wider range of vector-borne diseases.
About GeoSmart Nigeria
GeoSmart Nigeria is designed to help malaria programme teams move surveillance data more efficiently from field collection to analysis and practical use. The platform will integrate real-time geospatial data collection, automated analysis, data-quality checks, early warning alerts and a decision-support dashboard within a single system.
Through an offline-capable mobile application, field entomologists and health workers will record the locations and characteristics of mosquito populations, breeding sites, insecticide resistance and other relevant conditions. The platform will automatically check the information for missing, duplicate or unusual records before analysing it, generating updated maps, surveillance summaries and alerts to guide decisions on vector-control activities.
Historical surveillance records will also be integrated with newly collected field data, enabling programme managers to monitor transmission risks, identify changes in mosquito populations and insecticide resistance, and determine where closer attention or intervention may be required. The platform aims to make surveillance outputs available within 24 hours of field data collection, significantly reducing the delays that currently limit their operational use.
GeoSmart Nigeria will align with DHIS2 and Nigeria's national health-data governance requirements. The project will work with the relevant Department of Planning, Research and Statistics to map GeoSmart data to existing DHIS2 structures and establish an appropriate integration pathway. This approach is intended to strengthen Nigeria's existing health information system and support the use of surveillance findings within official programme processes.
UNIOSUN will lead the development of GeoSmart Nigeria in partnership with NMEP, participating state malaria elimination programmes and relevant national health-data authorities. NMEP will help define priority surveillance indicators, data-quality checks, alert thresholds and the programme decisions the platform should support. This collaboration will bring together the university's technical expertise and the operational experience of government institutions, supporting institutional ownership and long-term sustainability.
The nine-month pilot will be implemented in Ogun, Kano and Osun States from October 2026 to June 2027. Field workers and programme managers will test the platform during routine surveillance and planning activities, enabling the project team to refine its functions based on practical experience. Lessons from the pilot will inform a government-endorsed plan for transferring the platform to NMEP and expanding its use to other states and vector-borne disease programmes.
Looking Ahead
Through its partnership with UNIOSUN, the Umbrella Fund is supporting a locally led solution that seeks to strengthen how malaria surveillance information is translated into public health action.
The GeoSmart Nigeria pilot will provide an opportunity to assess how integrated geospatial surveillance can improve programme planning, strengthen institutional capacity and inform approaches to monitoring other vector-borne diseases.
Ultimately, effective malaria surveillance depends not only on collecting reliable data, but also on ensuring that the information reaches decision-makers when it is needed. By connecting data collection, analysis and programme planning, GeoSmart Nigeria aims to support more responsive, coordinated and evidence-informed malaria control efforts in Nigeria.
To learn more about this work or explore partnership opportunities, follow the Umbrella Fund on social media or contact us at team@umbrellafund.org
