Building GIS Capacity and Ownership in Sudan: A Collaborative Model for Sustainable Health System Capacity
Introduction and ObjectivesSudan's ongoing conflict has disrupted health services and surveillance systems, contributing to overlapping disease outbreaks and a rising noncommunicable disease burden. Surveillance data collection has been uneven and delayed, with Early Warning, Alert and Response completeness at 66% and timeliness at 44% as of March 2025, constrained by insecurity, movement restrictions, and infrastructure loss. Geographic information systems (GIS) remain a largely untapped resource for connecting field-level data to local decision-making, but access to GIS training and tools has historically been concentrated outside Sudan. This report describes a recent partnership between Sudan's Ministry of Health (MOH), diaspora clinicians, and academic institutions to build decentralized GIS capacity among surveillance staff and examines its early implications for humanitarian surveillance and health system resilience. MethodologyIn May 2026, the Yale Center for Geospatial Solutions (YCGS) hosted a week-long GIS Accelerator in New Haven, USA: an established internal training program run each January and May that builds applied ArcGIS skills through structured instruction paired with individualized project support. As part of the Sudan Public Health Surveillance Strengthening Project, funded by the 2025 Hecht Award, MOH staff were identified as a priority group for this training. The Sudanese American Physicians Association (SAPA) convened the partnership, contributed diaspora expertise, and covered internet costs; Yale graduate students and postdocs served as coordinators, evaluators, mentors, and tutors; and MOH nominated staff and coordinated their participation. Fourteen MOH staff across disease surveillance, geospatial, epidemiology, and information technology roles completed the training.Results and DiscussionTrainees gained direct experience in spatial analysis tools, enabling independent mapping and surveillance work that previously required external technical support. At the system level, this positions MOH to apply geospatial analysis to outbreak investigation and resource allocation, including mapping NCD burden and care access gaps among displaced populations. The initiative also modeled a structural shift in global health partnership design. Rather than concentrating analytic capacity in the Global North, the program built co-production and South-led ownership into how the tools and skills reached Sudanese practitioners. Achieving long-term sustainability remains a key challenge: securing training access requires sustained negotiation around software licensing. Furthermore, continued mentorship and long-term software access are still being secured.ConclusionsDecentralized GIS capacity building demonstrates a scalable, field-driven approach to strengthening health surveillance in conflict-affected settings. This partnership illustrates how ministries of health, diaspora networks, and academic institutions can jointly build durable technical capacity, even under conditions of active conflict, and highlights the value of investing in GIS and remote technical support as part of broader health system resilience strategies in fragile settings. Acknowledgments: We thank Dr. Kaveh Khoshnood, Dr. Faihaa Dafalla, and Jack Crew for their support and facilitation, and YIGH, the Hecht Award, YCGS, and SAPA for their partnership.
Authors
- Kaveh Khoshnood (ORCID: https://orcid.org/0000-0003-2795-0447)
- Eman Mukhtar Nasr Salih (ORCID: https://orcid.org/0000-0003-0186-0021)
- Sabanur Çavdar (ORCID: https://orcid.org/0000-0001-5490-6877)
- Monzur Morshed Patwary (ORCID: https://orcid.org/0000-0001-6210-0881)
- Philip Kutjok
- Heba Magdy Metwally (ORCID: https://orcid.org/0009-0004-6208-8826)
- Jack Crew
- Kinsey Medlin
Institutions
- Emory University (US)
- Yale University (US)
- Federal Ministry of Health (SD)
- Egyptian Government (EG)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-29
- DOI
- https://doi.org/10.5281/zenodo.23750625
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00