From Risk Score to Field Action: Development of a Health-Zone-Level Operational Prioritization and Action Framework for the 2026 Bundibugyo Virus Disease Outbreak in the Democratic Republic of the Congo

Background The 2026 Bundibugyo virus disease (BVD) outbreak, caused by Bundibugyo virus (BDBV), was declared by the Democratic Republic of the Congo (DRC) Ministry of Public Health on 15 May 2026 and subsequently reported across multiple health zones in Ituri, Nord-Kivu, and Sud-Kivu provinces. The World Health Organization subsequently determined that the event constituted a public health emergency of international concern. Outbreak situation reports generate large volumes of health-zone-level data, but operational teams require a standardized mechanism for translating those data into prioritized, role-specific field guidance.Methods This study developed the Bundibugyo Virus Disease Operational Intelligence System (BVD-OIS), a three-module framework built on an eight-domain Health Zone Operational Priority Index (HZ-OPI, version 1.1). The first additional module, the Field Action Prioritization Tool (FAPT), adds a trajectory layer that classifies changes in a health zone’s composite score between reporting cycles and a binding constraint engine that identifies the response domain most likely to limit outbreak control. The second additional module, the Response Intelligence Audit (RIA), flags health-zone domains where available data are insufficient to support confident scoring. All modules use aggregate, health-zone-level indicators from public reports and do not use individual-level data.Results The framework produces two standardized outputs: a one-page Health Zone Action Card combining priority tier, trajectory, binding constraint, data completeness, and time-stratified role-specific actions; and a Multi-Zone Priority Summary ranking scored health zones for coordination settings. This manuscript specifies the domain scoring rubric, priority tiers, 21-day inactivity override, trajectory classification scheme, binding constraint hierarchy, action translation matrix, data gap detection logic, and a fully worked illustrative example using hypothetical health-zone data.Conclusions The BVD-OIS provides a reproducible pathway from routinely reported outbreak surveillance indicators to field-level operational guidance. The framework is descriptive and not a validated predictive model. It is intended for transparent operational learning, local adaptation, and prospective validation during filovirus and other high-consequence outbreak responses.