Network-based modelling of Bundibugyo Ebola virus disease importation and spread in Uganda using Displacement Tracking Matrix flow data and non-pharmaceutical intervention compliance scenarios

The 2026 Bundibugyo Ebola outbreak in Uganda, linked to the ongoing epidemic in the Democratic Republic of the Congo (DRC), spread through human mobility across borders and within the country. We constructed a data-driven directed weighted mobility network using IOM Displacement Tracking Matrix (DTM) flows collected from 15–24 May 2026 (11,245 observed movements) and the 2024 Uganda census (45.9 million people). A stochastic metapopulation SEIR model, incorporating pre-symptomatic transmission and the movement of both exposed and infectious individuals, was simulated over 90 days across 135 Ugandan districts and two DRC provinces. The mobility network was sparse (density 0.11), highly unequal (Gini coefficient 0.67), and modular (modularity 0.5). Kisoro district had the highest import risk (in-strength 3,823) and export risk (out-strength 1,350), while Kampala showed substantial in-strength (1,290) but lower out-strength (150). Under baseline mobility, the model projected a median of 69–70 cumulative cases (95% CrI: 57–98) and 3 deaths over 90 days. Non-pharmaceutical interventions (community contact reduction, healthcare protection, movement restriction) at 20%, 40%, and 60% compliance produced no statistically significant reduction in cases. Superspreading events occurred in 34.6–40.6% of simulations. Kampala bore the highest predicted burden (median 22 cases, 100% outbreak probability more than 10 cases), followed by Wakiso (11 cases, 64.9%). Border districts had lower burdens (Bundibugyo 5, Kasese 3, Kisoro 2). Sobol sensitivity analysis (500 samples, 200 bootstraps) identified the infectious period (first-order index 0.838), case fatality rate (0.738), and basic reproduction number (0.664) as the most influential parameters; mobility-related parameters had lower total-order indices. Given that mobility already saturates the transmission potential in the connected network, resources should focus on targeted surveillance at high-risk importation hubs (Kisoro for border screening) and inland epidemic centres (Kampala for response capacity), rather than untargeted nationwide interventions.