This page shows the forecast that the MOBS Lab at Northeastern University submits each week to the InsightNet BDBV Modeling Hub. The target is the number of laboratory-confirmed cases of Bundibugyo virus disease in the DRC by week of symptom onset (Sunday to Saturday), as it will stand once all reports are in.
Each submission covers eight weeks: the four weeks before the reference week, for which the hub data are still being reported, the reference week itself and the three weeks after it. It consists of 100 trajectories of the calibrated GLEAM model. The median and the 50 % and 90 % intervals are computed from these 100 trajectories. Point at the chart to see the values for a week, and at a line to follow a single trajectory.
Model. GLEAM is a stochastic metapopulation model in which population basins are connected by daily commuting and air travel [1]. Within each basin, transmission follows a care-pathway model of Ebola disease, with community, hospital and funeral transmission and three branches of care (community, health-care facility and isolation) [2–4]. Individual transmissibility is overdispersed (dispersion k = 0.1). Five scenarios cap the share of cases routed to isolation at 30, 40, 50, 60 and 75 %.
Calibration. Model runs are first selected on the early cross-border onsets in Uganda and the early activity in Beni. They are then fitted to the increase in cumulative confirmed cases reported in the DRC situation reports since 31 July 2026 [5]. Confirmed cases are modelled as a multiple of the cases routed to isolation, and reach the reports after a delay from symptom onset with a mean of 5 days. Runs are accepted when the mean absolute percentage error is at most 5 %. The five isolation scenarios are pooled, so each contributes in proportion to its share of accepted runs. The hub data are not used in the fit.
Forecast. The 100 trajectories are drawn from the accepted runs so that each isolation scenario is represented by its share. Weekly values are confirmed cases by week of symptom onset with Poisson noise, i.e. the final counts once all reports are in. Before the submitted weeks, the trajectories shown are drawn in the same way from the same runs, for comparison with the data; they are not part of the submission.
Data. Hub data are DRC confirmed cases by week of symptom onset from the hub's target data [6], in the two most recent releases. The most recent weeks keep increasing in later releases as reports come in.
Assumptions. Isolation stays at the level of each scenario over the forecast horizon, and reporting practice does not change. Detection is assumed proportional to isolation across the DRC. The forecast is national; provinces are not forecast.
- 1Balcan D, Gonçalves B, Hu H, Ramasco JJ, Colizza V, Vespignani A. Modeling the spatial spread of infectious diseases: the GLobal Epidemic and Mobility computational model. J Comput Sci. 2010;1(3):132–145.
- 2Legrand J, Grais RF, Boelle PY, Valleron AJ, Flahault A. Understanding the dynamics of Ebola epidemics. Epidemiology and Infection. 2007;135(4):610–621.
- 3Gomes MFC, Pastore y Piontti A, Rossi L, Chao D, Longini I, Halloran ME, Vespignani A. Assessing the international spreading risk associated with the 2014 West African Ebola outbreak. PLOS Currents Outbreaks. 2014.
- 4Ajelli M, Muyembe J-J, Touré A, Diallo A, Litvinova M, Merler S, et al. Vaccination strategies for Ebola in the Democratic Republic of Congo: the WHO-Ebola modeling collaboration. International Journal of Infectious Diseases. 2025;153:107779.
- 5Institut National de Santé Publique, République Démocratique du Congo. Situation reports, Maladie à Virus Bundibugyo. Available at: https://insp.cd/category/sitrep/
- 6InsightNet BDBV Modeling Hub, target data. Available at: https://github.com/InsightNet-US/BDBV-Modeling-Hub