Estimating the current size of the 2026 DRC Bundibugyo virus outbreak: a joint Bayesian re-analysis of the McCabe et al. report

Authors: Sam Abbott, Kath Sherratt, Samuel Brand and Sebastian Funk.

Last updated: 26 May 2026. This is a live report, re-run as new data arrive, so the estimates change between updates.

Data as of: 23 May 2026. DRC counts come from the situation reports of the Institut National de Santé Publique (INSP); Uganda imports come from WHO. Estimates are reported as of this date; it can lag the update date above.

Abstract. An outbreak of Ebola disease caused by Bundibugyo virus (BVD) is ongoing in the Democratic Republic of the Congo (DRC), with cases also detected across the border in Uganda. Estimating the likely current size of the outbreak is useful for the response, but most cases are not yet reported and have to be inferred from the data streams that are available. The Imperial College London report (McCabe et al., 18 May 2026, revised in a 20 May 2026 update) estimates the size with two analyses, geographic spread from the cases exported to Uganda and back-calculation from suspected deaths in DRC. Building on that work, we re-analyse the same problem as a single joint Bayesian model over the latent cumulative case count, fitting all streams together with priors on the nuisance parameters that the report varies in scenario sweeps. Beyond the exported cases and DRC deaths the report uses, we condition on two further streams, the reported cases in DRC (with an ascertainment component) and the deaths among exported cases in Uganda. We also add a no-onward-transmission projected-deaths counterfactual, a one-week-ahead forecast and an onset-to-death delay sensitivity analysis, and replace two closed-form approximations (the deaths convolution and the small-growth-rate exports term) with their exact forms. We report the joint posterior over the cumulative case count from current data; to separate the effect of newer data from the change in method we also fit the model to the data as of each report version in sequence (18 May, then the 20 May update), comparing against both a joint reimplementation of the report's approach and its original published estimates at each version.

Scope. This work is motivated by adding an external view of the current situation, based on our understanding of real-time infectious disease dynamics and the infection process that gives rise to observed epidemic surveillance counts. We are actively developing it and encourage feedback, so please get in touch. We fully support reuse and adaptation. Find out more in the contributing guide.

Use of AI. The model code and analysis were drafted by a language model and reviewed and revised under human oversight; the named authors are responsible for that oversight.

Why our numbers differ from McCabe et al. Two reasons. First, the method: we fit all streams jointly in a single Bayesian model rather than combining separate scenario analyses (see each way our method departs from the report). Second, the data: our cut-off is later than either McCabe et al. report version (16 May for the 18 May report; 18 May for the 20 May update). The joint posterior assumes a single common cut-off for every data stream, so the deaths, exports and reported-case counts must all be kept in sync to the same date.

See: current outbreak size · comparison with McCabe et al. · how the data streams compare · limitations · full joint results.

Installing the package

To use the model and the bundled outbreak data from your own Julia environment, add the package from the repository:

using Pkg
Pkg.add(url = "https://github.com/epiforecasts/BVDOutbreakSize")

You can then load the model machinery and the data the report is fitted to:

using BVDOutbreakSize
obs = load_observations()

This gives you the exported model components, constants and data loaders, enough to build your own analysis on top of the package. Reproducing the full report (fitting the models and writing the result tables and plots) can be done in a few ways, described next.

Running

There are a couple of ways to re-fit the model.

Re-fit from a clone

git clone --recurse-submodules https://github.com/epiforecasts/BVDOutbreakSize
cd BVDOutbreakSize
julia --project=. -e 'using Pkg; Pkg.instantiate()'
julia --project=. scripts/run.jl

scripts/run.jl fits the models and writes the output CSVs (the analysis literate is also run as part of the docs build). Running docs/examples/analysis.jl directly instead steps through the full narrative.

Re-fit without cloning

scripts/reproduce.jl fetches the package, instantiates its environment, and runs the fit:

curl -fsSL https://raw.githubusercontent.com/epiforecasts/BVDOutbreakSize/main/scripts/reproduce.jl | julia

Outputs land in ./bvd-output; set BVD_OUTPUT_DIR to write them elsewhere, or BVD_REF to a release tag to reproduce a specific version. The script clones into a temporary directory and runs from there, so it leaves your own Julia environments untouched.

Render the docs page

Executes the literate and produces HTML at docs/build/:

julia --project=docs -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
julia --project=docs docs/make.jl

Updating the observation counts for a new sitrep is a single-file edit of data/observations.toml; the literate picks the new numbers up automatically.

Outputs and releases

Each push to main regenerates the model outputs as part of the documentation build and publishes them as a GitHub Release. The latest release bundles the saved result tables and plots, thinned posterior draws, a copy of the input observations.toml that produced them, a site.zip snapshot of the rendered report site, and analysis.html, a self-contained single-file copy of the report that opens offline (download the latest); the same artifacts are written to the repository's output/ directory on each build. Browse all releases for earlier output bundles — major versions of the report are kept as GitHub Releases.

The rendered report is published from the gh-pages branch, where past and development versions of the analysis page can be found.

Submodules

• external/bdbv-linelist-analysis — Bayesian reanalysis of the 2012 Isiro BDBV line list (Rosello et al. 2015). Source of the informative onset-to-death gamma shape and scale priors.

Citation

If you use or build on this project, please cite the works this repository depends on:

• This project — Abbott, S., Brand, S., Funk, S. (2026). BVDOutbreakSize: joint forward-generative Turing model for the 2026 DRC Bundibugyo outbreak. https://github.com/epiforecasts/BVDOutbreakSize. DOI: 10.5281/zenodo.20312758.

• INSP situation reports that supply the DRC suspected-case and suspected-death counts and the sitrep cumulative trajectory — Institut National de Santé Publique, Démocratique du Congo (2026). Situation reports on the 17th Ebola epidemic. https://insp.cd/ebola-17eme-epidemie/. Transcribed across health zones by INRB-UMIE/Ebola_DRC_2026, https://github.com/INRB-UMIE/Ebola_DRC_2026.

• WHO situation reports and Disease Outbreak News that supply the Uganda import-case counts and the dated detection and death events for the first Uganda import — World Health Organization Regional Office for Africa (2026). Ebola disease caused by Bundibugyo virus outbreak, Democratic Republic of the Congo and Uganda — Weekly External Situation Report 01. Data as of 18 May 2026. World Health Organization (2026). Disease Outbreak News: Ebola disease caused by Bundibugyo virus — Democratic Republic of the Congo and Uganda (DON602, DON603). Source of the first Uganda import hospital-admission date (11 May 2026) and the fatal import death date (14 May 2026).

• Imperial reports that this work re-implements and compares against, in both released versions — McCabe, R., Ebbarnezh, L., Okware, S., Fotsing, R., Koua, E., Mbaka, P., Lofungola, A., van Elsland, S. L., McMenamin, M., Ferguson, N., le Polain de Waroux, O., Cori, A. (2026). Estimation of the size of the outbreak of Ebola disease caused by Bundibugyo virus in DRC. Imperial College London, 18 May 2026. DOI: 10.25560/130007. Report page. McCabe, R. and others (2026). Estimation of the size of the Ebola outbreak caused by Bundibugyo virus in DRC: May 20, 2026 update. Imperial College London, 20 May 2026. DOI: 10.25560/13005307. Report PDF.

• Onset-to-death delay reanalysis that this work uses for delay priors — Funk, S. (2026). bdbv-linelist-analysis: Bayesian reanalysis of the 2012 Isiro Bundibugyo line list. https://github.com/sbfnk/bdbv-linelist-analysis.

Further references

• Rosello et al., Ebola virus disease in DRC, 1976–2014, eLife 2015. Original Isiro 2012 onset-to-death gamma point estimate.

• Imai et al., Estimating the potential total number of novel coronavirus cases in Wuhan City, Imperial COVID-19 Response Team Report 1, 17 January 2020. Methodological template for Method 1.

• Charniga et al., Best practices for estimating and reporting epidemiological delay distributions, PLOS Computational Biology 2024. Followed for the delay-distribution reporting here.