Estimating the current size of the 2026 DRC Bundibugyo virus outbreak

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

Last updated: 25 June 2026. This is a live report, re-run as new data arrive, so the estimates change between updates.

Data as of: 22 June 2026. DRC counts come from the situation reports of the Institut National de Santé Publique (INSP); Uganda imports come from WHO. The rendered report fills in the build date and the exact data cut-off automatically.

See: current outbreak size · one-week-ahead forecast · estimate evolution across releases · comparison with McCabe et al. · how the data streams compare · limitations · full joint results.

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. This is a real-time joint Bayesian estimate of the current size of that outbreak, refreshed as new data arrive. Most infections are not yet reported, so the current size has to be inferred from the surveillance data that are available. The model is a discrete-time renewal process on a daily grid that fits the surveillance streams jointly in a single posterior: the DRC suspected cases, suspected deaths, laboratory-confirmed cases and confirmed deaths, and the cases and deaths exported to Uganda. It estimates the latent infections, symptom onsets and deaths over time, the reported and confirmed cases, and the time-varying reproduction number with its growth rate and doubling time, alongside the case-fatality ratio, the ascertainment of each surveillance system, and a short-term forecast of each stream over the coming week. The DRC data come from the INSP situation reports and the Uganda exports from the WHO situation reports and Disease Outbreak News, with a genetic bound on the time to the most recent common ancestor and priors taken from the McCabe et al. report.

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.

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 data

The observations live in data/observations.toml; the literate picks up new numbers automatically. The figures come from the INSP situation reports, transcribed by INRB-UMIE/BDBV2026-Data, and are refreshed for each new sitrep with the scripts/ tooling (task download-sitreps, task confirm-data):

• The cumulative confirmed-case and confirmed-death series come from the upstream national_* daily CSVs, regenerated and spot-confirmed against our own scan by scripts/confirm_insp_data.jl.

• Every other stream (suspected totals, laboratory cumulatives, the 24h analysed volume, daily new suspects, isolation occupancy, bed capacity and recoveries) is read directly from the situation-report PDFs (fetched by scripts/download_sitreps.jl into data/sitrep_pdfs/) and recorded in data/insp_sitrep_scanned.csv.

scripts/confirm_insp_data.jl cross-checks the scan against the upstream national series and exits non-zero on any disagreement.

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 by INRB-UMIE/BDBV2026-Data, https://github.com/INRB-UMIE/BDBV2026-Data.

• 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).

• McCabe et al. estimates that this work re-implements and compares against, in all three released versions (the two Imperial reports and the peer-reviewed Lancet publication) — 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. McCabe, R., Ebbarnezh, L., Okware, S., Fotsing, R., Koua, E., Mbaka, P., Lofungola, A., Ebengo, D. M., Mbala, P. K., Bishola, T. T., Ibolobolo, C. M., Matondo, H. M., Sibo, J.-C. M., van Elsland, S. L., McMenamin, M., Ferguson, N., le Polain de Waroux, O., Cori, A. (2026). Estimation of the Ebola outbreak size in the Democratic Republic of the Congo. The Lancet Infectious Diseases, correspondence, online first 9 June 2026; estimates as of 27 May 2026. DOI: 10.1016/S1473-3099(26)00299-9.

• 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.

Funding

This work was funded by the National Institute for Health and Care Research (NIHR) Health Protection Research Unit in Health Analytics & Modelling, a partnership between the UK Health Security Agency, Imperial College London and the London School of Hygiene & Tropical Medicine (grant code NIHR207404). The views expressed are those of the author(s) and not necessarily those of the NIHR, UK Health Security Agency or the Department of Health and Social Care.

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.