Ebola Bundibugyo Virus — DRC
Spread Risk Assessment #1

On 16 May 2026, following laboratory confirmation of Bundibugyo virus disease (BVD), the WHO Director-General declared a Public Health Emergency of International Concern. As of 18 May 2026, the Democratic Republic of the Congo reports 33 laboratory-confirmed cases and 516 suspected cases with 131 suspected deaths across seven health zones in Ituri and North Kivu provinces; two laboratory-confirmed importations have been detected in Kampala, Uganda [1]. Using the GLEAM (Global Epidemic and Mobility) framework [4,5], we quantify relative importation risk under two scenarios: Ituri Province as sole source of exportation, and the confirmed multi-province footprint spanning Ituri, North Kivu, and Kampala. Approximate Bayesian Computation (ABC) inference, conditioned on the two detected importations, estimates a median of 773 underlying infections (90% CrI: 237–1,811) at 100% detection efficiency abroad. Under the Ituri-only scenario, the highest-risk destinations are Uganda's Western Region (RR 29.3%) and Northern Region (RR 21.0%), consistent with the first confirmed importation presenting initially in Hoima District, Western Uganda [1]. Under the expanded footprint, the South Kivu–Rwanda corridor emerges as an elevated-risk axis, though absolute risk outside Africa remains below 1%.

1   Introduction

On 16 May 2026, following laboratory confirmation of Bundibugyo virus disease (BVD) on 15 May 2026, the WHO Director-General determined that the outbreak constituted a Public Health Emergency of International Concern (PHEIC) under the International Health Regulations (2005). WHO had first received an alert on 5 May 2026 regarding an unknown illness with high mortality in Mongbwalu Health Zone, Ituri Province, Democratic Republic of the Congo. As of 18 May 2026, DRC has reported 33 laboratory-confirmed cases and 516 suspected cases, with 131 suspected deaths, across seven health zones: Mongbwalu, Nyankunde, Rwampara, and Bunia in Ituri Province, and Butembo, Katwa, and Goma in North Kivu Province. Two laboratory-confirmed imported cases, including one death, have been reported in Kampala, Uganda [1].

Preliminary IPC assessments in affected facilities revealed major gaps in screening, triage, and patient isolation, with four healthcare worker deaths reported to date. A total of 668 contacts have been identified (541 in DRC, 127 in Uganda). Cross-border transmission risk remains elevated due to active population movement, mining activities, insecurity, and the porous DRC–Uganda border.

This report quantifies local importation risk from Ituri Province, estimates the underlying outbreak size using the two Uganda-exported cases as observational evidence in a Bayesian framework, and evaluates how the risk footprint shifts under the confirmed multi-province geographic footprint spanning Ituri, North Kivu, and Kampala.

2   Methods

Mobility data

Global air travel patterns are derived from the International Air Transport Association (IATA) and the Official Airline Guide (OAG), providing passenger-level origin–destination flows between international airports. These data are complemented by short-scale commuting patterns capturing daily movements between adjacent subpopulations, representing the local spread of disease through routine human activity within and across health zones. The modeling approach follows the GLEAM (Global Epidemic and Mobility) computational framework [4,5].

Relative importation risk

For each potential destination Y, the model estimates the probability P(Y) that an infected individual originating in the affected area travels to Y, conditional on at least one exported case occurring. The output is a relative risk distribution across all candidate destinations, normalized so that values represent the share of importation probability assigned to each location.

Outbreak size estimation

The number of infections at the origin is inferred using an Approximate Bayesian Computation (ABC) approach. Given the observed international exportations as data D, the posterior distribution P(θ|D) over outbreak size θ is approximated by repeatedly simulating outbreaks of varying sizes, generating synthetic exportation events under the mobility model, and retaining parameter values whose simulated outputs are consistent with the observations. Two parameters condition the inference: the incubation period of BVD (2–21 days; average ~10 days based on the 2007 Uganda outbreak) and the case-detection efficiency abroad. Three detection-efficiency scenarios (100%, 66%, 50%) are reported to bound sensitivity to this assumption. Observed evidence: two laboratory-confirmed importations to Kampala, 15–16 May 2026 [1].

3   Analysis from Ituri Province

Under the scenario treating Ituri Province as the primary source of transmission, relative importation risk is heavily concentrated in the immediate cross-border region. The single highest-risk destination is the neighboring DRC province of Beni, followed by Uganda's Western Region (Kasese; RR 29.3%) and Northern Region (Pakuba, Arua; RR 21.0%), with Isiro (DRC) at lower magnitude. This spatial pattern is directly validated by the first confirmed importation to Uganda: a 59-year-old male from DRC who initially sought care in Hoima District, Western Uganda (the model's highest-ranked Ugandan corridor) before being admitted to a Kampala health facility on 11 May 2026 [1].

The Kampala detection reflects downstream clinical transfer rather than direct importation to the capital. The case's trajectory (initial presentation in the western border corridor, then referral to Kampala) is precisely what the model predicts: the highest cross-border entry probability runs through the short overland routes from Ituri into western Uganda, with onward healthcare-seeking in the capital following initial contact with local services.

4   Size of the Epidemic

The two internationally exported cases identified as importations in Kampala provide observational evidence for inferring the underlying scale of transmission in Ituri Province. Using these detected importations within the ABC framework, three scenarios are estimated reflecting different assumptions about case-detection efficiency abroad. Lower detection implies that the same two observed exports must be generated by a larger underlying outbreak.

Even under the most optimistic assumption (100% detection), the lower 5th percentile of the posterior sits above 200 infections. Preliminary IPC assessments in DRC documented major gaps in screening and isolation; four healthcare worker deaths further underscore the risk of nosocomial amplification [1].

The credible intervals are wide, reflecting genuine uncertainty given that only two exportation events have been observed. As additional exported cases are confirmed, or as time passes without further detected importations, posterior intervals will narrow and the most plausible detection-efficiency regime will become identifiable.

5   Analysis under the Current Expansion

The Ituri-only analysis represents an early-outbreak baseline. As confirmed by the WHO Situation Report of 18 May 2026, cases have been confirmed in seven health zones spanning Ituri and North Kivu, and the Kampala importations demonstrate that transmission has reached the Ugandan capital [1]; a more realistic scenario treats the outbreak as having a multi-node geographic footprint spanning Ituri, North Kivu, and Kampala.

Under this expanded scenario, the relative importation risk distribution shifts in three meaningful ways. First, Kampala enters as an active exportation source: because Kampala is connected by air to a much wider range of African and intercontinental cities than Ituri, its inclusion redistributes a portion of total exportation probability toward destinations the Ituri-only model assigned negligible risk: Kigali (RWA), Bukavu (DRC), Cyangugu (RWA), and a long tail of cities including Dubai, Nairobi, and Johannesburg. Second, the South Kivu–Rwanda corridor emerges as an elevated-risk axis that was below the detection threshold under the Ituri-only model. Third, risk outside the African region remains below 1% in absolute terms, but the set of plausible international destinations is broader than under the single-source scenario.

6   Limitations & Assumptions

Model scope

The mobility model does not incorporate sociodemographic attributes of travelers (age, economic status, occupation, or pre-existing medical conditions), any of which may modulate both exposure risk at origin and care-seeking behavior at destination. Travel probability within a catchment area is treated as independent of these attributes and of specific location within the catchment.

Case importations are modeled as statistically independent events. Real-world events involving multiple related cases (for example, a family cluster traveling together) are counted as a single importation event. To the extent that such clusters are common, the model will under-count the number of distinct exposure events while correctly counting the number of distinct geographic seedings.

Data limitations

Mobility data may not fully capture informal cross-border movement, which is substantial in the Ituri–Uganda corridor. The outbreak-size inference is sensitive to the assumed detection-efficiency scenario; actual detection efficiency in Uganda is not directly observed and may vary by port of entry, healthcare-seeking pathway, and clinical presentation.

Epidemiological assumptions

The incubation period of Bundibugyo virus (2–21 days; average ~10 days) constrains the window within which an exported case could reasonably travel while infectious or pre-symptomatic. The model does not predict downstream transmission chains following importation events: risk estimates reflect the probability of a single importation and do not account for the probability of sustained local transmission in the receiving location.

7   References

[1] World Health Organization Regional Office for Africa. Ebola Bundibugyo Virus Disease Outbreak — Democratic Republic of the Congo | Uganda. Weekly External Situation Report 01. Data as of 18 May 2026. Available at: afro.who.int

[2] World Health Organization. Epidemic of Ebola disease caused by Bundibugyo virus in the Democratic Republic of the Congo and Uganda determined a public health emergency of international concern. WHO Statement, 16 May 2026.

[3] Centers for Disease Control and Prevention. Ebola Disease: Current Situation. CDC Situation Summary, 18 May 2026.

[4] Balcan 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. Journal of Computational Science. 2010;1(3):132–145.

[5] Davis JT, Chinazzi M, Perra N, Mu K, Pastore y Piontti A, Ajelli M, Dean NE, Gioannini C, Litvinova M, Merler S, Rossi L, Sun K, Xiong X, Longini IM, Halloran ME, Viboud C, Vespignani A. Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave. Nature. 2021;600:127–132.

[6] Wamala JF, Lukwago L, Malimbo M, et al. Ebola hemorrhagic fever associated with novel virus strain, Uganda, 2007–2008. Emerging Infectious Diseases. 2010;16(7):1087–1092.

[7] International Air Transport Association (IATA). Passenger Intelligence Services. IATA, 2026.

[8] Official Airline Guide (OAG). Aviation Analytics. OAG, 2026.