On 16 May 2026 the WHO Director-General declared a Public Health Emergency of International Concern (PHEIC) for the outbreak of Ebola disease caused by Bundibugyo virus in the Democratic Republic of the Congo and Uganda [4]. As of 21 June 2026, DRC has reported 1,048 laboratory-confirmed cases and 267 confirmed deaths (case-fatality ratio ≈ 25 %) across 34 health zones spanning Ituri, North Kivu and South Kivu, with 371 patients currently hospitalised in isolation at Ebola Treatment Centers (ETC) and treatment facilities [1,2]. Uganda has reported 20 laboratory-confirmed cases including 2 deaths [3].
This report presents a stochastic, metapopulation transmission model built using the GLEAM framework [5], incorporates transmission occurring in the hospital, community, and through funerals, and it explicitly models isolation protocols through ETC. The model is calibrated in two stages using an Approximate Bayesian Computation approach on observed cross-border importations from Ituri to Uganda, and on the cumulative laboratory-confirmed count in Ituri at 13 June 2026 assuming a case ascertainment rate as low as 20 %.
Key findings
1
Posterior R₀ ≈ 2.34 (90 % CrI [1.83, 3.08]); empirical doubling time 10.6 d (90 % CrI [8.5, 13.5]). Posterior predictive cumulative cases in Ituri at the snapshot date 24 May 2026: median 757, 90 % CrI [378, 1,298].
2
Forward projection at 24 June 2026 (iso 75 %). Cumulative symptomatic cases in Ituri 2,509 (90 % CrI [1,053, 4,688]); active cases (I + H + ETC) 541 (90 % CrI [189, 1,260]); new symptomatic cases per day 52 (90 % CrI [15, 137]).
3
Scenario outcomes by 31 August 2026. Probability of ≥ 20,000 cumulative symptomatic cases: 0 % under 95 % isolation, 3 % under 75 %, 45 % under 50 %. Strong isolation (95 %) drives the outbreak to extinction by the end of August. The realistic 75 % target keeps cumulative size below 20,000 in most of the trajectories but transmission persists at end of August, although declining. An isolation rate of 50 % does not adequately control the outbreak, nearly half of trajectories exceed 20,000 cases.
The intervals reported below are predicted under the assumed model, intervention scenario and ascertainment-conditioned posterior. Calibration extends only to the 13 June 2026 confirmed-case evidence. Projections beyond that date are model-driven and depend on assumptions about isolation timing and intensity.
2 — Calibration and posteriors
Two-stage calibration and posteriors
The model is calibrated by Approximate Bayesian Computation in two stages. Stage 1 conditions on observed cross-border importations from Ituri to Uganda, requiring exactly one Uganda importation by 14 May 2026 and exactly one further importation in the window 14 to 18 May 2026. Stage 2 conditions the Stage-1 posterior on the cumulative laboratory-confirmed count in Ituri at 13 June 2026 (717 cases) allowing ascertainment as low as 20 %, requiring the simulated cumulative symptomatic onsets in Ituri by 13 June to lie in the window [717, 3,585].
The filtered posterior yields a median R₀ of 2.34 (90 % CrI [1.83, 3.08]) and a median empirical doubling time of 10.6 d (90 % CrI [8.5, 13.5 d]), measured by log-linear fit to cumulative onsets in Ituri over the pre-isolation window before 15 May.
Figure 1 — Filtered posterior: R₀ and empirical doubling time
Posterior densities over the 950 accepted trajectories from the two-stage calibration. R₀ is taken directly from the joint posterior; the doubling time Td is measured per draw by log-linear fit to cumulative symptomatic onsets in Ituri over the pre-isolation window before 15 May 2026. KDE on linear axes (Gaussian kernel, Scott bandwidth); dashed line marks the median; shaded band the 90 % credible interval; dots below the baseline show a 250-trajectory subsample.
Parameter
Median
90 % CrI
R₀
2.34
[1.83 – 3.08]
Td (days)
10.6
[8.5 – 13.5]
Cumulative cases in Ituri at 24 May 2026
As a reference snapshot of the posterior before the projection horizon, the filtered posterior predictive distribution of cumulative symptomatic cases in Ituri on 24 May 2026 has a median of 757 and a 90 % credible interval of [378, 1,298].
Filtered posterior predictive distribution of cumulative symptomatic cases in Ituri on 24 May 2026, n = 950 trajectories. Gaussian KDE on log-transformed values (Scott bandwidth); dashed line marks the median; shaded band the 90 % credible interval; dots below the baseline show a 250-trajectory subsample.
Posterior summary · 24 May 2026
Median
757
IQR
[542 – 985]
90 % CrI
[378 – 1,298]
3 — Forward projection at 24 June 2026
Posterior predictive distributions, Ituri · 24 June 2026 · iso75
The Stage-2 posterior predictive distributions in Ituri at the projection date 24 June 2026, eleven days after the evidence-filter date and six weeks into the 75 % isolation ramp, are summarised below. The cumulative outbreak continues to grow modestly (≈ 30 % over the eleven days following the filter date), while the active cases is roughly flat and daily incidence is gently declining. These dynamics are consistent with Reff just below 1: the outbreak is no longer expanding exponentially but the residual transmission keeps it from extinguishing within the projection horizon.
Filtered posterior predictive distributions in Ituri on 24 June 2026 under 75 % target isolation: cumulative symptomatic cases (top, navy), active cases, community + HCF + ETC, (middle, red), and new symptomatic cases per day (bottom, teal). Shared log x-axis. Gaussian KDE on log-transformed values; dashed line marks the median; shaded band the 90 % credible interval; dots below each baseline show a 250-trajectory subsample. n = 950 trajectories.
Statistic
Median
90 % CrI
Cumulative cases
2,509
[1,053 – 4,688]
Active (I + H + ETC)
541
[189 – 1,260]
New per day
52
[15 – 137]
4 — Scenario projections
Scenario projections through 31 August 2026
Forward projections evaluate three target isolation rates, 50 %, 75 % and 95 %, each phased in at 10 percentage points every 2 days from 15 May 2026 in the Ituri Province until the scenario target is reached. We assume a similar ramp up of isolation in North and South Kivu but with a starting date that is a week later (May 22). The isolation Q determines the probability with which each new symptomatic case is routed to the isolation pathway (Iiso → HETC → ETC). Isolation-tracked cases are identified faster than routine cases (onset-to-HCF 2 d versus 5 d on the routine track) and progress to the ETC compartment, where transmission stops and any deaths receive safe and dignified burial. A small residual nosocomial channel (10 % of the baseline HCF rate) is retained during the 3-day HCF → ETC transit, reflecting imperfect IPC during transfer; community deaths and routine-HCF deaths still contribute to funeral transmission.
Probability of a large outbreak by 31 August 2026
The probability that the cumulative number of symptomatic cases in Ituri exceeds 10,000 by 31 August 2026 is 70 % under 50 % isolation, 21 % under 75 % and 0 % under 95 %. For the higher threshold of ≥ 20,000 cases, the corresponding probabilities are 45 %, 3 % and 0 %.
Figure 4 — Probability of a large outbreak in Ituri by 31 August 2026
Probability that cumulative symptomatic cases in Ituri exceed 10,000 (left) and 20,000 (right) by 31 August 2026, by target isolation rate. Bars show the fraction of filtered posterior trajectories above each threshold; n = 950 per scenario.
Target isolation
P(≥ 10,000)
P(≥ 20,000)
50 %
70 %
45 %
75 %
21 %
3 %
95 %
0 %
0 %
Controllability — daily incidence on 31 August 2026
As a measure of controllability we compute the probability that daily new symptomatic onsets in Ituri exceed 10 cases on 31 August 2026, the end of the simulation window. Under 50 % isolation the probability is essentially certain (100 % of filtered trajectories). Under 75 % isolation it is 78 %, indicating that the outbreak is bounded in cumulative size but sustained low-level transmission persists. Only under 95 % isolation does the probability drop substantially, to 5 %, indicating that the outbreak is driven to extinction by end-August in nearly all trajectories.
Figure 5 — Probability of > 10 daily symptomatic onsets in Ituri on 31 August 2026
Probability that daily new symptomatic onsets in Ituri exceed 10 on 31 August 2026, by target isolation rate. Bars show the fraction of filtered posterior trajectories above 10 daily new cases on that date; n = 950 per scenario.
Target isolation
P(daily > 10)
50 %
100 %
75 %
78 %
95 %
5 %
5 — Methods
Methods
Model framework
The framework is GLEAM (Global Epidemic and Mobility Model) [5], an Africa-wide metapopulation network coupled by daily commuting matrices and origin-destination passenger flows from IATA Passenger Intelligence Services and OAG Aviation Analytics. The within-basin compartmental dynamics are simulated as a discrete-time multinomial chain-binomial process. At each time step the number of individuals exiting a compartment is drawn from a binomial with exit probability 1 − exp(−Σᵢ λᵢ · Δt), and exits are partitioned across the available destination compartments by a multinomial whose probabilities are proportional to the per-route hazards. We do not assume any mobility reductions between subpopulations: no behavioral reduction, no border closure is explicitly modeled.
Compartmental structure
The compartmental structure follows a Legrand-like SEIHFR scheme [7,8]. However, in order to model the impact of isolation and safe burial protocols, we increase the complexity of the model to incorporate three potential outcomes an infectious individual could experience (see Fig. 6 for details):
Community Branch: the individual does not get admitted to any healthcare facility. They are able to infect people in the community in their infectious stage and, if death occurs, through unsafe burial practices.
HCF-only Branch: the infected individual is infectious for an average time of 5 days until they are admitted to a HCF where they can generate new infections through nosocomial transmission and, if death occurs, through unsafe burial practices.
Isolation Branch: individuals are infectious for an average time of 2 days before they are moved to a HCF for an average time of 3 days and have a transmissibility that is 10 % of individuals in a HCF in the HCF-only branch. They are then moved to an ETC, where they no longer contribute to ongoing transmission.
The funeral compartment F is fed only by community deaths and regular-HCF deaths (deaths in ETC receive safe and dignified burial and bypass F). Transmission rates by compartment: βI in all three community-infectious compartments (Icom, IcomH, Iiso), βH in regular-track H, βH,iso = 0.1 · βH in the HCF → ETC transit compartment HETC, zero in ETC, and βF in F.
Natural-history parameters
Compartmental dwell times and severity values are based on literature. The Legrand-type SEIHFR formulation [7,8] supplies the framework, Wamala et al. [9] are the source for the original 2007–2008 Uganda BVD outbreak data on which some of the BVD-specific natural-history estimates rest. Isolation-pathway case-finding timings (Tiso and The) follow the 2018 North Kivu RVEAP response [6].
Symbol
Meaning
Value
Source
TE
Latent period (Erlang-2 mean)
8 d (prior U(5, 10))
[8, 9]
TI
Icom dwell (community, no HCF)
9.6 d
[7, 8]
Tsh
Onset to HCF admission, routine track
5 d
[8]
Tiso
Onset to HCF admission, iso track
2 d
[6]
The
HCF to ETC transit, iso track
3 d
[6]
TH
HCF stay, routine track
4.6 d
[7, 8]
TETC
ETC stay
4.6 d
assumed equal to TH
TF
Funeral period
2 d
[7, 8]
pH
HCF admission probability (Legrand baseline)
0.80
[8, 9]
δnh
CFR, non-hospitalised
0.50
supportive-care gradient
δh
CFR, regular HCF
0.45
supportive-care gradient
δetc
CFR, ETC
0.30
best clinical management
R₀ split
Community : HCF : Funeral at baseline
0.44 : 0.22 : 0.34
[8]
κiso
HCF iso transmission factor (βH,iso / βH)
0.1
assumed (residual nosocomial)
Figure 6 — Compartmental structure of the model
Twelve compartments, three potential outcomes at E₂ exit. Latent stages E₁ → E₂ feed three parallel infectious-community sub-compartments: Icom (community-only fate, dwell TI), IcomH (regular HCF fate, dwell Tsh = 5 d) and Iiso (isolation fate, dwell Tiso = 2 d). Routine cases progress to H with full nosocomial transmission rate βH; isolated cases progress through HETC (residual rate 0.1 · βH) to ETC (no transmission, safe burial). The funeral compartment F (transmission rate βF) is fed only by community and regular-HCF deaths.
Seeding
The epidemic originates in Ituri, DRC, with 5 infectious cases on the inferred start date. Every other basin (including all of Uganda) begins fully susceptible and is reached only through mobility coupling.
Inference — two-stage calibration
The model is calibrated by Approximate Bayesian Computation in two stages. Stage 1 conditions on observed cross-border importations from Ituri to Uganda, requiring exactly one Uganda importation by 14 May 2026 and exactly one further importation in the window 14 to 18 May 2026. Stage 2 conditions the Stage-1 posterior on the cumulative laboratory-confirmed count in Ituri at 13 June 2026 (717 cases) allowing ascertainment as low as 20 %, requiring the simulated cumulative symptomatic onsets in Ituri by 13 June to lie in the window [717, 3,585].
Parameter
Prior
Notes
R₀
U(1.2, 5.0)
Basic reproduction number
Incubation period TE
U(5, 10) d
Erlang-2 (two-stage latent)
Outbreak start date
U(15 Feb, 15 Mar 2026)
Date of first case in Ituri
Ascertainment sensitivity
The Stage-2 evidence filter assumes a specific ascertainment rate that maps the laboratory-confirmed count to a credible window on simulated cumulative onsets. The baseline analysis allows ascertainment as low as 20 % (window [717, 3,585]). The table below shows how the accepted posterior changes if we instead allow ascertainment as low as 15 % ([717, 4,780]) or 10 % ([717, 7,170]).
Min ascertainment
n accepted
R₀ (med · 90 % CrI)
Td (med · 90 % CrI)
10 % (≤ 7,170)
1,322
2.43 · [1.85, 3.26]
10.3 d · [8.1, 13.4]
15 % (≤ 4,780)
1,141
2.43 · [1.85, 3.26]
10.3 d · [8.1, 13.4]
20 % (≤ 3,585), baseline
950
2.34 · [1.83, 3.08]
10.6 d · [8.5, 13.5]
Posterior medians are stable across the three ascertainment assumptions (R₀ shifts by about 4 %, Td by about 3 %). The 90 % credible-interval upper bounds tighten progressively as the assumed ascertainment rises (the stricter the cap on simulated cumulative cases, the smaller the right-tail mass that is accepted). The qualitative scenario conclusions are unchanged: the High (95 %) scenario achieves extinction by 31 August across all three ascertainment assumptions, the Low (50 %) scenario remains uncontrolled.
Isolation mechanism
Forward projections evaluate three target isolation rates, 50 %, 75 % and 95 %, each phased in at 10 percentage points every 2 days from 15 May 2026 in the Ituri Province until the scenario target is reached. We assume a similar ramp up of isolation in North and South Kivu but with a starting date that is a week later (May 22). The isolation Q determines the probability with which each new symptomatic case is routed to the isolation pathway (Iiso → HETC → ETC). Isolation-tracked cases are identified faster than routine cases (onset-to-HCF 2 d versus 5 d on the routine track) and progress to the ETC compartment, where transmission stops and any deaths receive safe and dignified burial. A small residual nosocomial channel (10 % of the baseline HCF rate) is retained during the 3-day HCF → ETC transit, reflecting imperfect IPC during transfer; community deaths and routine-HCF deaths still contribute to funeral transmission.
Empirical doubling-time estimation
The doubling time Td reported in §2 is measured directly from each accepted trajectory rather than derived analytically from R₀. For each draw we extract daily new symptomatic onsets in Ituri from the iso75 scenario, build the cumulative series C(t), and fit log-linear by ordinary least squares: log C(t) = a + r · t, then Td = ln 2 / r. The fit window is C(t) ∈ [10, 1000], truncated at 14 May 2026 (the last day before the isolation ramp begins).
Limitations and Assumptions
Ascertainment assumption.
The Stage-2 evidence filter allows ascertainment as low as 20 % for the laboratory-confirmed Ituri count at the 13 June 2026 snapshot. The sensitivity table above shows that medians are stable when the ascertainment rate is relaxed to 15 % or 10 %, but the upper credible-interval bounds move modestly with the ascertainment rate.
Calibration targets.
Stage 1 uses only evidence of importations from Ituri → Uganda importations (exact-count, no tolerance band); within-Ituri incidence is not directly fit in Stage 1. Stage 2 adds a single cumulative count at one date. Alternative acceptance rules or additional within-basin time-points would shift the posteriors.
Care-pathway parameters.
Isolation-track timings (Tiso = 2 d, HCF → ETC ≈ 3 d) follow the 2018 North Kivu RVEAP response, which may not exactly match the 2026 operational reality. The residual nosocomial channel in the iso branch (0.1 · βH) is a modelling assumption, sensitivity-testable.
Scope.
All figures and statistics in this report are for the Ituri Province only. Cross-basin spillover to North Kivu, Uganda, Rwanda, etc., is not reported here (see Reports #3 and #4 for international dissemination).
Mobility and seasonality.
Mobility is held static across the simulation, with no behavioral reduction, no border closure modeled, and no seasonality in transmissibility. Informal cross-border movement may be under-captured.
Isolation policy.
The isolation ramp (10 percentage points every 2 days from 15 May 2026) and the case-finding timings are applied homogeneously across all symptomatic cases. Real-world coverage varies by location and over time.
6 — References
References
1World Health Organization Regional Office for Africa. Ebola Bundibugyo Virus Disease Outbreak — Democratic Republic of the Congo | Uganda. Weekly External Situation Report. Available at: https://insp.cd/category/sitrep/
2Institut National de Santé Publique, République Démocratique du Congo. Situation reports, Maladie à Virus Bundibugyo. Available at: https://insp.cd/category/sitrep/
5Balcan 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.
6Ajelli M, Merler S, Fumanelli L, Pastore y Piontti A, 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.
7Legrand J, Grais RF, Boelle PY, Valleron AJ, Flahault A. Understanding the dynamics of Ebola epidemics. Epidemiology and Infection. 2007;135(4):610–621.
8Gomes 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.
9Wamala 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.
Epistorm · Northeastern University / CFA–CDC Insight Net
On 16 May 2026 the WHO Director-General declared a Public Health Emergency of International Concern for the outbreak of Ebola disease caused by Bundibugyo virus in DRC and Uganda. As of 21 June 2026 DRC has reported 1,048 laboratory-confirmed cases and 267 confirmed deaths (case-fatality ratio ≈ 25 %) across 34 health zones, with 371 patients hospitalised in isolation. We present a stochastic, metapopulation transmission model built using the GLEAM framework, which incorporates transmission in the hospital, the community and through funerals, and which explicitly models isolation protocols through Ebola treatment centres (ETC). The model is calibrated by Approximate Bayesian Computation in two stages, on observed cross-border importations from Ituri to Uganda, and on the cumulative laboratory-confirmed count in Ituri at 13 June 2026, allowing ascertainment as low as 20 %. The accepted posterior yields R₀ = 2.34 (90 % CrI [1.83, 3.08]) and an empirical doubling time of 10.6 d (90 % CrI [8.5, 13.5]). Forward projections in Ituri at 24 June 2026 under 75 % isolation give median cumulative cases of 2,509 (90 % CrI [1,053, 4,688]). Under three isolation scenarios (50 %, 75 %, 95 %) phased in from 15 May 2026, the probability of ≥ 20,000 cumulative cases in Ituri by 31 August 2026 is 45 %, 3 % and 0 % respectively. Strong isolation drives the outbreak to extinction by end of August, while a slip to 50 % leaves it uncontrolled.
1 Background
On 16 May 2026 the WHO Director-General declared a Public Health Emergency of International Concern (PHEIC) under the International Health Regulations (2005) for the outbreak of Ebola disease caused by Bundibugyo virus (BVD) in the Democratic Republic of the Congo and Uganda. As of the 21 June 2026 snapshot used in this report, DRC has reported 1,048 laboratory-confirmed cases and 267 confirmed deaths (case-fatality ratio ≈ 25 %) across 34 health zones spanning Ituri, North Kivu and South Kivu, with 371 patients hospitalised in isolation at Ebola treatment centre (ETC) and treatment facilities. Uganda has reported 20 laboratory-confirmed cases including 2 deaths.
The outbreak originated in Ituri (Ituri Province, DRC) and has produced two attributed cross-border importations to Uganda by mid-May. Local isolation interventions are being rolled out across the affected basins. This report estimates the posterior burden of the outbreak in Ituri and projects forward trajectories under three counterfactual isolation scenarios, conditioning on the observed importation pattern and on the cumulative laboratory-confirmed case count at 13 June 2026.
All figures and statistics in this report are restricted to the Ituri Province. Cross-basin spillover and international dissemination are addressed in Reports #3 and #4.
2 Results
2.1 Posterior of R₀ and the doubling time
The accepted posterior over the 950 trajectories that pass the two-stage calibration yields a median basic reproduction number R₀ of 2.34 (90 % CrI [1.83, 3.08]) and a median empirical doubling time of 10.6 d (90 % CrI [8.5, 13.5 d]).
Figure 1. Filtered posterior over the 950 accepted trajectories. R₀ posterior (left) and empirical doubling-time posterior (right). KDE on linear axes (Gaussian kernel, Scott bandwidth); dashed line marks the median; shaded band the 90 % credible interval; dots below the baseline show a 250-trajectory subsample.
2.2 Cumulative cases in Ituri at 24 May 2026
As a reference snapshot of the posterior before the projection horizon, the filtered posterior predictive distribution of cumulative symptomatic cases in Ituri on 24 May 2026 has a median of 757 and a 90 % credible interval of [378, 1,298].
Figure 2. Filtered posterior predictive distribution of cumulative symptomatic cases in Ituri on 24 May 2026 (n = 950).
2.3 Forward projection at 24 June 2026
The filtered posterior predictive distributions in Ituri at the projection date 24 June 2026, eleven days after the evidence-filter date and six weeks into the 75 % isolation ramp, give median cumulative symptomatic cases of 2,509 (90 % CrI [1,053, 4,688]), active cases (community + HCF + ETC) of 541 (90 % CrI [189, 1,260]) and new symptomatic cases per day of 52 (90 % CrI [15, 137]). The cumulative outbreak continues to grow modestly (≈ 30 % over the eleven days following the filter date), while active cases are roughly flat and daily incidence is gently declining.
Figure 3. Filtered posterior predictive distributions in Ituri on 24 June 2026 under 75 % target isolation: cumulative symptomatic cases (top, navy), active cases (middle, red), and new symptomatic cases per day (bottom, teal). Shared log x-axis. n = 950.
2.4 Scenario projections through 31 August 2026
Forward projections evaluate three target isolation rates (50 %, 75 % and 95 %), each phased in at 10 percentage points every 2 days from 15 May 2026. The probability that cumulative symptomatic cases in Ituri exceed 10,000 by 31 August 2026 is 70 % under 50 % isolation, 21 % under 75 % and 0 % under 95 %. For the higher threshold of ≥ 20,000 cases, the corresponding probabilities are 45 %, 3 % and 0 %.
Figure 4. Probability that cumulative symptomatic cases in Ituri exceed 10,000 (left) and 20,000 (right) by 31 August 2026, by target isolation rate. n = 950 per scenario.
As a complementary measure of controllability, we compute the probability that daily new symptomatic onsets in Ituri exceed 10 cases on 31 August 2026 (the end of the simulation window). Under 50 % isolation the probability is essentially certain (100 %). Under 75 % isolation it is 78 %, indicating that the outbreak is bounded in cumulative size but sustained low-level transmission persists. Only under 95 % isolation does the probability drop substantially, to 5 %, indicating that the outbreak is driven to extinction by end-August in nearly all trajectories.
Figure 5. Probability that daily new symptomatic onsets in Ituri exceed 10 on 31 August 2026, by target isolation rate. n = 950 per scenario.
3 Methods
3.1 Model framework
The framework is GLEAM (Global Epidemic and Mobility Model) [5], an Africa-wide metapopulation network coupled by daily commuting matrices and origin-destination passenger flows from IATA Passenger Intelligence Services and OAG Aviation Analytics. The within-basin compartmental dynamics are simulated as a discrete-time multinomial chain-binomial process. At each time step the number of individuals exiting a compartment is drawn from a binomial with exit probability 1 − exp(−Σᵢ λᵢ · Δt), and exits are partitioned across the available destination compartments by a multinomial whose probabilities are proportional to the per-route hazards. We do not assume any mobility reductions between subpopulations: no behavioral reduction, no border closure is explicitly modeled.
3.2 Compartmental structure
The compartmental structure follows a Legrand-like SEIHFR scheme [7,8]. To model the impact of isolation and safe burial protocols, we incorporate three potential outcomes an infectious individual could experience (Figure 6):
Community Branch: the individual does not get admitted to any healthcare facility. They infect people in the community in their infectious stage and, if death occurs, through unsafe burial practices.
HCF-only Branch: the individual is infectious for an average of 5 days until admission to a HCF, where they can generate new infections through nosocomial transmission and, if death occurs, through unsafe burial practices.
Isolation Branch: the individual is infectious for an average of 2 days before being moved to a HCF for 3 days with transmissibility 10 % of the HCF-only branch, and is then moved to an ETC where they no longer contribute to ongoing transmission.
The funeral compartment F is fed only by community deaths and regular-HCF deaths (deaths in ETC receive safe and dignified burial and bypass F). Transmission rates by compartment: βI in all three community-infectious compartments (Icom, IcomH, Iiso), βH in regular-track H, βH,iso = 0.1 · βH in the HCF → ETC transit compartment HETC, zero in ETC, and βF in F.
Figure 6. Compartmental structure of the model. Twelve compartments, three potential outcomes at E₂ exit. Latent stages E₁ → E₂ feed three parallel infectious-community sub-compartments. Routine cases progress to H (βH); isolated cases progress through HETC (0.1 · βH) to ETC (no transmission, safe burial). F (βF) is fed only by community and regular-HCF deaths.
3.3 Natural-history parameters
Compartmental dwell times and severity values are based on literature. The Legrand-type SEIHFR formulation [7,8] supplies the framework, Wamala et al. [9] are the source for the original 2007–2008 Uganda BVD outbreak data on which some of the BVD-specific natural-history estimates rest. Isolation-pathway case-finding timings (Tiso and The) follow the 2018 North Kivu RVEAP response [6].
Symbol
Meaning
Value
Source
TE
Latent period (Erlang-2 mean)
8 d (prior U(5, 10))
[8, 9]
TI
Icom dwell (community, no HCF)
9.6 d
[7, 8]
Tsh
Onset to HCF admission, routine track
5 d
[8]
Tiso
Onset to HCF admission, iso track
2 d
[6]
The
HCF to ETC transit, iso track
3 d
[6]
TH
HCF stay, routine track
4.6 d
[7, 8]
TETC
ETC stay
4.6 d
assumed = TH
TF
Funeral period
2 d
[7, 8]
pH
HCF admission probability (Legrand baseline)
0.80
[8, 9]
δnh
CFR, non-hospitalised
0.50
supportive-care gradient
δh
CFR, regular HCF
0.45
supportive-care gradient
δetc
CFR, ETC
0.30
best clinical management
R0 split
Community : HCF : Funeral at baseline
0.44 : 0.22 : 0.34
[8]
κiso
HCF iso transmission factor (βH,iso/βH)
0.1
assumed (residual nosocomial)
3.4 Seeding
The epidemic originates in Ituri, DRC, with 5 infectious cases on the inferred start date. Every other basin (including all of Uganda) begins fully susceptible and is reached only through mobility coupling.
3.5 Two-stage calibration
The model is calibrated by Approximate Bayesian Computation in two stages. Stage 1 conditions on observed cross-border importations from Ituri to Uganda, requiring exactly one Uganda importation by 14 May 2026 and exactly one further importation in the window 14 to 18 May 2026. Stage 2 conditions the Stage-1 posterior on the cumulative laboratory-confirmed count in Ituri at 13 June 2026 (717 cases) allowing ascertainment as low as 20 %, requiring the simulated cumulative symptomatic onsets in Ituri by 13 June to lie in the window [717, 3,585].
Parameter
Prior
Notes
R0
U(1.2, 5.0)
Basic reproduction number
Incubation period TE
U(5, 10) d
Erlang-2 (two-stage latent)
Outbreak start date
U(15 Feb, 15 Mar 2026)
Date of first case in Ituri
3.6 Ascertainment sensitivity
The baseline analysis allows ascertainment as low as 20 % (window [717, 3,585]). If we instead allow ascertainment as low as 15 % ([717, 4,780]) or 10 % ([717, 7,170]), the accepted posterior changes only modestly. Posterior medians are stable across the three floors; the upper credible-interval bounds tighten progressively as the floor rises.
Min ascertainment
n accepted
R0 (med · 90 % CrI)
Td (med · 90 % CrI)
10 % (≤ 7,170)
1,322
2.43 · [1.85, 3.26]
10.3 d · [8.1, 13.4]
15 % (≤ 4,780)
1,141
2.43 · [1.85, 3.26]
10.3 d · [8.1, 13.4]
20 % (≤ 3,585), baseline
950
2.34 · [1.83, 3.08]
10.6 d · [8.5, 13.5]
3.7 Isolation mechanism
Forward projections evaluate three target isolation rates, 50 %, 75 % and 95 %, each phased in at 10 percentage points every 2 days from 15 May 2026 in the Ituri Province until the scenario target is reached. We assume a similar ramp up of isolation in North and South Kivu but with a starting date that is a week later (May 22). The isolation Q determines the probability with which each new symptomatic case is routed to the isolation pathway (Iiso → HETC → ETC). Isolation-tracked cases are identified faster than routine cases (onset-to-HCF 2 d versus 5 d on the routine track) and progress to the ETC compartment, where transmission stops and any deaths receive safe and dignified burial. A small residual nosocomial channel (10 % of the baseline HCF rate) is retained during the 3-day HCF → ETC transit, reflecting imperfect IPC during transfer; community deaths and routine-HCF deaths still contribute to funeral transmission.
3.8 Empirical doubling-time estimation
The doubling time Td is measured directly from each accepted trajectory rather than derived analytically from R₀. For each draw we extract daily new symptomatic onsets in Ituri from the iso75 scenario, build the cumulative series C(t), and fit log-linear by ordinary least squares: log C(t) = a + r · t, then Td = ln 2 / r. The fit window is C(t) ∈ [10, 1000], truncated at 14 May 2026 (the last day before the isolation ramp begins).
3.9 Limitations and assumptions
Ascertainment assumption. The Stage-2 evidence filter allows ascertainment as low as 20 % for the laboratory-confirmed Ituri count at the 13 June 2026 snapshot. The sensitivity table above shows that medians are stable when the ascertainment rate is relaxed to 15 % or 10 %, but the upper credible-interval bounds move modestly with the ascertainment rate. Calibration targets. Stage 1 uses only evidence of importations from Ituri → Uganda importations (exact-count, no tolerance band); within-Ituri incidence is not directly fit in Stage 1. Stage 2 adds a single cumulative count at one date. Alternative acceptance rules or additional within-basin time-points would shift the posteriors. Care-pathway parameters. Isolation-pathway timings follow the 2018 North Kivu RVEAP response, which may not exactly match 2026 operational reality. The residual nosocomial channel in the iso branch (0.1 · βH) is a modelling assumption. Scope. All figures and statistics are for the Ituri Province only. Mobility and seasonality. Mobility is held static across the simulation, with no behavioral reduction, no border closure modeled, and no seasonality. Isolation policy. The isolation ramp and case-finding timings are applied homogeneously across all symptomatic cases; real-world coverage varies.
References
[1] World Health Organization Regional Office for Africa. Ebola Bundibugyo Virus Disease Outbreak, Democratic Republic of the Congo | Uganda. Weekly External Situation Report. https://insp.cd/category/sitrep/
[2] Institut National de Santé Publique, République Démocratique du Congo. Situation reports, Maladie à Virus Bundibugyo. https://insp.cd/category/sitrep/
[3] Ministry of Health, Uganda. Ebola disease, situation updates. https://evd-daily.health.go.ug/
[4] World Health Organization. Disease Outbreak News, Ebola disease caused by Bundibugyo virus, Democratic Republic of the Congo and Uganda (DON 606). https://www.who.int/emergencies/disease-outbreak-news/item/2026-DON606
[5] 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. J Comput Sci. 2010;1(3):132–145.
[6] Ajelli M, Merler S, Fumanelli L, Pastore y Piontti A, 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.
[7] Legrand J, Grais RF, Boelle PY, Valleron AJ, Flahault A. Understanding the dynamics of Ebola epidemics. Epidemiol Infect. 2007;135(4):610–621.
[8] Gomes 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.
[9] Wamala JF, Lukwago L, Malimbo M, et al. Ebola hemorrhagic fever associated with novel virus strain, Uganda, 2007–2008. Emerg Infect Dis. 2010;16(7):1087–1092.
