Surveillance methodology brief, May 23, 2026

Bundibugyo virus, Democratic Republic of the Congo and Uganda, 2026

Latent Outbreak Visibility System (LOVS) applied to the 2026 BDBV outbreak. Ascertainment, detection depth, and pre-committed methodology calibration points, as of May 23, 2026.

Bottom line. Public reporting likely captures 40-46% of laboratory-confirmable cases. This brief quantifies that visibility gap and pre-commits how the method will be judged.

Spatial evidence mapInspect outbreak zones, corridor edges, calibration links, and source-state evidence on the map.Open map
Why this methodology brief matters
As of May 23, 2026, the most prominent public estimate of the outbreak's scale comes from the joint WHO-Imperial College MRC GIDA report (May 20, 2026), which estimates 400-900 total cases in DRC (values over 1,000 not excluded) using population-movement extrapolation and deaths-back-projection through the case-fatality ratio. This brief is built to sit alongside that work and help the teams responding see one more thing clearly: how much of the outbreak public reporting is likely capturing at this snapshot, how that visibility is shifting, and where cross-border movement would most test the standing assumptions. To keep the contribution accountable, it adds a reporting-completeness estimate, a calibration set committed in advance, and a corridor view with date-stamped resolution, so anyone can check it against what actually happens. It is offered in support of that effort, building on the WHO-Imperial estimate rather than replacing it.

Executive overview, May 23, 2026

What sources available for this snapshot show, and what the method estimates beneath it.

Public reporting picture

Confirmed (laboratory)

84[25]

Range across sources: 1084[25][7][9][3][8][14]

Suspected

750[25]

Range across sources: 395750[25][4][2][3][17][14]

Deaths

177[25]

Range across sources: 106177[25][4][2][17][3][8][14]

Confirmed split: 82 in DRC, 2 in Uganda. Healthcare workers among the deaths: 4.

What the method adds

Visible share

40-46%

Estimated share of laboratory-confirmable cases captured by public reporting.

Detection depth

Multiple rounds

Detection occurred after silent transmission generations, intrinsic to early-stage filovirus surveillance.

Corridors

Calibration only

The watchlist tests uncertainty quality. It is not a ranked deployment list.

Supporting detail

Snapshot clocks3
Snapshot
2026-05-23
Analytic cutoff
2026-05-22T23:59:59Z
Headline data as of
2026-05-22
Publication cutoff
2026-05-23

This is a publication-state snapshot: May 23 sources are visible in the evidence trail, while the scored model endpoint remains 2026-05-22.

RoleData as ofPublishedRetrievedStatus
headline_count_endpoint2026-05-222026-05-222026-05-22T16:11:52Zprimary_count_endpoint
corridor_source_load2026-05-212026-05-222026-05-23T18:36:26Zcumulative_health_zone_table_verified
timeline_geography_anchor2026-05-212026-05-212026-05-23T19:21:01Zofficial_count_geography_anchor

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Generated timestamp status: not_recorded.

Reporting notes

Uganda count: 2 confirmed in Kampala (1 death) per WHO PHEIC statement, Africa CDC PHECS declaration, WHO 20 May remarks, WHO 22 May remarks, and WHO IHR Emergency Committee temporary recommendations. WHO reported 82 confirmed cases in DRC as of 22 May. The reported Kinshasa case tested negative on confirmatory INRB testing and is not counted as confirmed. WHO IHR temporary recommendations state that no onward Uganda transmission among contacts of the two confirmed imported cases was documented as of 22 May.[7][2][9][8][25][26][3]

Source-conflict notes6
  • Suspected count spans 395 (Africa CDC PHECS, 18 May 2026) to almost 750 (WHO Director-General Member State briefing, 22 May 2026). CDC Current Situation reports a lower 21 May structured tuple of 575 suspected cases; ECDC's 21 May update carries the WHO-derived approximately-600 suspected cross-check, and the archived 20 May consensus aggregator reports 653. WHO's newer official briefing is the headline endpoint.[2][3][17][14][25]
  • Deaths span 106 (Africa CDC PHECS, 18 May 2026) to 177 suspected deaths (WHO Director-General Member State briefing, 22 May 2026). Earlier anchors remain in the conflict trail: ECDC 130 on 19 May, WHO/ECDC 139 on 20/21 May, the archived 20 May consensus aggregator 144, and CDC 148 on 21 May.[2][9][17][8][3][14][25]
  • Confirmed count spans 10 (WHO PHEIC statement, 17 May 2026, case data as of 16 May: 8 Ituri + 2 Kampala; Kinshasa case deconfirmed) to 84 total country-scope confirmed cases (WHO Director-General Member State briefing, 22 May 2026: 82 DRC + 2 imported Uganda). CDC's 21 May structured tuple is superseded for the headline endpoint but retained as dated conflict evidence.[7][8][14][25]
  • Spatial model source zones use the newest official per-health-zone confirmed-count table in the manifest: the DRC MoH SitRep MVE N 007/MVB_17/2026 PDF cumulative Table IV (data as of 21 May 2026, published 22 May 2026) lists 79 confirmed cases across Bambu, Bunia, Butembo, Goma, Katwa, Kilo, Miti-Murhesa, Mongbwalu, Nizi, Nyankunde, and Rwampara. This table supersedes WHO AFRO SitRep-01 (18 May 2026) as the zone-attributed source. CDC 21 May reports the outbreak in 11 DRC health zones in Ituri and Nord-Kivu as of 20 May. Uganda has 2 confirmed imported cases including 1 death; WHO IHR temporary recommendations state no onward Uganda transmission among contacts was documented as of 22 May.[31][11][8][14][25][26]
  • Per-source archive status: all cited sources are registered in data/bundibugyo-2026/manifest.json. WHO DON 602, WHO PHEIC, WHO DG remarks, WHO IHR temporary recommendations, WHO AFRO landing page, CDC HAN, CDC Current Situation, ECDC May 19/21, and the consensus aggregator are byte-archived with SHA-256 or content-addressed raw bytes; Africa CDC, Imperial, and PAHO/WHO are hash-recorded with restricted raw publisher bytes kept private pending terms or permission confirmation.[1][7][8][25][26][4][5][14][9][17][3][2][6][13][19]
  • May 21 context-only sources are archived separately from count truth. CDC traveler guidance and traveler information, the ECDC threat assessment, the PAHO/WHO epidemiological alert, WHO AFRO regional readiness reporting, and the UK support update inform preparedness and monitoring context; they do not change headline case/death counts unless they publish explicit count or geography evidence.[16][15][18][19][21][20]
Data latency32

Median lag, in days, across 32 archived editions (13 state a current-as-of date).

Publication lag
0d
Archival capture
1.2d
Total visibility
2.2d

The trajectory chart uses the Data as of column as its x-axis when a source states one. Publication and archive capture stay visible here as latency, rather than moving the plotted epidemiologic point forward in time.

SourceData as ofPublication lag (d)Archival lag (d)Total visibility (d)
World Health Organization, Regional Office for Africa2026-05-1803.83.8
World Health Organization, Regional Office for Africa2026-05-1802.92.9
World Health Organization2026-05-2102.82.8
Ministere de la Sante Publique, Hygiene et Prevoyance sociale, Democratic Republic of the Congo2026-05-2111.82.8
US Centers for Disease Control and Prevention2026-05-1911.72.7
European Centre for Disease Prevention and Control2026-05-2010.42.2
European Centre for Disease Prevention and Control2026-05-2011.22.2
US Centers for Disease Control and Prevention2026-05-2201.21.2
European Centre for Disease Prevention and Control2026-05-2201.21.2
US Centers for Disease Control and Prevention2026-05-21011
Wikipedia contributors (consensus aggregator)2026-05-2000.90.9
World Health Organization2026-05-2200.70.7
World Health Organization2026-05-2200.70.7
World Health Organizationn/an/a5.2n/a
World Health Organizationn/an/a3.9n/a
Imperial College London, MRC Centre for Global Infectious Disease Analysis (with WHO HEP/Uganda/AFRO)n/an/a3.8n/a
Imperial College London, MRC Centre for Global Infectious Disease Analysis (with WHO Health Emergencies Programme, WHO Uganda, WHO Regional Office for Africa)n/an/a2.9n/a
Africa Centres for Disease Control and Preventionn/an/a2.9n/a
European Centre for Disease Prevention and Controln/an/a2n/a
US Centers for Disease Control and Prevention, Health Alert Networkn/an/a1.9n/a
Imperial College London, MRC Centre for Global Infectious Disease Analysis (with WHO HEP/Uganda/AFRO)n/an/a1.8n/a
Associated Pressn/an/a1.3n/a
eNCA / AFPn/an/a1.3n/a
International Federation of Red Cross and Red Crescent Societiesn/an/a1.3n/a
US Centers for Disease Control and Preventionn/an/a1.2n/a
US Centers for Disease Control and Preventionn/an/a1.2n/a
Pan American Health Organization / World Health Organizationn/an/a1.2n/a
UK Foreign, Commonwealth & Development Office / UK Health Security Agencyn/an/a1.2n/a
World Health Organization, Regional Office for African/an/a1.2n/a
US Centers for Disease Control and Preventionn/an/a1.2n/a
US Centers for Disease Control and Preventionn/an/a1.2n/a
World Health Organizationn/an/a1n/a

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Publication lag: current-as-of date to publication. Archival lag: publication to capture here. Total visibility lag: their sum. Editions without a stated current-as-of date show n/a.

01

Deep analysis

What the public numbers imply

The overview freezes what public reporting can see. This phase explains the hidden-case band, detection depth, and corridor output without turning any of them into a forecast.

Visible vs inferred burden

Trajectory views

Start with the public time series, then compare it with two latent-quantity views: ascertainment-adjusted laboratory-confirmable cases and deaths-back-projected total cases.

Outbreak trajectoryPublic-reporting counts over time, plotted by the source's data/reporting date. The endpoint is carried in the May 23 snapshot but plotted at May 22 because that is the data date. At the endpoint, the orange bar above the confirmed line shows the method's inferred-underlying range for laboratory-confirmable cases only (not deaths, not suspected) after correcting for the reporting-completeness posterior.
Trajectory of confirmed, suspected, and deaths over time, with the inferred underlying confirmed-case range at the as-of date.Three trend lines (confirmed, suspected, deaths) plotted from May 15 to May 22. At the as-of date, an orange interval bar sits directly above the confirmed-case endpoint of 84, marking the inferred underlying confirmed-case range of 183 to 212, derived from the reporting-completeness posterior.02004006008001,000May 15May 17May 18May 19May 20May 21May 22snap May 2375017741030538584No confirmed-case count reported on 2026-05-18.INFERRED UNDERLYINGLAB-CONFIRMABLE CASES18321250% interval (LOVS)↑ 128+ unobservedCOUNT

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Suspected (case definition)
Deaths
Confirmed (laboratory, PCR)
Inferred underlying confirmable cases (50% range), confirmed-only
Timeline refs.May 15: [1]May 17: [7]May 18: [2]May 19: [9]May 20: confirmed [8], suspected/deaths [3]May 21: confirmed [32], suspected/deaths [32]May 22: confirmed [25], suspected/deaths [25]

How to read.The three lines are the dated public-reporting anchors carried in this snapshot's source trail [1][7][2][9][8][3][32][25][14][4][17]. Official sources are preferred for headline values; the x-axis uses each source's reported data date when available, while later snapshot/capture timing is shown separately in the data-latency table. Where a row mixes publisher cadences, the timeline refs above identify the source used for each metric. Suspected counts use the clinical case definition, deaths are attributed deaths, and confirmed are laboratory-PCR positives. The orange band sits directly above the confirmed-case endpoint and shows the inferred underlying laboratory-confirmable count after correcting only for reporting completeness. The band applies to the confirmed series alone; the method does not model an inferred range on deaths or on suspected counts. The vertical dashed arrow is the ascertainment gap, the implied count of confirmable cases not yet captured in lab data, not a forecast of future spread.

Inferred underlying trajectoryTwo inference bands over the same outbreak timeline. The orange band is the LOVS Module C output: each confirmed-case point divided by the snapshot's reporting-completeness 50% interval (4046%), estimating the true laboratory-confirmable count. The blue-slate band is the deaths back-projection (Imperial Method 2): each reported death count is projected to total cumulative cases as C = D · (1 + r/β)^α / CFR with r = ln(2) / τ₂ at central doubling time τ₂ = 14 d, the BDBV onset-to-death gamma from Rosello et al. 2015 eLife (α = 4.42, β = 0.388/day), and the BDBV case-fatality-ratio 95% CI from US CDC outbreak history (2640%, spanning 55 deaths / 169 cases across the 2007-08 Uganda and 2012 DRC outbreaks). The band's width carries CFR uncertainty only; doubling-time uncertainty is presented separately in the sibling sensitivity grid. When a headline death input has only a publication clock, it is shown as a dashed interval-censored current endpoint rather than a connected dated node. The horizontal markers at 400 and 900 are the joint WHO + Imperial College MRC GIDA, May 20, 2026 total-case estimate (same death-back-projection formula plus a population-movement model), included as an external cross-check. Deaths are the input to the blue-slate back-projection; they are not drawn as a separate band on this chart.
Inferred underlying case trajectory over the snapshot timeline, showing both LOVS confirmable-correction and deaths back-projection bands.Three-series chart over the same outbreak timeline. The lowest line shows publicly-confirmed cases per date. The middle orange band shows the inferred underlying laboratory-confirmable count after correcting for the reporting-completeness 50 percent interval of 40 to 46 percent; at the as-of date this is 183 to 212. The upper blue-slate band shows the inferred total cases from Imperial Method 2 death back-projection at central doubling time 14 days using BDBV case-fatality-ratio priors of 26 to 40 percent; the current snapshot input is 752 to 1158 total cases from 177 deaths. Two horizontal reference ticks at 400 and 900 mark the joint WHO and Imperial College MRC GIDA total-case estimate from May 20, 2026.02004006008001,0001,2001,400May 15May 17May 19May 20May 21May 22WHO + Imperial May 20, 400 totalWHO + Imperial May 20, 900 total841832127521158CASES (CONFIRMABLE AND TOTAL)

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Confirmed cases (laboratory, PCR), public reporting
Inferred underlying confirmable cases (50% interval, LOVS Module C output)
Inferred total cases (Imperial Method 2 deaths back-projection at central doubling time τ₂ = 14 d, CFR 2640% per US CDC BVD outbreak history, 95% CI of 55/169)
Inferred confirmable-cases midline (mean of orange band)
Inferred total-cases midline (mean of blue-slate band)
Imperial College MRC GIDA, 20 May 2026 (400900total cases, >1,000 not excluded)

How to read the two bands. The orange band comes from LOVS Module C: each publicly-confirmed point divided by the reporting-completeness 50% uncertainty interval. It estimates only the laboratory-confirmable count, because the completeness posterior was fit against confirmed cases. The blue-slate band is a different quantity: total cases (clinically compatible, most never lab-confirmed). It applies Imperial Method 2, C = D · (1 + r/β)^α / CFR, with r = ln(2) / 14d, the Rosello 2015 onset-to- death gamma (α = 4.42, β = 0.388/day), and the BDBV CFR 95% CI from US CDC outbreak history (CFR_LOW = 26%, CFR_HIGH = 40%, 55 deaths / 169 cases across the 2007-08 Uganda and 2012 DRC outbreaks); upper-band uses CFR low, lower-band uses CFR high. The (1 + r/β)^α term is the gamma moment-generating function evaluated at the growth rate; it back-corrects the right-censoring bias from infections that will die but have not yet died at the observation date. Naive D / CFR omits this correction and systematically undershoots in a growing epidemic, which is why the band below is wider and higher than a naive ratio would imply. At the as-of date this yields 7521158 total cases from 177 deaths. The dashed horizontal lines at 400 and 900 mark the joint WHO + Imperial College MRC GIDA estimate from May 20, 2026, which uses the same Method 2 formula plus a population-movement model (Uganda export counts vs. observed importations). At the as-of date, the blue-slate band (752 to 1158) brackets and extends above the upper end of the Imperial range (400 to 900). The two methods do not have to agree: Imperial integrates an export-flow signal that pulls the central estimate down, while the band here only uses deaths and CFR at the central doubling time. Both methods agree the true total is several multiples of the 84 publicly confirmed cases. The Imperial "values over 1,000 not excluded" tail tracks with the upper edge of the blue-slate band. Honest caveats: (1) the band carries CFR uncertainty only; the doubling-time uncertainty (τ₂ ∈ {7, 14, 21} days per the Imperial sensitivity set) is presented separately in the sibling sensitivity grid so the two assumptions are not blurred into one width; (2) no BDBV-specific published doubling time exists; the 14-day central scenario is anchored to the 2014 West Africa NEJM range (Guinea 15.7 d, Liberia 23.6 d, Sierra Leone 30.2 d) on the fast side, consistent with Imperial's central choice; (3) the as-of completeness posterior is applied across the whole window for the orange band, assuming approximate stability; (4) both bands are latent-quantity uncertainty, not forecasts of growth.

Doubling-time and CFR sensitivity gridDeterministic sensitivity grid for inferred total cases under paired doubling-time and CFR assumptions, using the same analytical form as Imperial Method 2. Computed for the current snapshot's death count with the Rosello 2015 Isiro 2012 onset-to-death gamma (alpha = 4.42, beta = 0.388 per day). Imperial reported the analogous grid for its own report death input; the grid below recalculates it for the current snapshot. This is a sensitivity analysis, not a fitted posterior.
CFR ↓ / Doubling time →7 days14 days21 days
26%1,8591,158977
33%1,465912769
40%1,208752635

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How to read the grid. Each cell shows the projected cumulative-case estimate on the same denominator scale as the assumed CFR; it is not a laboratory-confirmed count. The calculation uses 177 deaths at that (CFR, doubling-time) pair and the formula total_cases = deaths × (1 + r/β)^α / CFR with r = ln(2) / doubling_time and the Rosello 2015 onset-to-death gamma (α = 4.42, β = 0.388 per day). Faster doubling (left columns) implies more cases per observed death because each endpoint death reflects a case that occurred ~11.4days ago, when the outbreak was smaller; the column corrects for right-censoring in a growing epidemic. Lower CFR (top rows) implies more total cases per observed death because each death indexes proportionally more survivors. The orange tint is a readability aid: darker cells carry larger inferred totals. The grid's spread is the honest range to hold in mind, not a rank ordering of cells by likelihood.

Outbreak geography24 review-set corridors are overlaid on verified WGS-84 zone markers (data/zones.json); country outlines and lakes are Natural Earth 1:10m public-domain geodata. Confirmed-case and spillover-case zones (the latter, Goma, outside the calibration set) in orange, corridor watch points in blue, the imported-case site (Kampala) in green, border-crossing watch points (Mahagi, Arua) in gray-purple, and source-review geographies in amber. Faint blue lines show review-set corridors at or above 10% adjusted 50% upper bound; the 12 pre-committed calibration corridors are dashed orange. Inline percentage chips are suppressed for this dense calibration set; exact registry intervals are in the calibration table below.Open spatial map
BDBV 2026 outbreak geography, real coordinates over Natural Earth 1:10m outlines.Equirectangular projection of the eastern DRC and western Uganda border region (28.5°E-33.2°E, 2.6°S-3.4°N). Country outlines and lakes (Albert, Edward, Kivu, Victoria) are Natural Earth 1:10m public-domain geodata. Markers show 19 georeferenced zones at verified WGS-84 coordinates. The map overlays 24 review-set inter-zone watchlist corridors whose adjusted 50% upper bound is at least 10%; 42 lower-signal corridors remain in the audit list. The 12 pre-committed calibration corridors are highlighted in orange. Source-review geographies are shown only when carried by the active snapshot and are not model inputs. Calibration upper-bound chips are suppressed because the dense set would overlap.29°E30°E31°E32°E33°E2°S1°S0°N1°N2°N3°NLake AlbertLake EdwardLake KivuDRCUGANDAIturi ProvinceNorth Kivu ProvinceSouth Kivu ProvinceWestern RegionRwampara Health Zone to Beni: 50% upper 47.6%Rwampara Health Zone to Kampala: 50% upper 47.3%Rwampara Health Zone to Bundibugyo District: 50% upper 46.6%Rwampara Health Zone to Arua: 50% upper 45.8%Rwampara Health Zone to Kasese District: 50% upper 44.5%Bunia to Kasese District: 50% upper 27.5%Bunia to Kampala: 50% upper 27.2%Bunia to Beni: 50% upper 26.3%Mongbwalu to Kasese District: 50% upper 26.3%Mongbwalu to Nebbi: 50% upper 26.1%Bunia to Arua: 50% upper 26.0%Mongbwalu to Beni: 50% upper 25.2%Mongbwalu: 1.935°N, 30.046°EMongbwaluBunia: 1.562°N, 30.260°EBuniaRwampara Health Zone: 1.578°N, 30.140°ERwampara Health ZoneBambu Health Zone: 1.874°N, 30.220°EBambu Health ZoneNizi Health Zone: 1.780°N, 30.324°ENizi Health ZoneKilo Health Zone: 1.762°N, 30.085°EKilo Health ZoneMahagi: 2.313°N, 30.984°EMahagiArua: 3.020°N, 30.911°EAruaNebbi: 2.479°N, 31.090°ENebbiBeni: 0.491°N, 29.472°EBeniButembo: 0.142°N, 29.291°EButemboKatwa: 0.100°S, 29.317°EKatwaNyankunde: 1.432°N, 30.033°ENyankundeBundibugyo District: 0.710°N, 30.062°EBundibugyo DistrictKasese District: 0.183°N, 30.083°EKasese DistrictKampala: 0.316°N, 32.582°EKampalaKinshasa: 4.322°S, 15.312°EKinshasaGoma: 1.679°S, 29.223°EGomaMiti-Murhesa Health Zone: 2.240°S, 28.812°EMiti-Murhesa Health ZoneConfirmed-case site (Ituri HZ)Corridor target / watch siteImported case (Kampala, 2 confirmed)Border-crossing watch (Mahagi, Arua), not in calibration setSpillover case (Goma), not in calibration setLocal reporting review site, not a model inputCalibration corridor (n=12), values in table belowOther review-set corridors (n=12)

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How to read. Country outlines and lakes are Natural Earth 1:10m public-domain geodata, Douglas-Peucker simplified for inline display (border tolerance 0.025°, lake tolerance 0.01°). Zone markers are placed at verified WGS-84 decimal-degree coordinates from data/zones.json in the source repository; visible labels show names only to keep the dense border cluster readable. The map foregrounds 24 corridors whose adjusted 50% upper bound reaches at least 10%; 42 lower-signal corridors remain in the audit list rather than the map. The 12 pre-committed calibration corridors are highlighted. The corridor lines are watch points, not predictions of where the outbreak will spread, and not recommendations to restrict movement between these zones.

Model-abstracted zones not plotted (2)
  • ituri: Province-level label, not a specific point. The three affected health zones (Mongbwalu, Rwampara, Bunia) sit inside this province. The corridor model treats 'ituri' as a candidate source label; this is a known model artifact (province-level rollup) rather than a verified third source zone.
  • bundibugyo: The pipeline emits 'bundibugyo' as both a DRC source zone and a Uganda target ('bundibugyo-uga'). The target form is a real Ugandan district (Bundibugyo District). The source form has NO verified DRC referent: BDBV is the virus name, and Bundibugyo District is in Uganda not DRC. This is a model-attribution error that we surface honestly rather than hide. Excluded from the projected map.

Analysis step 1

Ascertainment gap is wide and quantifiable

The first question is not whether the public count is wrong; it is how much of the underlying outbreak the public count can plausibly see.

Reporting completeness

39.7% to 45.8%

50% uncertainty range for the share of underlying laboratory-confirmable cases reflected in public counts.

Drivers

Delay + context

Reporting delay, historical late Bundibugyo detection, insecurity, displacement, malaria, and other febrile, gastrointestinal, arboviral, or influenza-like illnesses all widen the visible-to-underlying gap.

Interpretation

Structural

The gap is an early-outbreak reporting feature, not a critique of the national response.

The May 23 parameter audit identifies Rosello 2015 eLife [Rosello 2015] as the BDBV-specific onset-to-notification default, while retaining Camacho 2015 PLOS Currents [Camacho 2015] as the EBOV-Zaire sensitivity comparator. This visibility interval is from that Rosello-default rerun. Bundibugyo detection history is anchored to Wamala 2010 Emerging Infectious Diseases [Wamala 2010]; the Ituri operating context is described with ACLED conflict context [ACLED] and concurrent diagnostic confounders.

Reporting completeness, 50% interval
Reporting completeness 50% interval: 39.7% to 45.8%.0%25%50%75%100%39.7%45.8%

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Analysis step 2

Detection occurred after multiple silent transmission rounds

The second question is timing: how much person-to-person spread likely occurred before the outbreak was visible in public reporting.

At least 3 generations

essentially 100%

Posterior mass that three or more person-to-person transmission rounds preceded public visibility.

Censored upper bin

95%

Mass at at least 6 generations, the simulator's capped upper bin.

Chart drivers

Count + priors

This posterior uses the confirmed-case count, an interim R prior, and an under-ascertainment prior. Wamala 2010 [Wamala 2010] and MacNeil 2010 [MacNeil 2010] inform timing context, not the numeric bins.
Posterior over transmission generations before detectionP(≥ 3 silent generations) = 100%. Most of that mass sits at the censored upper bin (≥ 6 generations): 95%. The branching-process simulator caps at 6 generations by construction, so the upper bin should be read as a lower bound on detection depth, not a precise count.
Posterior probability over number of transmission generations before detection, bins 1 through 6.0%25%50%75%100%1gen2gen3gen1.1%4gen3.6%5gen95%≥ 66+ gensPOSTERIOR PROBABILITYGENERATIONS BEFORE DETECTION

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Point bin (exactly N generations)
Censored upper bin (N or more generations)

Analysis step 3

Corridor watch list is descriptive, not a ranking

The corridor output is useful because it is pre-committed and inspectable. It is not yet useful as a ranked deployment list.

Corridors tested

66

Inter-zone corridors at a 30-day horizon.

Upper-bound cluster

1.8%-47.6%

Ascertainment-adjusted 50% uncertainty upper bounds cluster tightly; lower bounds span 0.6%-20.8%.

Reader takeaway

No ranking yet

The clustering is the signal: the method does not yet discriminate corridors above chance.
Corridor watchlist24 review-set corridors at a 30-day horizon, with an ascertainment-adjusted 50% upper bound of at least 10%. 42 lower-signal corridors are collapsed below so the first read stays focused on epidemiologically interpretable signal.
Corridor watchlist with ascertainment-adjusted 50% intervals.Horizontal interval bars for 66 corridors. Each bar shows the method's 50% uncertainty range for the binary outcome of at least one new laboratory-confirmed case appearing in the target zone within the horizon, given continued reporting in the source zone.SOURCE → TARGETASCERTAINMENT-ADJUSTED 50% INTERVALUPPER0%25%50%75%100%rwamparabeni-cod47.6%rwamparanebbi-uga47.5%rwamparakampala-uga47.3%rwamparabundibugyo-uga46.6%rwamparaarua-uga45.8%rwamparakasese-uga44.5%buniakasese-uga27.5%buniakampala-uga27.2%bunianebbi-uga26.7%buniabeni-cod26.3%mongbwalukasese-uga26.3%mongbwalunebbi-uga26.1%buniabundibugyo-uga26.1%buniaarua-uga26.0%mongbwalubeni-cod25.2%mongbwalukampala-uga25.1%mongbwaluarua-uga24.4%mongbwalubundibugyo-uga24.3%nyankundenebbi-uga21.1%nyankundearua-uga20.1%nyankundekampala-uga20.0%nyankundebeni-cod20.0%nyankundebundibugyo-uga19.5%nyankundekasese-uga19.2%Range across all 66 upper bounds: 1.8% to 47.6% (lower bounds: 0.6% to 20.8%)

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Pre-committed calibration corridor
Descriptive watch point
42 background corridors below 10% upper bound
  • katwa -> kasese-uga 1.4%-4.2%
  • katwa -> nebbi-uga 1.3%-4.1%
  • katwa -> kampala-uga 1.7%-4.1%
  • katwa -> bundibugyo-uga 1.4%-3.9%
  • katwa -> beni-cod 1.4%-3.9%
  • katwa -> arua-uga 1.4%-3.8%
  • goma-cod -> nebbi-uga 0.7%-2.2%
  • butembo -> bundibugyo-uga 0.8%-2.2%
  • nizi -> nebbi-uga 0.8%-2.2%
  • nizi -> bundibugyo-uga 0.8%-2.1%
  • nizi -> kasese-uga 0.7%-2.1%
  • bambu -> beni-cod 0.7%-2.1%
  • nizi -> arua-uga 0.7%-2.1%
  • goma-cod -> bundibugyo-uga 0.7%-2.1%
  • bambu -> bundibugyo-uga 0.8%-2.1%
  • bambu -> arua-uga 0.7%-2.1%
  • goma-cod -> arua-uga 0.7%-2.1%
  • bambu -> kasese-uga 0.7%-2.1%
  • miti-murhesa -> kampala-uga 0.7%-2.1%
  • kilo -> nebbi-uga 0.8%-2.1%
  • kilo -> kampala-uga 0.8%-2.1%
  • kilo -> arua-uga 0.7%-2.0%
  • butembo -> arua-uga 0.7%-2.0%
  • butembo -> kampala-uga 0.7%-2.0%
  • bambu -> kampala-uga 0.7%-2.0%
  • miti-murhesa -> nebbi-uga 0.7%-2.0%
  • miti-murhesa -> beni-cod 0.8%-2.0%
  • bambu -> nebbi-uga 0.7%-2.0%
  • kilo -> kasese-uga 0.7%-2.0%
  • goma-cod -> kasese-uga 0.7%-2.0%
  • butembo -> nebbi-uga 0.7%-2.0%
  • butembo -> kasese-uga 0.8%-2.0%
  • goma-cod -> beni-cod 0.7%-2.0%
  • miti-murhesa -> arua-uga 0.7%-2.0%
  • miti-murhesa -> kasese-uga 0.8%-2.0%
  • miti-murhesa -> bundibugyo-uga 0.7%-1.9%
  • goma-cod -> kampala-uga 0.6%-1.9%
  • butembo -> beni-cod 0.7%-1.9%
  • nizi -> kampala-uga 0.7%-1.9%
  • kilo -> beni-cod 0.7%-1.8%
  • nizi -> beni-cod 0.7%-1.8%
  • kilo -> bundibugyo-uga 0.7%-1.8%

How to read. Each bar is the method's 50% uncertainty range for the binary outcome "at least one new laboratory-confirmed case appears in the target zone within 30 days, given continued reporting in the source zone." The tight clustering of upper bounds across the review set is the headline signal: the method has enough structure to identify a surveillance review set, but not enough to rank corridors as deployment priorities. Corridors below 10% are retained for auditability rather than foregrounded.

Corridor watchlist (map view)This map foregrounds 24 georeferenced review-set corridors with an ascertainment-adjusted 50% upper bound of at least 10%: 12 pre-committed calibration corridors in dashed orange, plus 12 descriptive watchlist corridors in blue. The 42 lower-signal mapped corridors stay in the interval chart audit list rather than cluttering the default geography view. This snapshot has 12 calibration corridors, so inline percentage chips are suppressed to keep the map legible; exact registry intervals are in the calibration table below. The descriptive corridors are intentionally not given inline percentage chips; their numeric ordering lives in the bar chart above.Open spatial map
Georeferenced corridor watchlist drawn over Natural Earth outlines.Equirectangular projection of the eastern DRC and western Uganda border region. The map draws 24 review-set corridors with verified coordinates as source-to-target centroid lines: 12 pre-committed calibration corridors and 12 descriptive watchlist corridors. Line weight scales with the watchlist-row ascertainment-adjusted 50% upper bound, range 19.2% to 47.6%. 42 mapped lower-signal corridors below 10% are omitted from this default map view and retained in the interval chart audit list. Calibration percentage chips are suppressed because the dense calibration set would otherwise overlap. 0 corridors are omitted because at least one endpoint lacks verified coordinates.29°E30°E31°E32°E33°E2°S1°S0°N1°N2°N3°NLake AlbertLake EdwardLake KivuDRCUGANDARwampara Health Zone to Beni: registry 50% upper 51.8%Rwampara Health Zone to Kampala: registry 50% upper 51.5%Rwampara Health Zone to Bundibugyo District: registry 50% upper 52.3%Rwampara Health Zone to Arua: registry 50% upper 49.4%Rwampara Health Zone to Kasese District: registry 50% upper 51.5%Bunia to Kasese District: registry 50% upper 55.3%Bunia to Kampala: registry 50% upper 52.3%Bunia to Beni: registry 50% upper 52.5%Mongbwalu to Kasese District: registry 50% upper 51.9%Mongbwalu to Nebbi: registry 50% upper 51.0%Bunia to Arua: registry 50% upper 52.0%Mongbwalu to Beni: registry 50% upper 52.2%MongbwaluBuniaRwampara HZAruaNebbiBeniNyankundeBundibugyo DistrictKasese DistrictKampalaCalibration corridors (12/12), values in table belowOther review-set corridors (12)Source zone (Ituri HZ)Corridor target (DRC + Uganda)Line weight ∝ ascertainment-adjusted 50% upper bound

Scroll horizontally to inspect the full figure.

How to read. Each line is one review-set corridor from the watchlist bar chart, drawn from source-zone centroid (orange dot) to target-zone centroid (blue dot) at WGS-84 decimal-degree coordinates from data/zones.json. Wider lines indicate higher watchlist-row upper bounds. The 12 mapped pre-committed calibration corridors are dashed orange; the other mapped corridors are descriptive blue. Background corridors below 10% stay in the interval chart audit list. All review-set corridors in the bar chart are georeferenced and shown here. The cluster of mapped upper bounds within the 19%48% band shows what the bar chart says numerically: the method does not yet discriminate corridors above chance.

On Goma. Goma is a major commercial hub in North Kivu, roughly 700 km south of the outbreak core in Bunia. It already shows one laboratory-confirmed BDBV case, a traveler infected in Ituri, so it is rendered as a spillover-case site on the Outbreak geography map above. The most parsimonious epidemiological reading of that case is one of two: the virus traveled directly from the outbreak core via Goma's commercial air or lake links, or community transmission has gone undetected along the Bunia, Beni, Bundibugyo, Kasese corridor. Either reading raises surveillance priority for those intermediate zones. Goma is not in this snapshot's pre-committed corridor calibration set, because each snapshot freezes its calibration zones at build time and the 20 May snapshot was pinned without a Goma corridor. Goma should only join a later snapshot as a candidate calibration zone if that snapshot pins its own scoring contract before outcome assessment.

02

Calibration thread

How the method will be judged

The next pieces separate live outbreak interpretation from method evaluation: pre-committed June resolution blocks, then a retrospective backtest that says what the method is already good and bad at.

Forward scorecard

Calibration blocks carried by the May 22, 2026 snapshot

This snapshot carries 2 earlier calibration blocks unchanged. No new calibration block is pinned by this snapshot; future snapshots can append their own blocks with their own pin date, horizon, and resolution clock.

Snapshot as-of

May 22, 2026

This page is a new snapshot; carried blocks are not re-pinned.

Active blocks

2 blocks

12 points; 0 blocks pinned in this snapshot.

Next scoring clock

28 days

2 days elapsed since pin; 28 days remain.
Pre-commitment timeline
Three-event timeline from outbreak declaration to calibration resolution.May 15, 2026Outbreak declaredDRC MoPHHSW / WHO DON 602May 21, 2026Calibration blocks pre-committed12 corridors across 2 blocks (May 20, 2026-May 21, 2026)Jun 20, 2026Resolution windowJun 19, 2026-Jun 20, 2026

Scroll horizontally to inspect the full figure.

PointCorridorBlock / designRegistry intervalStatement
Point 1Bunia -> Kampala2026-05-20[22.9% to 52.3%]30d from 2026-05-20
Details

At least one new laboratory-confirmed BDBV case appears in Kampala (Uganda) between 20 May 2026 and 19 June 2026, given continued reporting from Bunia Health Zone (Ituri Province, DRC).

Point 2Rwampara -> Bundibugyo2026-05-20[22.7% to 52.3%]30d from 2026-05-20
Details

At least one new laboratory-confirmed BDBV case appears in Bundibugyo District (Uganda) between 20 May 2026 and 19 June 2026, given continued reporting from Rwampara Health Zone (Ituri Province, DRC).

Point 3Mongbwalu -> Beni2026-05-20[21.8% to 52.2%]30d from 2026-05-20
Details

At least one new laboratory-confirmed BDBV case appears in Beni Health Zone (North Kivu Province, DRC) between 20 May 2026 and 19 June 2026, given continued reporting from Mongbwalu Health Zone (Ituri Province, DRC).

Point 4Rwampara -> Kasese2026-05-20[20.9% to 51.5%]30d from 2026-05-20
Details

At least one new laboratory-confirmed BDBV case appears in Kasese District (Uganda) between 20 May 2026 and 19 June 2026, given continued reporting from Rwampara Health Zone (Ituri Province, DRC).

Point 5Bunia -> Kasese2026-05-21designed[22.0% to 55.3%]30d from 2026-05-21
Details

Calibration point for corridor bunia -> kasese-uga.

relative-high cross-border watch corridor / relative high / cross border / watchlist high

Point 6Bunia -> Beni2026-05-21designed[24.3% to 52.5%]30d from 2026-05-21
Details

Calibration point for corridor bunia -> beni-cod.

relative-high in-country likely-positive control / relative high / in country / likely positive

Point 7Rwampara -> Kampala2026-05-21designed[21.8% to 51.5%]30d from 2026-05-21
Details

Calibration point for corridor rwampara -> kampala-uga.

mid-band cross-border imported-case positive control / relative mid / cross border / likely positive

Point 8Mongbwalu -> Kasese2026-05-21designed[23.6% to 51.9%]30d from 2026-05-21
Details

At least one new laboratory-confirmed BDBV case appears in Kasese District (Uganda) between 20 May 2026 and 19 June 2026, given continued reporting from Mongbwalu Health Zone (Ituri Province, DRC).

mid-band cross-border watch corridor / relative mid / cross border / watchlist mid

Point 9Rwampara -> Beni2026-05-21designed[23.6% to 51.8%]30d from 2026-05-21
Details

Calibration point for corridor rwampara -> beni-cod.

mid-band in-country likely-positive control / relative mid / in country / likely positive

Point 10Bunia -> Arua2026-05-21designed[23.6% to 52.0%]30d from 2026-05-21
Details

Calibration point for corridor bunia -> arua-uga.

mid-band cross-border blindspot watch corridor / relative mid / cross border / blindspot watch

Point 11Rwampara -> Arua2026-05-21designed[22.1% to 49.4%]30d from 2026-05-21
Details

Calibration point for corridor rwampara -> arua-uga.

relative-low cross-border likely-negative control / relative low / cross border / likely negative

Point 12Mongbwalu -> Nebbi2026-05-21designed[22.2% to 51.0%]30d from 2026-05-21
Details

Calibration point for corridor mongbwalu -> nebbi-uga.

relative-low cross-border likely-negative control / relative low / cross border / likely negative

Scroll horizontally to inspect the full figure.

Retrospective scorecard

Historical calibration on the 2014 West Africa Ebola epidemic

The method has been tested against a known historical outbreak before being used as a live calibration artifact here.

Uncertainty quality

35% tighter

Country-level context improves interval score from 0.1002 to 0.0649.

Discrimination

Still chance-level

Local context does not yet separate individual corridors above chance in this backtest.

Transfer caveat

Zaire -> BDBV

The 2014 substrate is a Zaire-species outbreak; species-transfer uncertainty remains unquantified here.

The retrospective substrate is Backer and Wallinga 2016 [Backer 2016]: 62 prefectures across 74 weeks. The five evaluation checkpoints are historical West Africa backtest weeks W3, W5, W7, W9, and W11, not the live BDBV case count. The current-outbreak sections use the snapshot's reconciled confirmed count separately from this historical backtest. Three runs are reported below: without local context, with country-level local context, and with district-level local context.

MetricNo local contextCountry-levelDistrict-level
Brier score, probability accuracy, lower is better0.05860.05900.0590
Interval score, Bracher 2021, uncertainty quality, lower is better0.10020.06490.0649
Calibration error, predicted vs observed frequency, lower is better0.03910.05000.0500

Scroll horizontally to inspect the full figure.

03

Use with care

What should change the weight you give the outputs

These sections make the blindspots visible before asking for better field inputs. The intent is not to hide uncertainty, but to show exactly which data would most improve the method.

Known caveats

Known blindspots and calibration-design notes

These are the caveats that should change how much weight a reader gives each output. The highest-impact gap is separated from secondary caveats so the audit story is easier to scan.

Source-zone validation

Still open

The May 22 official WHO sources and the DRC MoH per-zone table (SitRep MVE N 007/MVB_17/2026 Table IV) were rechecked against the blindspot list. Bambu, Kilo, Miti-Murhesa, and Nizi enter the source-zone footprint alongside the previously attributed zones; Arua and Nebbi remain target-side watch endpoints; Mahagi is still not promoted to a source zone because no DRC MoH, WHO, or Africa CDC source names Mahagi health zone as case-affected.

Calibration design

Narrow band

The May 21 block improves relative coverage across high/mid/low ranks and control roles, but the aggregate-input model still does not produce a clean 5-20% absolute low-risk band.

Attribution

Beni confounding

North Kivu is already part of the reported outbreak footprint. A positive mongbwalu -> beni-cod resolution may reflect Beni already being active, not a clean source-to-target transmission event.

Context input

Qualitative conflict

CODECO and ADF activity plus eastern DRC displacement are used as descriptive context, but the per-zone conflict input still comes from the 2014 West Africa ACLED backtest. A 2026 eastern DRC ACLED snapshot is a documented next lever.

Reporting-delay prior

Single prior outbreak

The May 23 parameter audit adopts the Rosello 2015 BDBV Isiro 2012 onset-to-notification distribution as the species-matched reporting-delay default, but it is a small single prior outbreak (n=52) and is graded as historical, not a fitted 2026 estimate. Camacho 2015 EBOV-Zaire is retained as a faster-reporting sensitivity comparator.

These blindspots are surfaced so a responder can adjust how much weight to give each output. They are tracked in the source repository's commit history; updates will land in subsequent snapshots.

Contribution path

If you have point-of-care data

Publicly aggregated reporting can only take the method so far. The inputs below are the highest-leverage ways to sharpen it without moving sensitive data into public view.

This brief reports method estimates from publicly aggregated reporting only. Responders in the affected zones may hold data that can sharpen the method, but those data are likely privileged, time-sensitive, and not appropriate for a public repository.

  • Onset-date extract

    A partial onset-date histogram for one health zone narrows the latent-active-chains plausibility interval. A two-column CSV with anonymous row ID and onset date is enough.

  • Zone-attributed counts

    A {health-zone-id: confirmed_count} mapping for affected districts is the largest single discrimination lever the method is missing.

  • Validated centroids

    For zones the snapshot may have missed, a GPS centroid plus one-sentence rationale is enough to extend the corridor model and geography visual.

  • Mobility or transport flow

    Admin-2 call-detail-record summaries or surveyed transport flows are the documented next lever for corridor-spread discrimination.

  • Confirmation latency

    Observed sample-to-PCR-result delays, in days, directly update the reporting-completeness prior.

Public issues are welcome for methodology. For sensitive data, coordinate a secure handoff first; contributions that land in the repository are cited and timestamped.

Email Frans
04

Audit trail

Limits, external cross-checks, and source trail

The final phase collects the hard boundaries of the brief, how LOVS uses the Imperial estimate, and the references needed to inspect the evidence chain.

May 23 methods audit

Parameter provenance and sensitivity

A source-chain pass aligned the BDBV parameter library with WHO grEPI. This section shows which inputs are now consumed in the live run, which remain sensitivity comparators, and where residual uncertainty still sits.

Reporting-delay default

8.83 d

Rosello et al. 2015 Table 5 reports a BDBV Isiro 2012 onset-to-notification mean of 8.83 days (SD 8.29, n=52). grEPI surfaces the same event pair, so this is the species-matched default for BDBV visibility runs.

Sensitivity comparator

4.5 d

Camacho et al. 2015 remains attached as the former EBOV-Zaire onset-to-notification comparator (mean 4.5 days, SD 5.0). It is still useful because it shows how much faster-reporting assumptions narrow the hidden-case window.

R prior stance

0.86-1.37

Choi et al. 2019 gives historical BDBV model-derived R0 candidates for Isiro 2012. The library keeps the existing mean 1.33 prior because it sits inside that span, but caps the claim at derived-supported evidence.

Current visibility output

39.7% to 45.8%

This interval is from the current rerun with the Rosello BDBV default prior. It is shown next to Camacho sensitivity context so the epidemiologic shift is explicit.
What changes epidemiologically
The reporting-delay prior becomes less optimistic for very recent cases: under the Rosello BDBV distribution, about 53.3% of cases would be reported by day 7 and 79.9% by day 14; under the Camacho EBOV-Zaire comparator, those values are 78.6% and 94.5%. The practical read is that a fresh official count may be more right-censored than the old proxy implied.
What does not change yet
The rerun updates visibility-linked latent quantities (the reporting-completeness band and any confirmable-case inference that divides by it), but it does not alter headline reported counts or the deaths-back-projection constants.
What already matches the existing system
The onset-to-death value already used by the deaths-back-projection arm is the Rosello Isiro fit: mean 11.37 days, SD 5.41 days. The crude CFR scenario set remains 26%, 33%, and 40% from the CDC prior-outbreak aggregate. These are value-preserving; the material new sensitivity is the onset-to-notification prior.

External source feed: WHO grEPI. Scope boundary: population-level epidemiological parameters only; sequence-derived or organism-level quantities are excluded from the parameter library.

Boundaries

What this brief does NOT claim

These limits are part of the product surface. They keep the page from being misread as operational guidance or a forecast.

  • Not a forecast

    The pre-committed calibration points exist to evaluate the method's uncertainty quality at resolution. They are not surveillance recommendations and not deployment recommendations.
  • Not a critique of the national response

    Ascertainment gaps and late detection of filoviruses are intrinsic to the pathogen and to the operational context (security, displacement, co-circulating pathogens), not to the speed of any specific national response. The DRC Ministry of Public Health declared on 15 May, the Uganda Ministry of Health confirmed imported cases on 15-16 May, and INRB confirmed BDBV by PCR within days. This brief takes the national declarations as the authoritative timeline.
  • Does not replace field epidemiology

    Line-listing, contact tracing, genomic sequencing, and clinical reasoning are where outbreak control happens.
  • Species-transfer uncertainty is not separately quantified

    The historical calibration substrate is a Zaire-species outbreak; transfer to Bundibugyo carries unquantified uncertainty in the priors and the corridor model.
  • Numbers are prior-dominated at this case count

    The ascertainment and transmission-depth posteriors are heavily informed by the prior delay and transmission distributions, not by data alone. In particular, the branching-process reproduction prior is an interim modeling assumption: the May 23 parameter audit found historical BDBV model-derived R0 candidates, but not a measured 2026 R0. The detection-depth result is therefore prior-driven and not a data-driven current-outbreak BDBV estimate. Sensitivity analyses across alternative priors remain a recommended next step.
  • Open to independent replication

    Code is Apache 2.0 licensed; original authored methodology, prose, schema, and derived artifacts are CC BY 4.0; third-party source material and extracted publisher-owned tables retain their original terms. The method is described in CITATIONS.md. Independent replication is welcomed.

External cross-check

How LOVS treats the Imperial estimate

On May 20, 2026, Imperial College MRC GIDA and WHO published a joint situation estimate using two independent methods. LOVS uses that report as a methodological cross-check, not as a value to copy.

Adopted public inputs

CFR scenarios of 26%, 33%, 40% from the US CDC BDBV history; the Rosello onset-to-death fit; and the Method 2 deaths-back-projection formula as a cross-check.

Held separate

Imperial's final 400 to 900 total-case range and restricted Table 3 point-of-entry counts are not adopted into public LOVS outputs. The total-case range appears on the trajectory chart only as dashed reference ticks, so the LOVS band remains independent.

LOVS adds

Pre-committed corridor calibration, retrospective West Africa scoring, per-corridor reporting-completeness intervals, open-source code, and resolution scoring with the Weighted Interval Score.
Why the blue-slate band uses Imperial Method 2
The trajectory chart uses C = D · (1 + r/β)^α / CFR, not naive D / CFR. The correction follows Nishiura's real-time CFR formulation: in a growing epidemic, some infections that will die have not died yet, so a simple deaths/CFR ratio systematically undershoots. Joint Bayesian alternatives such as Salje, Cauchemez et al. 2020 require line-list or hospital-admission time series that this public snapshot does not have.
How doubling-time uncertainty is handled
No published BDBV-specific doubling time exists. Rosello et al. report effective reproduction numbers for Isiro 2012, but not a doubling time; the nearest filovirus growth anchors are the WHO Ebola Response Team 2014 estimates for Guinea, Liberia, and Sierra Leone. LOVS follows Imperial's central τ₂ = 14 d scenario and shows τ₂ ∈ {7, 14, 21} d in the sensitivity grid instead of mixing CFR and growth-rate uncertainty into one band.

Both efforts agree that the true outbreak is several multiples of public confirmations. The independent LOVS contribution is the pre-committed corridor view and its future scoring surface. Original authored methodology, prose, schema, and derived artifacts are released through the source repository; third-party source material retains publisher terms. Retrospective context comes from the West Africa 2014 outbreak.

Source trail

References

Consolidated bibliography across the brief, the LOVS pipeline priors, and the joint WHO-Imperial College MRC GIDA May 20, 2026 report referenced as an external cross-check. The full version with method-by-method attribution is in CITATIONS.md.

Frozen outbreak sources

32

Pulled from the snapshot JSON so the source trail moves with the dated page.

Methodology priors

14

Literature used by LOVS or by the Imperial cross-check.

Candidate inputs

1

Useful next-lever source classes that are not yet integrated into the pipeline.

Downloadable appendix

XLSX

Public-health evidence workbook generated from the pinned snapshot, source manifest, evidence-chain registry, and calibration ledger. Download workbook. Schema.

The outbreak-source list below is the frozen public-source set for this snapshot. Archive status is shown inline where available.

Primary outbreak and reporting sources

Methodology priors used by LOVS or Imperial

  • [M1]Imai et al. 2020, Imperial College COVID-19 Response Team Report 1, geographic-spread extrapolation blueprint cited by the Imperial-WHO outbreak-size estimate.
  • [M2]Rosello et al. 2015 eLife, Ebola virus disease in the Democratic Republic of the Congo, 1976-2014. The Isiro 2012 BDBV fit is the source of the onset-to-death gamma used in the deaths-back-projection arm and, after the May 23 parameter audit, of the onset-to-notification distribution adopted as the reporting-delay default for the Module C visibility nowcast (Camacho 2015 retained as the faster-reporting sensitivity comparator).
  • [M3]Wamala et al. 2010 EID, the Bundibugyo 2007-2008 Uganda discovery outbreak; source of the BDBV case-fatality-ratio range and the inter-case interval prior.
  • [M4]MacNeil et al. 2010 EID, BVD clinical features in Uganda; source of the mean incubation period and the bleeding-prevalence prior.
  • [M5]Albarino et al. 2013 Virology, BDBV genomic analysis across Uganda and DRC outbreaks; consistency check for species-stable transmission dynamics.
  • [M6]Faye et al. 2015 Lancet Infectious Diseases, Zaire-species serial-interval estimate referenced in the broader LOVS methodology lineage.
  • [M7]Camacho et al. 2015 PLOS Currents Outbreaks, EBOV-Zaire onset-to-notification delay retained as the reporting-delay sensitivity comparator after the May 23 parameter audit.
  • [M8]Choi et al. 2019 BIOMATH, historical Isiro 2012 BDBV modeling source surfaced by WHO grEPI for model-derived reproduction-number candidates; used only to cap and ground the R prior, not as a measured current-outbreak R0.
  • [M9]Cori et al. 2013 American Journal of Epidemiology, the EpiEstim R_t estimation framework from the broader Ebola modeling lineage; not a source for any LOVS delay or transmission prior.
  • [M10]Van Kerkhove et al. 2015 Scientific Data, Ebola epidemiological-parameter review; documents the earlier BDBV R0 evidence gap that the May 23 grEPI/Choi audit updates with capped, model-derived historical evidence.
  • [M11]WHO grEPI, Global Repository of Epidemiological Parameters; used on May 23 as the external source feed for population-level BDBV parameter candidates, with organism-level quantities excluded.
  • [M12]Backer and Wallinga 2016 PLOS Computational Biology, the 2014 West Africa Ebola spatiotemporal panel used as the LOVS Mode A retrospective substrate.
  • [M13]Bracher et al. 2021 PLOS Computational Biology, the Weighted Interval Score used in the LOVS calibration scoring.
  • [M14]ACLED conflict-event data, political-violence context used in the historical calibration substrate and referenced as qualitative Ituri/eastern DRC operating-context evidence.

Candidate inputs not yet integrated