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Peer-reviewedCC BYViruses

Rapid Geographic Expansion, Decelerating Growth, and Six-Month Scenario Projections of Bundibugyo Virus Disease in the Democratic Republic of the Congo: Analysis of Situation Reports 1-61.

  • David Lupande Mwenebitu1,2,3,4
  • Demelash Areda5
  • Pascal Adroba6
  • Franklin Mwamba7,8
  • Philippe Boribo Kikunda9,10
  • Olivier Mukuku11
  • Danstan Bagenda12
  • Misaki Wayengera13
  • Patrick D M Katoto1,2,4
  • Gaylord Ngaboyeka14
14 affiliations
  1. 1Laboratoire de Recherche Biomédicale Prof. Lurhuma, Faculty of Medicine, Université Catholique de Bukavu, B.P. 285, Bukavu, South Kivu, Democratic Republic of the Congo.
  2. 2Center for Tropical Diseases and Global Health, Université Catholique de Bukavu, B.P. 285, Bukavu, South Kivu, Democratic Republic of the Congo.
  3. 3Department of Biology, Institut Supérieur Pédagogique de Baraka (ISP Baraka), Baraka, South Kivu, Democratic Republic of the Congo.
  4. 4Interdisciplinary Consortium for Epidemics Research (ICER)-Regional Network, Bukavu, South Kivu, Democratic Republic of the Congo.
  5. 5College of Arts and Sciences, Ottawa University, 15950 N Civic Center Plaza, Surprise, AZ 85374, USA.
  6. 6Laboratoire Provincial de Santé Publique de l'Ituri, Bunia, Ituri, Democratic Republic of the Congo.
  7. 7Institute for Health Sciences Research (IRSS), B.P. 10.183, Kinshasa, Democratic Republic of the Congo.
  8. 8Department of Mathematics, Statistics and Computer Science, Faculty of Sciences and Technology, University of Kinshasa, B.P. 190, Kinshasa, Democratic Republic of the Congo.
  9. 9Faculty of Science and Technology, Université Catholique de Bukavu, B.P. 285, Bukavu, South Kivu, Democratic Republic of the Congo.
  10. 10Department of Management Information Systems, Institut Supérieur Pédagogique de Bukavu (ISP-Bukavu), B.P. 854, Bukavu, South Kivu, Democratic Republic of the Congo.
  11. 11École de Santé Publique, Université Officielle de Goma, B.P. 204, Goma, North Kivu, Democratic Republic of the Congo.
  12. 12Department of Anesthesiology, University of Nebraska Medical Center, 42nd and Emile Street, Omaha, NE 68198, USA.
  13. 13College of Health Sciences, Makerere University, Kampala P.O. Box 7062, Uganda.
  14. 14École Régionale de Santé Publique, Université Catholique de Bukavu, B.P. 285, Bukavu, South Kivu, Democratic Republic of the Congo.
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Abstract

In May 2026, the Democratic Republic of the Congo declared an outbreak of Bundibugyo virus disease caused by Bundibugyo ebolavirus. We analysed aggregated official Situation Reports (SitReps) issued from 14 May through 14 July 2026 to describe the reported epidemic trajectory, geographic expansion, mortality, interval-specific growth, and conditional six-month projections. Confirmed cases increased from 8 to 2073 and confirmed deaths reached 796; 45 health zones in five provinces were affected. Average interval-specific growth rates generally declined over the observation period, although cumulative cases and the geographic footprint continued to increase. Gompertz and Richards curves described the observed cumulative trajectory better than logistic and exponential curves according to root mean square error (RMSE), the corrected Akaike information criterion (AICc), and the Bayesian information criterion (BIC); this comparison reflects in-sample fit only. Conditional six-month scenarios varied substantially across assumptions (approximately 2435 to 10,839 cumulative cases by 14 January 2027) and are contingent and highly uncertain; Gompertz fits showed underprediction of the subsequently reported total in four temporal checks. Reported case fatality ratios (CFRs) varied across provinces but are vulnerable to outcome delay, incomplete case ascertainment, small denominators, and retrospective reclassification. The results support continued surveillance and response planning but do not identify the causes of epidemic slowing or establish that transmission was controlled.

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Cite

BibTeXRIS
BibTeX
@article{mwenebitu2026rapid,
  title = {{Rapid Geographic Expansion, Decelerating Growth, and Six-Month Scenario Projections of Bundibugyo Virus Disease in the Democratic Republic of the Congo: Analysis of Situation Reports 1-61.}},
  author = {David Lupande Mwenebitu and Demelash Areda and Pascal Adroba and Franklin Mwamba and Philippe Boribo Kikunda and Olivier Mukuku and Danstan Bagenda and Misaki Wayengera and Patrick D M Katoto and Gaylord Ngaboyeka},
  journal = {Viruses},
  year = {2026},
  month = oct,
  doi = {10.3390/v18101104},
  url = {https://europepmc.org/article/MED/42944023},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Rapid Geographic Expansion, Decelerating Growth, and Six-Month Scenario Projections of Bundibugyo Virus Disease in the Democratic Republic of the Congo: Analysis of Situation Reports 1-61.
AU  - David Lupande Mwenebitu
AU  - Demelash Areda
AU  - Pascal Adroba
AU  - Franklin Mwamba
AU  - Philippe Boribo Kikunda
AU  - Olivier Mukuku
AU  - Danstan Bagenda
AU  - Misaki Wayengera
AU  - Patrick D M Katoto
AU  - Gaylord Ngaboyeka
PY  - 2026
DA  - 2026/10/06
JO  - Viruses
DO  - 10.3390/v18101104
UR  - https://europepmc.org/article/MED/42944023
AB  - In May 2026, the Democratic Republic of the Congo declared an outbreak of Bundibugyo virus disease caused by Bundibugyo ebolavirus. We analysed aggregated official Situation Reports (SitReps) issued from 14 May through 14 July 2026 to describe the reported epidemic trajectory, geographic expansion, mortality, interval-specific growth, and conditional six-month projections. Confirmed cases increased from 8 to 2073 and confirmed deaths reached 796; 45 health zones in five provinces were affected. Average interval-specific growth rates generally declined over the observation period, although cumulative cases and the geographic footprint continued to increase. Gompertz and Richards curves described the observed cumulative trajectory better than logistic and exponential curves according to root mean square error (RMSE), the corrected Akaike information criterion (AICc), and the Bayesian information criterion (BIC); this comparison reflects in-sample fit only. Conditional six-month scenarios varied substantially across assumptions (approximately 2435 to 10,839 cumulative cases by 14 January 2027) and are contingent and highly uncertain; Gompertz fits showed underprediction of the subsequently reported total in four temporal checks. Reported case fatality ratios (CFRs) varied across provinces but are vulnerable to outcome delay, incomplete case ascertainment, small denominators, and retrospective reclassification. The results support continued surveillance and response planning but do not identify the causes of epidemic slowing or establish that transmission was controlled.
SN  - 1999-4915
ER  -