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Sixteen Days Undetected: Growth Dynamics and the Case for Pre-Positioned Response Capacity in the 2026 Bundibugyo Virus Disease Outbreak, Democratic Republic of the Congo

Journal
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases (Q1)
Published
8 October 2026
Study design
Unclassified
Evidence level
Level 5, Expert Opinion (CEBM 5)
Authors
Johan G L Verheyden, Celestin Nzanzu Mudogo
PMID
42849565
DOI
10.1016/j.ijid.2026.109170

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Abstract

OBJECTIVES: To estimate early growth rate, back-calculate transmission onset, and characterise the case-fatality trajectory of the 2026 Bundibugyo virus disease (BDBV) outbreak in the Democratic Republic of the Congo, the largest recorded BDBV outbreak to date. DESIGN OR METHODS: We analysed a corrected daily surveillance series (65 observations, 14 May-27 July 2026) using non-linear least-squares regression and a Bayesian Poisson growth model fitted by Markov chain Monte Carlo, with five sensitivity analyses. RESULTS: Early confirmed cases grew at 0.1261 per day (95% CI 0.0885-0.1636), a doubling time of 5.50 days (4.24-7.83), three-fold faster than previous BDBV outbreaks (15-18 days). Bayesian back-calculation placed transmission onset on 19 April 2026 (95% highest-density interval 9-27 April), 16 days before the WHO alert and 25 days before laboratory confirmation. Confirmed case-fatality ratio rose from 12.1% to 44.3%; a higher ratio among suspected than confirmed cases on 21 May (23.6% vs 10.8%; p=0.0080) supported progressive reclassification rather than increasing virulence. CONCLUSIONS: Rapid BDBV growth leaves little time for outbreak-triggered mobilisation. Sentinel alerts based on unexplained deaths compatible with viral haemorrhagic fever, with healthcare-worker deaths as a high-priority special case, together with pre-positioned surveillance, diagnostic, and response capacity, could reduce avoidable amplification before confirmation.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.