Abstract
Before 2026, Bundibugyo virus disease had only two recognized outbreaks. By August 2026, delayed recognition and multi-day sample transport in eastern Democratic Republic of the Congo had contributed to a large, spatially dispersed epidemic. We hypothesized that model-guided placement of decentralized diagnostics in frontier health zones could help contain spatial spread by acting as a spatial fence: delayed recognition would be converted into timely polymerase chain reaction (PCR) confirmation, isolation, and contact tracing before imported lineages became established.
We fit a Bayesian spatial branching process to public situation reports through 2 August 2026, with Flowminder movement and a latent-burden anchor. Lineages had overdispersed offspring, PCR access and turnaround, clinical recognition, isolation, tracing, safe burial, and local behaviour change. Because the observed history did not identify future control, we assumed a national response ramp yielding West-Africa-scale status-quo burden and replayed 2,000 posterior trees with 5-100 zone-level PCR laboratories, deployment delays of 0-180 days, and postmortem rapid diagnostic test (RDT) coverage.
The posterior reproduced case, death, latent-burden, and spatial targets. Speed dominated: 35 PCR laboratories averted a median 49% of future deaths if deployed immediately, 38% after 14 days, and 11% after 60 days, with 90% prediction intervals of 30-65%, 23-53%, and 5-20%, respectively. Placement also mattered: with a 30-day delay, model-informed placement averted 18-33% of future deaths with 20-100 laboratories, versus 1-8% under random placement. Postmortem RDTs partly filled gaps left by live-case detection, increasing future deaths averted from 26% to 41% with 20 laboratories, a 14-day delay, and 75% coverage. Decentralized diagnostics can slow spatial spread when they are placed ahead of likely importations and paired with staffing, isolation, tracing, and safe-burial capacity.