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As of October 12, 2018, 211 cases of Ebola virus disease (EVD) were reportedin North Kivu Province, Democratic Republic of Congo. Since the beginning ofOctober the outbreak has largely shifted into regions in which active armedconflict is occurring, and in which EVD cases and their contacts are difficultfor health workers to reach. We modeled EVD transmission using a branchingprocess with gradually quenching transmission estimated from past EVDoutbreaks, with outbreak trajectories conditioned on agreement with the courseof the current outbreak, and with multiple levels of vaccination coverage. Weused an autoregression for short-term projections, a regression model for finalsizes, and a simple Gott's law rule as an ensemble of forecasts. Short-termmodel projections were validated against actual case counts. During validationof short-term projections, models consistently scored higher on shorter-termforecasts. Based on case counts as of October 13, the stochastic modelprojected a median case count of 226 by October 27 (95% prediction interval:205-268) and 245 by November 10 (95% PI: 208-315), while the auto-regressionmodel projected median case counts of 240 (95% PI: 215-307) and 259 (95% PI:216-395) for those dates, respectively. Projected median final counts rangefrom 274 to 421. Except for Gott's law, the projected probability of anoutbreak surpassing 2013-2016 is exceedingly small. The stochastic modelestimates that vaccine coverage in this outbreak is lower than reported in itstrial. Based on our projections we believe that the epidemic had not yet peakedat the time of these estimates, though an outbreak like 2013-2016 is notlikely. We estimate that transmission rates are higher than under target levelsof vaccine coverage, and this model estimate may offer a surrogate indicatorfor the outbreak response challenges.

Real-time projections of epidemic transmission and estimation of  vaccination impact during an Ebola virus disease outbreak in the Eastern  region of the Democratic Republic of Congo