Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019

Worden, Lee; Wannier, Rae; Hoff, Nicole A.; Musene, Kamy; Selo, Bernice; Mossoko, Mathias; Okitolonda-Wemakoy, Emile; Muyembe Tamfum, Jean Jacques; Rutherford, George W.; Lietman, Thomas M.; Rimoin, Anne W.; Porco, Travis C.; Kelly, J. Daniel

Our models do not account for spatial heterogeneity in transmission, which may be relevant to the course of this outbreak, in which an increase in transmission appears to coincide with a shift in location. The stochastic model may be sensitive to the assumption of an exponentially decaying curve for transmission rate by day, and alternative assumptions might lead to a different distribution of forecast outcomes. Indeed, all of our projections are conditional on model assumptions being met. If unpredictable events were to change patterns of EBOV transmission in ways not seen in past outbreaks, assumptions used for model projections could be violated and our results could change. For example, exceedingly improbable events such as a catastrophic outbreak (more than 10,000 cases or approaching the size of the 2013-2016 West Africa outbreak) might become more probable. A strength of our approach was the use of multiple methods to estimate the outbreak size, including both mechanistic modeling and purely statistical approaches.