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

We used four independent methods to generate projections of future case counts: (1) a stochastic simulation model, (2) a negative binomial auto-regression model, (3) a Theil-Sen regression model, and (4) a final size projection based on Gott's rule. The stochastic simulation model, extending a model used in previous work [16] , was calibrated to time-dependent transmission rates measured from past EVD outbreaks, and constrained to the observed partial trajectory of the current outbreak. This model generated short-and long-term projections. The negative binomial auto-regression model produced short-term projections based on case counts from the outbreak to date and prior outbreaks. The Theil-Sen regression model predicted final outbreak size based on prior outbreaks. We used a probability mass function derived from Gott's rule as a minimum-information projection of final outbreak size, using only the assumption that the proportion of the outbreak observed so far is entirely unknown. From these, we assembled an ensemble of projections to be compared and recorded for future evaluation against final outcomes.