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Multiple epidemiological models have been proposed to predict the spread ofEbola in West Africa. These models include consideration of counter-measuresmeant to slow and, eventually, stop the spread of the disease. Here, we examineone component of Ebola dynamics that is of growing concern -- the transmissionof Ebola from the dead to the living. We do so by applying the toolkit ofmathematical epidemiology to analyze the consequences of post-deathtransmission. We show that underlying disease parameters cannot be inferredwith confidence from early-stage incidence data (that is, they are not"identifiable") because different parameter combinations can produce virtuallythe same epidemic trajectory. Despite this identifiability problem, we findrobustly that inferences that don't account for post-death transmission tend tounderestimate the basic reproductive number -- thus, given the observed rate ofepidemic growth, larger amounts of post-death transmission imply largerreproductive numbers. From a control perspective, we explain how improvementsin reducing post-death transmission of Ebola may reduce the overall epidemicspread and scope substantially. Increased attention to the proportion ofpost-death transmission has the potential to aid both in projecting the courseof the epidemic and in evaluating a portfolio of control strategies.

Post-death Transmission of Ebola: Challenges for Inference and Opportunities for Control