The magnitude and pace of the current Ebola outbreak is unprecedented and requires tools to assess the future scope of the epidemic, as well as the efficacy of intervention tools and strategies. Unfortunately, our understanding of Ebola transmission dynamics is incomplete and data on the present outbreak are limited. Consequently, we present our forecasts as estimates, and cannot provide well-constrained certainties or likelihoods to any of the predicted outcomes.

Data: Ebola data for Guinea, Liberia, and Sierra Leone were compiled from World Health Organization’s Disease Outbreak News and Situation Reports. Total cases and deaths were used to train these model forecasts. The data include confirmed, probable, and suspected cases and may therefore decrease between measurements should some of the unconfirmed cases (i.e. the probable and suspected cases) be excluded after testing.

Methods: The model used to generate these forecasts contains a stochastic component that allows the force of transmission to vary through time. This variability is intended to emulate the spatial-temporal variability of Ebola transmission dynamics within country due to changes in intervention, containment and social practices. Three scenarios are forecast using the optimized model:

  1. an improved scenario, in which intervention and containment, as estimated during the assimilation process, are more effective in the future;
  2. a no change scenario, in which intervention and containment, as estimated during the assimilation process, continues with the same efficacy;
  3. a degraded scenario, in which intervention and containment, though not absent, are less effective in the future.
Update 09/18/2014: In Guinea the no change forecasts, which previously best matched future outcomes, are now biased high and the improved scenario forecasts better match observations, suggesting an improvement of the situation within country (i.e. slowed growth and perhaps improved efficacy of intervention). In Liberia, there is some indication of slowing exponential growth. In Sierra Leone, the no change scenario forecasts continue to best match observed outcomes. Overall, for the combined forecast, the exponential growth of the outbreak has slowed over the last two weeks.

Mean estimates of cumulative cases of Infections (upper-pane) and Mortality (lower-pane) are shown below. The shaded region around the forecasts shows the interquartile range. A forecast horizon of 6 weeks is displayed. Hover on a data point to look at values. Use the Fit Cutoff slider at the top right to base estimates on a different observation cutoff date and Country selection box to see estimates for a different country. Use the Intervention selection box to see the forecasts under different scenarios.

Last updated on September 18, 2014 using data reported through September 14, 2014.