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. New weekly cases were used to train these model forecasts. The data include confirmed and probable cases and may therefore decrease between measurements should some of the be reclassified. Additionally, delays in reporting may lead to temporal imprecision of both incidence and mortality data and an underestimation of outbreak growth.

For the forecasts posted here, we train our model using weekly case counts from the patient database; however, for the more recent weeks (two for Guinea and Sierra Leone, eight for Liberia) we use data from the weekly situation reports instead. The weekly mortality counts are displayed but were not used to train the models. The mortality forecasts are estimated from forecasts for new cases and last known case fatality rates.

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.
Method Revision An archive of forecasts based on cumulative case counts and cumulative mortality can be accessed here.

Mean estimates of new infections (upper-pane) and the number presently infectious (lower-pane) are shown above. The number infectious also represents the beds needed should all persons seek medical attention upon becoming symptomatic. 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. Use the Data tab for a table of forecast errors.

Last updated on January 28, 2015 using data reported through January 25, 2015