Ebola cases could top 10,000 by month’s end

Ebola cases could top 10,000 by month’s end, Fred Hutch researchers say
Disease modeling shows virus is spreading ‘without any end in sight’

Sept. 9, 2014

The deadly Ebola epidemic raging across West Africa will likely get far worse before it gets better, more than doubling the number of known cases by the end of this month.

That’s the word from disease modelers at Northeastern University and the Fred Hutchinson Cancer Research Center, who predict as many as 10,000 cases of Ebola virus disease could be detected by Sept. 24 – and thousands more after that.

“The epidemic just continues to spread without any end in sight,” said Dr. Ira Longini, a biostatistician at the the University of Florida and an affiliated member of Fred Hutch’s Vaccine and Infectious Disease and Public Health Sciences divisions. “The cat’s already out of the box – way, way out.”

It’s only a matter of time, they add, before the virus could start spreading to other places, including previously unaffected countries in Africa and developed nations like the United Kingdom -- and the U.S., according to a paper published Sept. 2 in the journal PLOS Currents Outbreaks.

[link to www.fhcrc.org]

Assessing the International Spreading Risk Associated with the 2014 West African Ebola Outbreak

September 2, 2014 · Research     


Background: The 2014 West African Ebola Outbreak is so far the largest and deadliest recorded in history. The affected countries, Sierra Leone, Guinea, Liberia, and Nigeria, have been struggling to contain and to mitigate the outbreak. The ongoing rise in confirmed and suspected cases, 2615 as of 20 August 2014, is considered to increase the risk of international dissemination, especially because the epidemic is now affecting cities with major commercial airports.

Method: We use the Global Epidemic and Mobility Model to generate stochastic, individual based simulations of epidemic spread worldwide, yielding, among other measures, the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. The mobility model integrates daily airline passenger traffic worldwide and the disease model includes the community, hospital, and burial transmission dynamic. We use a multimodel inference approach calibrated on data from 6 July to the date of 9 August 2014. The estimates obtained were used to generate a 3-month ensemble forecast that provides quantitative estimates of the local transmission of Ebola virus disease in West Africa and the probability of international spread if the containment measures are not successful at curtailing the outbreak.

Results: We model the short-term growth rate of the disease in the affected West African countries and estimate the basic reproductive number to be in the range 1.5 − 2.0 (interval at the 1/10 relative likelihood). We simulated the international spreading of the outbreak and provide the estimate for the probability of Ebola virus disease case importation in countries across the world. Results indicate that the short-term (3 and 6 weeks) probability of international spread outside the African region is small, but not negligible. The extension of the outbreak is more likely occurring in African countries, increasing the risk of international dissemination on a longer time scale.
http://currents.plos.org/outbreaks/