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Estimates of Outbreak Risk from New Introductions of Ebola with Immediate and Delayed Transmission Control - Volume 21, Number 8—August 2015 - Emerging Infectious Disease journal - CDC

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Estimates of Outbreak Risk from New Introductions of Ebola with Immediate and Delayed Transmission Control - Volume 21, Number 8—August 2015 - Emerging Infectious Disease journal - CDC

Volume 21, Number 8—August 2015


Estimates of Outbreak Risk from New Introductions of Ebola with Immediate and Delayed Transmission Control

Damon J.A. TothComments to Author , Adi V. Gundlapalli, Karim Khader, Warren B.P. Pettey, Michael A. Rubin, Frederick R. Adler, and Matthew H. Samore
Author affiliations: University of Utah, Salt Lake City, Utah, USA (D.J.A. Toth, A.V. Gundlapalli, K. Khader, W.B.P. Pettey, M.A. Rubin, F.R. Adler, M.H. Samore)US Department of Veterans Affairs Salt Lake City Health Care System, Salt Lake City (D.J.A. Toth, A.V. Gundlapalli, K. Khader, W.B.P. Pettey, M.A. Rubin, M.H. Samore).


While the ongoing Ebola outbreak continues in the West Africa countries of Guinea, Sierra Leone, and Liberia, health officials elsewhere prepare for new introductions of Ebola from infected evacuees or travelers. We analyzed transmission data from patients (i.e., evacuees, international travelers, and those with locally acquired illness) in countries other than the 3 with continuing Ebola epidemics and quantitatively assessed the outbreak risk from new introductions by using different assumptions for transmission control (i.e., immediate and delayed). Results showed that, even in countries that can quickly limit expected number of transmissions per case to <1, the probability that a single introduction will lead to a substantial number of transmissions is not negligible, particularly if transmission variability is high. Identifying incoming infected travelers before symptom onset can decrease worst-case outbreak sizes more than reducing transmissions from patients with locally acquired cases, but performing both actions can have a synergistic effect.
The ongoing Ebola outbreak in West Africa, thought to have begun from a single index case in Guinea in December 2013 (1), has produced thousands of cases in Guinea, Sierra Leone, and Liberia (2). This Ebola outbreak is the largest and most widespread since the Ebola virus was discovered in 1976 (3), and the probability of international spread outside of West Africa is not negligible (4). By late April 2015, the virus had been introduced by 7 infected people traveling during their incubation or symptomatic periods to a country other than Guinea, Sierra Leone, or Liberia. Of these 7 cases, 1 led to an outbreak with 19 transmissions in Nigeria (5,6); 1 led to 2 transmissions in the United States (7,8); 1 led to 7 transmissions in Mali (9,10); and 4 led to no transmissions in Mali (11), Senegal (12), the United States (13), and the United Kingdom (14). Additionally, 20 persons who acquired infection in Africa were transferred to the United States and several European countries for treatment (15), leading to 1 transmission in Spain (16).
Although none of these introductions led to a long chain of transmissions, even a small outbreak in a new country can cause societal disruption and disproportionate costs (17). Furthermore, how likely it is that an introduced case will lead to a substantial number of transmissions is unclear, even in settings with a quick and vigorous public health response to new outbreaks. Gomes et al. (4) performed simulations of Ebola outbreaks in each of 220 countries by first estimating the risk of Ebola being exported from Guinea, Liberia, or Sierra Leone by international travelers and then simulating a stochastic Ebola transmission model conditioned on an importation. The model incorporated Ebola transmission from infected persons in the community and hospital settings and from recently deceased Ebola patients. Assumptions used in the model were that only community transmissions are relevant outside of Africa and that transmissions occur at rates corresponding to containment measures already in place. Gomes et al. provided no explicitly numerical probabilities of large outbreaks per importation, but their simulations apparently produced <100 cases in each country.
In another study, Rainisch et al. (18) calculated the estimated number of beds required to treat Ebola patients in the United States by using estimates of importation frequency and subsequent transmission. These researchers reported a high estimate of 7 beds (95% CI 2–13) required at any 1 time; they also provided no numerical probabilities for their estimates.
In our study, we use a branching process model to estimate the probability distribution of outbreak sizes resulting from the introduction of an Ebola case to a new country where the reproductive number R (i.e., expected number of transmissions per case) would likely be quickly, if not immediately, reduced to <1. In this scenario, theory from subcritical branching processes (19), also known as mortal branching processes (20), guarantees that an outbreak will eventually die out, although perhaps not before a substantial number of transmissions occur. In the modeling literature, outbreaks that die out on their own have been called minor outbreaks (21) or stuttering chains (22). Such branching process models have been used to estimate transmission parameters in the context of emerging (22,23) or reemerging (1921,24) infectious diseases. However, unlike other studies, we used the outbreak final size distribution equations derived from branching process theory to calculate the risk for a large Ebola outbreak under the assumptions of immediate and delayed transmission control after an importation.
Dr. Toth is an assistant professor in the Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA. His research interest is applied mathematics, specifically mathematical modeling of infection and transmission of pathogens to support risk assessment and intervention planning for public health.


  1. Baize SPannetier DOestereich LRieger TKoivogui LMagassouba NEmergence of Zaire Ebola virus disease in Guinea. N Engl J Med.2014;371:141825DOIPubMed
  2. Centers for Disease Control and Prevention2014 Ebola outbreak in West Africa—outbreak distribution map. 2015 Apr 17 [cited 2015 Apr 24].
  3. Centers for Disease Control and Prevention. Outbreaks chronology: Ebola virus disease. 2015 Apr 24 [cited 2015 Apr 24].
  4. Gomes MFCPostore y Piontti ARossi LChao DLongini IHalloran MEAssessing the international spreading risk associated with the 2014 West African Ebola outbreak. PLoS Curr Outbreaks. 2014 Sep 2. Edition 1.
  5. Fasina FOShittu ALazarus DTomori OSimonsen LViboud CTransmission dynamics and control of Ebola virus disease outbreak in Nigeria, July to September 2014. Euro Surveill2014;19:20920.PubMed
  6. Shuaib FGunnala RMusa EOMahoney FJOguntimehin ONguku PMEbola virus disease outbreak—Nigeria, July–September 2014. MMWR Morb Mortal Wkly Rep2014;63:86772.PubMed
  7. McCarty CLBasler CKarwowski MErme MNixon GKippes CResponse to importation of a case of Ebola virus disease—Ohio, October 2014.MMWR Morb Mortal Wkly Rep2014;63:1089–91.PubMed
  8. Chevalier MSChung WSmith JWeil LMHughes SMJoyner SNEbola virus disease cluster in the United States—Dallas County, Texas, 2014.MMWR Morb Mortal Wkly Rep2014;63:1087–8.PubMed
  9. World Health Organization. Mali: details of the additional cases of Ebola virus disease. 2014 Nov 20 [cited 2015 Apr 24].
  10. World Health Organization. Mali confirms 2 new cases of Ebola virus disease. 2014 Nov 25 [cited 2015 Apr 24].
  11. World Health Organization. Mali case, Ebola imported from Guinea. 2014 Nov 10 [cited 2015 Apr 24].
  12. Mirkovic KThwing JDiack PAImportation and containment of Ebola virus disease— Senegal, August–September 2014. MMWR Morb Mortal Wkly Rep2014;63:8734.PubMed
  13. Centers for Disease Control and Prevention. Cases of Ebola diagnosed in the United States. 2014 Dec 16 [cited 2015 Apr 24].
  14. Jenkins L. Nurse who contracted Ebola released from hospital. 2015 Jan 24 [cited 2015 Apr 24].
  15. Public Health England. Ebola virus disease epidemiological update: no. 32. 2015 Apr 24 [cited 2015 Apr 24].
  16. Gulland ASpanish authorities investigate how nurse contracted Ebola. BMJ2014;349:g6120DOIPubMed
  17. Szabo L. Costs of responding to Ebola adding up. 2014 Nov 25 [cited 2015 Apr 24].
  18. Rainisch GAsher JGeorge DClay MSmith TLCosmos KEstimating Ebola treatment needs, United States [letter]. Emerg Infect Dis. 2015 Jul [cited 2015 Apr 27].
  19. Farrington CPGrant ADThe distribution of time to extinction in subcritical branching processes: applications to outbreaks of infectious disease. J Appl Probab1999;36:7719DOI
  20. Becker NOn parametric estimation for mortal branching processes. Biometrika1974;61:3939DOI
  21. Nishiura HYan PSleeman CKMode CJEstimating the transmission potential of supercritical processes based on the final size distribution of minor outbreaks. J Theor Biol2012;294:4855DOIPubMed
  22. Blumberg SLloyd-Smith JOInference of R0 and transmission heterogeneity from the size distribution of stuttering chains. PLOS Comput Biol.2013;9:e1002993DOIPubMed
  23. Ferguson NMFraser CDonnelly CAGhani ACAnderson RMPublic health risk from the avian H5N1 influenza epidemic. Science.2004;304:9689DOIPubMed
  24. Jansen VAAStollenwerk NJensen HJRamsay MEEdmunds WJRhodes CJMeasles outbreaks in a population with declining vaccine uptake.Science2003;301:804DOIPubMed
  25. Lloyd-Smith JOSchreiber SJKopp PEGetz WMSuperspreading and the effect of individual variation on disease emergence. Nature.2005;438:3559DOIPubMed
  26. DiCiccio TEfron BBootstrap confidence intervals. Stat Sci1996;11:189228 .DOI
  27. Arnold TBEmerson JW. Nonparametric goodness-of-fit tests for discrete null distributions. R J. 2011;3/2:34–9.
  28. Consul PCShenton LRUse of Lagrange expansion for generating discrete generalized probability distributions. SIAM J Appl Math.1972;23:23948DOI
  29. Consul PCFamoye F. Lagrangian probability distributions. Boston: Birkhauser; 2006.
  30. Centers for Disease Control and Prevention. Interim guidance for U.S. hospital preparedness for patients under investigation (PUIs) or with confirmed Ebola virus disease (EVD): a framework for a tiered approach. 2015 Feb 20 [cited 2015 Apr 24].
  31. Althaus CLEbola superspreading: the real lessons from HIV scale-up. Lancet Infect Dis2015;15:5078DOIPubMed
  32. Faye OBoelle PHeleze EFaye OLoucoubar CMagassouba NChains of transmission and control of Ebola virus disease in Conakry, Guinea, in 2014: an observational study. Lancet Infect Dis2015;15:3206DOIPubMed
  33. Bogoch IICreatore MICetron MSBrownstein JSPesik NMiniota JAssessment of the potential for international dissemination of Ebola virus via commercial air travel during the 2014 west African outbreak. Lancet2015;385:2935DOIPubMed
  34. Rainisch GShankar MWellman MMerlin TMeltzer MIRegional spread of Ebola virus, West Africa, 2014. Emerg Infect Dis2015;21:4447.DOIPubMed
  35. Chowell DCastillo-Chavez CKrishna SQiu XAnderson KSModelling the effect of early detection of Ebola. Lancet Infect Dis2015;15:1489.DOIPubMed



Technical Appendix

Suggested citation for this article: Toth DJA, Gundlapalli AV, Khader K, Pettey WBP, Rubin MA, Adler FR, et al. Estimates of outbreak risk from new introductions of Ebola with immediate and delayed transmission control. Emerg Infect Dis. 2015 Aug [date cited].
DOI: 10.3201/eid2108.150170

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