Volume 98, Issue 5
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645



We report on and evaluate the process and findings of a real-time modeling exercise in response to an outbreak of measles in Lola prefecture, Guinea, in early 2015 in the wake of the Ebola crisis. Multiple statistical methods for the estimation of the size of the susceptible (i.e., unvaccinated) population were applied to weekly reported measles case data on seven subprefectures throughout Lola. Stochastic compartmental models were used to project future measles incidence in each subprefecture in both an initial and a follow-up iteration of forecasting. Measles susceptibility among 1- to 5-year-olds was estimated to be between 24% and 43% at the beginning of the outbreak. Based on this high baseline susceptibility, initial projections forecasted a large outbreak occurring over approximately 10 weeks and infecting 40 children per 1,000. Subsequent forecasts based on updated data mitigated this initial projection, but still predicted a significant outbreak. A catch-up vaccination campaign took place at the same time as this second forecast and measles cases quickly receded. Of note, case reports used to fit models changed significantly between forecast rounds. Model-based projections of both current population risk and future incidence can help in setting priorities and planning during an outbreak response. A swiftly changing situation on the ground, coupled with data uncertainties and the need to adjust standard analytical approaches to deal with sparse data, presents significant challenges. Appropriate presentation of results as planning scenarios, as well as presentations of uncertainty and two-way communication, is essential to the effective use of modeling studies in outbreak response.

[open-access] This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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  1. Takahashi S, Metcalf CJ, Ferrari MJ, Moss WJ, Truelove SA, Tatem AJ, Grenfell BT, Lessler J, , 2015. Reduced vaccination and the risk of measles and other childhood infections post-Ebola. Science 347: 12401242.
  2. Doumtsop JG, Malano ER, Diallo IT, Sirimah C, , 2014. An evaluation of the 2012 measles mass vaccination campaign in Guinea. Pan Afr Med J 17: 4.
  3. Wolfson LJ, Strebel PM, Gacic-Dobo M, Hoekstra EJ, McFarland JW, Hersh BS, Measles Initiative; , 2007. Has the 2005 measles mortality reduction goal been achieved? A natural history modelling study. Lancet 369: 191200.
  4. Suk JE, 2016. Post-Ebola measles outbreak in Lola, Guinea, January–June 2015. Emerg Infect Dis 22: 11061108.
  5. Orenstein WA, Bernier RH, Dondero TJ, Hinman AR, Marks JS, Bart KJ, Sirotkin B, , 1985. Field evaluation of vaccine efficacy. Bull World Health Organ 63: 10551068.
  6. De Serres G, Boulianne N, Meyer F, Ward BJ, , 1995. Measles vaccine efficacy during an outbreak in a highly vaccinated population: incremental increase in protection with age at vaccination up to 18 months. Epidemiol Infect 115: 315323.
  7. Marin M, Nguyen HQ, Langidrik JR, Edwards R, Briand K, Papania MJ, Seward JF, LeBaron CW, , 2006. Measles transmission and vaccine effectiveness during a large outbreak on a densely populated island: implications for vaccination policy. Clin Infect Dis 42: 315319.
  8. Sudfeld CR, Navar AM, Halsey NA, , 2010. Effectiveness of measles vaccination and vitamin A treatment. Int J Epidemiol 39: i48i55.
  9. DHS, 2012. International, Demographic and Health Surveys (Various). Available at: http://dhsprogram.com/data/. Accessed April 5, 2015.
  10. Wesseh CS, Najjemba R, Edwards JK, Owiti P, Tweya H, Bhat P, , 2017. Did the Ebola outbreak disrupt immunisation services? A case study from Liberia. Public Health Action 7: S82S87.
  11. University of Southampton/Oxford, 2014. WorldPop. Available at: http://www.worldpop.org.uk/. Accessed April 5, 2015.
  12. Anderson RM, May RM, , 1982. Directly transmitted infections diseases: control by vaccination. Science 215: 10531060.
  13. Mossong J, Muller CP, , 2000. Estimation of the basic reproduction number of measles during an outbreak in a partially vaccinated population. Epidemiol Infect 124: 273278.
  14. Stan Development Team, 2015. Stan Modeling Language User’s Guide and Reference Manual, Version 2.8.0. Available at: http://mc-stan.org/users/documentation/. Accessed April 5, 2015.
  15. Stan Development Team, 2015. RStan: The R Interface to Stan, Version 2.8.0. Available at: https://cran.r-project.org/web/packages/rstan/vignettes/rstan.html. Accessed April 5, 2015.
  16. Gelman A, Rubin DB, , 1992. Inference from iterative simulation using multiple sequences. Stat Sci 7: 457511.
  17. Vink MA, Bootsma MCJ, Wallinga J, , 2014. Serial intervals of respiratory infectious diseases: a systematic review and analysis. Am J Epidemiol 180: 865875.
  18. Fine PE, , 2003. The interval between successive cases of an infectious disease. Am J Epidemiol 158: 10391047.
  19. Diekmann O, Heesterbeek JAP, Metz JAJ, , 1990. On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations. J Math Biol 28: 365382.
  20. Reliefweb-OCHA, 2017. Guinea Measles 2017 Outbreak. Available at: http://reliefweb.int/report/guinea/guinea-measles-outbreak-continues-spread. Accessed on March 15, 2017.
  21. WHO Ebola Response Team, 2014. Ebola virus disease in West Africa—the first 9 months of the epidemic and forward projections. N Engl J Med 371: 14811495.
  22. Meltzer MI, Atkins CY, Santibanez S, Knust B, Petersen BW, Ervin ED, Nichol ST, Damon IK, Washington ML, Centers for Disease Control and Prevention (CDC), 2014. Estimating the future number of cases in the Ebola epidemic—Liberia and Sierra Leone, 2014–2015. Morb Mortal Wkly Rep Suppl 63: 114.
  23. Rivers C, , 2014. Ebola: models do more than forecast. Nature 515: 492.
  24. Lewnard JA, Ndeffo Mbah ML, Alfaro-Murillo JA, Altice FL, Bawo L, Nyenswah TG, Galvani AP, , 2014. Dynamics and control of Ebola virus transmission in Montserrado, Liberia: a mathematical modelling analysis. Lancet Infect Dis 14: 11891195.
  25. Lofgren ET, 2014. Opinion: mathematical models: a key tool for outbreak response. Proc Natl Acad Sci USA 111: 1809518096.
  26. Van Kerkhove MD, Ferguson NM, , 2012. Epidemic and intervention modelling: a scientific rationale for policy decisions? Lessons from the 2009 influenza pandemic. Bull World Health Organ 90: 306310.

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Supplementary Data

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  • Received : 18 Mar 2017
  • Accepted : 14 Nov 2017

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