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Modeling the Ebola Outbreak in West Africa, 2014 Sept 30 th Update Bryan Lewis PhD, MPH (blewis@vbi.vt.edu)blewis@vbi.vt.edu Caitlin Rivers MPH, Eric Lofgren PhD, James Schlitt, Katie Dunphy, Henning Mortveit PhD, Dawen Xie MS, Samarth Swarup PhD, Hannah Chungbaek, Keith Bisset PhD, Maleq Khan PhD, Chris Kuhlman PhD, Stephen Eubank PhD, Madhav Marathe PhD, and Chris Barrett PhD Slide 2 Currently Used Data Data from WHO, MoH Liberia, and MoH Sierra Leone, available at https://github.com/cmrivers/ebola https://github.com/cmrivers/ebola MoH and WHO have reasonable agreement Sierra Leone case counts censored up to 4/30/14. Time series was filled in with missing dates, and case counts were interpolated. 2 CasesDeaths Guinea1074648 Liberia33621830 Nigeria228 Sierra Leone2208605 Total66663091 Slide 3 Epi Notes Reports of efficacy of HIV drug lowering mortality CNNCNN Two other physicians infected with Ebola back in US, one at NIH enrolled in vax trial PoliticoPolitico Suspect cases continue to be identified in the US, currently a patient in Dallas (previous negatives from CA, NY, NM, FL) WaPoWaPo Sierra Leones reporting still inconsistent Crawford Killian Crawford Killian 3 Slide 4 Liberia Case Locations 4 Slide 5 Liberia Contact Tracing 5 Slide 6 Liberia Forecasts 6 8/18- 8/24 8/25 8/31 9/01 9/07 9/08 9/14 9/15 9/21 9/22 9/29 9/30- 10/6 Actual431368421620558-- Forecast31441755573898113041733 Forecast performance Reproductive Number Community1.3 Hospital0.4 Funeral0.5 Overall2.2 52% of Infected are hospitalized Slide 7 Prevalence of Cases 7 WeekPeople in H+I 9/28/20141228 10/05/20141631 10/12/20142167 10/19/20142878 10/26/20143821 11/02/20145071 11/16/20148911 Slide 8 Sierra Leone Forecasts 8 Forecast performance 41% of cases are hospitalized 8/25 8/31 9/01 9/07 9/08 9/14 9/15 9/21 9/22- 9/28 9/29 10/06 10/06- 10/12 Actual196219194274332-- Forecast267333413512635786974 Slide 9 Prevalence in SL 9 WeekPeople in H+I 9/28/2014668 10/05/2014828 10/12/20141026 10/19/20141271 10/26/20141573 11/02/20141947 11/16/20142978 Slide 10 All Countries Forecasts 10 rI: 1.1 rH:0.4 rF:0.3 Overall:1.7 Slide 11 Combined Forecasts 11 8/18 8/24 8/25 8/31 9/1 9/7 9/8 9/14 9/15- 9/21 9/22 9/28 9/29 10/5 10/6 - 10/12 Actual559783681959917-- Forecast48357869383099411911426 Slide 12 Experiments Hospital bed estimate calculations Reduction in time to hospitalization Improvements in time from symptom onset to hospitalization 12 Slide 13 Hospital Beds Prelim analysis 13 Cases on Feb 1 Oct 1245k Nov 1312k Dec 1391k Jan 1475k No beds533k Impact in Liberia, beds only 16% hospitalization ratio -> 70% Beta_H reduction by 90% Slide 14 Hospital Beds Prelim analysis 14 Cases on Feb 1 Oct 173k Nov 1135k Dec 1230k Jan 1375k No beds533k Impact in Liberia, beds and proper burial 16% hospitalization ratio -> 70% Beta_H reduction by 90% Beta_F reduction by 90% Slide 15 Hospital beds Prelim analysis 15 Impact in Liberia, beds + proper burial + shortened time to hospitalization Slide 16 Hospital beds Prelim analysis 5 days3 days1 days Oct 152k25k10k Nov 1108k65k31k Dec 1206k152k92k Jan 1358k318k2506 16 Cumulative cases in Liberia on Feb 1 with reduced beta_H, reduced beta_F, and shortened time to hospitalization Slide 17 Optimal center placement Preliminary optimization using road networks and population centers 17 Slide 18 Agent-based Simulations Progress Regional travel method, developed Implementation working this week Interventional support designed for Increasing hospitalization level Better burial Decreasing time to hospitalization Capacity monitoring at ETU/ECU designed Need some bounds on experimental design 18 Slide 19 APPENDIX Supporting material describing model structure, and additional results 19 Slide 20 Legrand et al. Model Description Legrand, J, R F Grais, P Y Boelle, A J Valleron, and A Flahault. Understanding the Dynamics of Ebola Epidemics Epidemiology and Infection 135 (4). 2007. Cambridge University Press: 61021. doi:10.1017/S0950268806007217. 20 Slide 21 Compartmental Model Extension of model proposed by Legrand et al. Legrand, J, R F Grais, P Y Boelle, A J Valleron, and A Flahault. Understanding the Dynamics of Ebola Epidemics Epidemiology and Infection 135 (4). 2007. Cambridge University Press: 61021. doi:10.1017/S0950268806007217. 21 Slide 22 Legrand et al. Approach Behavioral changes to reduce transmissibilities at specified days Stochastic implementation fit to two historical outbreaks Kikwit, DRC, 1995 Gulu, Uganda, 2000 Finds two different types of outbreaks Community vs. Funeral driven outbreaks 22 Slide 23 Parameters of two historical outbreaks 23 Slide 24 NDSSL Extensions to Legrand Model Multiple stages of behavioral change possible during this prolonged outbreak Optimization of fit through automated method Experiment: Explore degree of fit using the two different outbreak types for each country in current outbreak 24 Slide 25 Optimized Fit Process Parameters to explored selected Diag_rate, beta_I, beta_H, beta_F, gamma_I, gamma_D, gamma_F, gamma_H Initial values based on two historical outbreak Optimization routine Runs model with various permutations of parameters Output compared to observed case count Algorithm chooses combinations that minimize the difference between observed case counts and model outputs, selects best one 25 Slide 26 Fitted Model Caveats Assumptions: Behavioral changes effect each transmission route similarly Mixing occurs differently for each of the three compartments but uniformly within These models are likely overfitted Many combos of parameters will fit the same curve Guided by knowledge of the outbreak and additional data sources to keep parameters plausible Structure of the model is supported 26 Slide 27 Liberia model params 27 Slide 28 Sierra Leone model params 28 Slide 29 All Countries model params 29 Slide 30 Long-term Operational Estimates Based on forced bend through extreme reduction in transmission coefficients, no evidence to support bends at these points Long term projections are unstable 30 Turn from 8-26 End from 8-26 Total Case Estimate 1 month3 months13,400 1 month6 months15,800 1 month18 months31,300 3 months6 months64,300 3 months12 months91,000 3 months18 months120,000 6 months12 months682,100 6 months18 months857,000