BETTER EPIDEMIC CONTROL FOR FUTURE AFRICAN EBOLA OUTBREAKS: DYNAMIC SIMULATION MODELING CALIBRATION AND ANALYSIS
Method: We developed a 5-compartment dynamic transmission model of Ebola for the 2014 Liberian outbreak and performed literature review to characterize model inputs and their uncertainty. We matched 2-week moving averages of new Ebola cases reported by the World Health Organization both before widespread burial and social distancing interventions began in Liberia (prior to September 2014) as well as afterwards (through mid-May 2015) by performing 10,000 Neldor-Mead search calibrations from random starting sets of inputs. By simultaneously calibrating to both periods, we recovered natural history parameters and intervention effectiveness. The objective function of the calibration was a weighted sum-of-squares where weights were the inverse of the standard error of the observed estimates under the binomial distribution. For analyses of alternative timings of interventions, we sampled 1,000 calibrated parameter sets with replacement from the 10,000, weighting the sampling by an approximation of the likelihood function so that better-fitting sets were more likely to be sampled.
Result: Compared to the observed 10,604 cumulative Ebola cases from the current outbreak in Liberia, our model predicts 10,519 cases [95%CrI: 9,755-10,992]. If interventions had been implemented earlier by 1 month, total cases are predicted at 1,904 [95%CrI: 1,359-2,951]. At 2 months earlier, these figures are 485 cases [95%CrI: 273-1,041].
Conclusion: Initiating safe burial and social distancing interventions earlier via better surveillance and epidemic preparedness has the potential to substantially decrease the impact of future Ebola epidemics in urban African settings.