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. 2015 Dec 15;5(12):e009346.
doi: 10.1136/bmjopen-2015-009346.

Estimating the probability of demonstrating vaccine efficacy in the declining Ebola epidemic: a Bayesian modelling approach

Anton Camacho  1 , Rosalind M Eggo  1 , Sebastian Funk  1 , Conall H Watson  1 , Adam J Kucharski  1 , W John Edmunds  1
Affiliations

Estimating the probability of demonstrating vaccine efficacy in the declining Ebola epidemic: a Bayesian modelling approach

Anton Camacho et al. BMJ Open. .

Abstract

Objectives: We investigate the chance of demonstrating Ebola vaccine efficacy in an individually randomised controlled trial implemented in the declining epidemic of Forécariah prefecture, Guinea.

Methods: We extend a previously published dynamic transmission model to include a simulated individually randomised controlled trial of 100,000 participants. Using Bayesian methods, we fit the model to Ebola case incidence before a trial and forecast the expected dynamics until disease elimination. We simulate trials under these forecasts and test potential start dates and rollout schemes to assess power to detect efficacy, and bias in vaccine efficacy estimates that may be introduced.

Results: Under realistic assumptions, we found that a trial of 100,000 participants starting after 1 August had less than 5% chance of having enough cases to detect vaccine efficacy. In particular, gradual recruitment precludes detection of vaccine efficacy because the epidemic is likely to go extinct before enough participants are recruited. Exclusion of early cases in either arm of the trial creates bias in vaccine efficacy estimates.

Conclusions: The very low Ebola virus disease incidence in Forécariah prefecture means any individually randomised controlled trial implemented there is unlikely to be successful, unless there is a substantial increase in the number of cases.

Keywords: Clinical trials < THERAPEUTICS; Protocols & guidelines < HEALTH SERVICES ADMINISTRATION & MANAGEMENT; STATISTICS & RESEARCH METHODS.

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Figures

Figure 1
Figure 1
Model fit (blue) to the incidence data in Forécariah (red points) and forecast (grey) based on the posterior distribution at the latest data point (A). The solid line corresponds to the median estimate and the shaded areas to the 50% and 95% credible intervals. Fitted (blue) and forecasted (grey) values for the time-varying reproduction number Rt (B). Posterior distribution of Rt on 7 June 2015 (blue) and distribution corresponding to the trajectories used for forecasting (grey)(C). Mechanistic model for the vaccine trial (D). Susceptible participants are recruited into the trial at rate, rt. Before the trial begins, rt equals zero, and the model reduces to an SEIR model. Those entering the vaccine arm pass through a period of immune development, Vs, during which they are susceptible to Ebola virus disease infection. Following onset of protective immunity, they enter Vp and experience reduced susceptibility, σ, equal to the vaccine efficacy. Protective immunity is lost at rate γ, and individuals become susceptible again. Participants enter the control arm at the same rate as vaccinated participants and are separated between early (C1) and late (C2) control to match the delay in acquiring immunity in the vaccine arm. For biological realism, the distribution of durations of E, Vs and Vp follow an Erlang distribution with shape parameter two. Similarly, to match the vaccine arm, the same distribution is assumed for the compartment C1.
Figure 2
Figure 2
Detection of vaccine efficacy for a trial starting on 1 July with immediate vaccination. Extinction probability (A), power to detect efficacy (B) and power to detect efficacy adjusted by extinction probability (C), for assumed efficacy values 50, 70 and 90%.
Figure 3
Figure 3
Effect of group definition on trial outcomes. The X-axis shows the probability that the epidemic goes extinct before the value on the Y-axis is reached. Advancing time moves left-to-right, as the extinction probability increases. Power to detect efficacy (A), false-positive rate (B), and measured vaccine efficacy (where 70% is assumed) (C). The three group definitions (1) no early cases excluded (blue), (2) early cases in the vaccine arm excluded (black), and (3) cases in both arms excluded (red).
Figure 4
Figure 4
Effect of start date on trial success. The figure shows immediate administration of a 70% efficacious vaccine to all participants (round points) for trials starting on the 1 July, 1 August and 1 September. In addition, the gradual recruitment of participants (triangles) is shown for the 1 July start date. The dashed line shows the power when the assumed delay from administration of vaccine until protective immunity is 1 week. All other results are for a 2-week delay.
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