Statistical power and validity of Ebola vaccine trials in Sierra Leone: a simulation study of trial design and analysis - 19/05/15

Doi : 10.1016/S1473-3099(15)70139-8

Steven E Bellan, DrPhD ^a,^⁎ , Juliet R C Pulliam, PhD ^c,^d, Carl A B Pearson, PhD ^d, David Champredon, MSc ^e, Spencer J Fox, BS ^b, Laura Skrip, MPH ^g, Alison P Galvani, ProfPhD ^g,^h, Manoj Gambhir, PhD ^i,^j,^l, Ben A Lopman, PhD ^k,^m, Travis C Porco, ProfPhD ^n,^o,^p, Lauren Ancel Meyers, ProfPhD ^b,^q, Jonathan Dushoff, PhD ^f
^a Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, TX, USA
^b Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA
^c Department of Biology, University of Florida, Gainesville, FL, USA
^d Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
^e School of Computational Science and Engineering, McMaster University, Hamilton, ON, Canada
^f Department of Biology, McMaster University, Hamilton, ON, Canada
^g Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT, USA
^h Department of Ecology and Evolution, Yale University, New Haven, CT, USA
ⁱ Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
^j Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
^k Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
^l IHRC Inc, Atlanta, GA, USA
^m Rollins School of Public Health, Emory University, Atlanta, GA, USA
ⁿ Francis I Proctor Foundation, University of California, San Francisco, CA, USA
^o Department of Ophthalmology, University of California, San Francisco, CA, USA
^p Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
^q The Santa Fe Institute, Santa Fe, NM, USA

^*Correspondence to: Dr Steven E Bellan, Center for Computational Biology and Bioinformatics, College of Natural Sciences, The University of Texas at Austin, 1 University Station C4500, Austin, TX 78712, USA

Summary

Background

Safe and effective vaccines could help to end the ongoing Ebola virus disease epidemic in parts of west Africa, and mitigate future outbreaks of the virus. We assess the statistical validity and power of randomised controlled trial (RCT) and stepped-wedge cluster trial (SWCT) designs in Sierra Leone, where the incidence of Ebola virus disease is spatiotemporally heterogeneous, and is decreasing rapidly.

Methods

We projected district-level Ebola virus disease incidence for the next 6 months, using a stochastic model fitted to data from Sierra Leone. We then simulated RCT and SWCT designs in trial populations comprising geographically distinct clusters at high risk, taking into account realistic logistical constraints, and both individual-level and cluster-level variations in risk. We assessed false-positive rates and power for parametric and non-parametric analyses of simulated trial data, across a range of vaccine efficacies and trial start dates.

Findings

For an SWCT, regional variation in Ebola virus disease incidence trends produced increased false-positive rates (up to 0·15 at α=0·05) under standard statistical models, but not when analysed by a permutation test, whereas analyses of RCTs remained statistically valid under all models. With the assumption of a 6-month trial starting on Feb 18, 2015, we estimate the power to detect a 90% effective vaccine to be between 49% and 89% for an RCT, and between 6% and 26% for an SWCT, depending on the Ebola virus disease incidence within the trial population. We estimate that a 1-month delay in trial initiation will reduce the power of the RCT by 20% and that of the SWCT by 49%.

Interpretation

Spatiotemporal variation in infection risk undermines the statistical power of the SWCT. This variation also undercuts the SWCT’s expected ethical advantages over the RCT, because an RCT, but not an SWCT, can prioritise vaccination of high-risk clusters.

Funding

US National Institutes of Health, US National Science Foundation, and Canadian Institutes of Health Research.

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Plan

Introduction

Methods

Projection of district-level incidence in Sierra Leone

Simulation of trial populations

Simulation of trial designs

Statistical analysis

Role of the funding source

Results

Discussion

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Vol 15 - N° 6

P. 703-710 - juin 2015 Retour au numéro

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Statistical power and validity of Ebola vaccine trials in Sierra Leone: a simulation study of trial design and analysis - 19/05/15

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