Format

Send to

Choose Destination
See comment in PubMed Commons below
Lancet Infect Dis. 2015 Jun;15(6):703-10. doi: 10.1016/S1473-3099(15)70139-8. Epub 2015 Apr 14.

Statistical power and validity of Ebola vaccine trials in Sierra Leone: a simulation study of trial design and analysis.

Author information

1
Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, TX, USA. Electronic address: steve.bellan@gmail.com.
2
Department of Biology, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.
3
Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.
4
School of Computational Science and Engineering, McMaster University, Hamilton, ON, Canada.
5
Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA.
6
Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT, USA.
7
Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT, USA; Department of Ecology and Evolution, Yale University, New Haven, CT, USA.
8
Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia; Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA; IHRC Inc, Atlanta, GA, USA.
9
Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA; Rollins School of Public Health, Emory University, Atlanta, GA, USA.
10
Francis I Proctor Foundation, University of California, San Francisco, CA, USA; Department of Ophthalmology, University of California, San Francisco, CA, USA; Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA.
11
Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA; The Santa Fe Institute, Santa Fe, NM, USA.
12
Department of Biology, McMaster University, Hamilton, ON, Canada.

Abstract

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.

Comment in

PMID:
25886798
PMCID:
PMC4815262
DOI:
10.1016/S1473-3099(15)70139-8
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Elsevier Science Icon for PubMed Central
    Loading ...
    Support Center