Ensemble forecast modeling for the design of COVID-19 vaccine efficacy trials.
Vaccine
; 38(46): 7213-7216, 2020 10 27.
Article
in English
| MEDLINE | ID: covidwho-759423
ABSTRACT
To rapidly evaluate the safety and efficacy of COVID-19 vaccine candidates, prioritizing vaccine trial sites in areas with high expected disease incidence can speed endpoint accrual and shorten trial duration. Mathematical and statistical forecast models can inform the process of site selection, integrating available data sources and facilitating comparisons across locations. We recommend the use of ensemble forecast modeling - combining projections from independent modeling groups - to guide investigators identifying suitable sites for COVID-19 vaccine efficacy trials. We describe an appropriate structure for this process, including minimum requirements, suggested output, and a user-friendly tool for displaying results. Importantly, we advise that this process be repeated regularly throughout the trial, to inform decisions about enrolling new participants at existing sites with waning incidence versus adding entirely new sites. These types of data-driven models can support the implementation of flexible efficacy trials tailored to the outbreak setting.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Viral Vaccines
/
Clinical Trials as Topic
/
Coronavirus Infections
/
Pandemics
/
Betacoronavirus
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
/
Randomized controlled trials
Topics:
Vaccines
Limits:
Humans
Language:
English
Journal:
Vaccine
Year:
2020
Document Type:
Article
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