Abstract

BackgroundInfectious disease epidemics are a constant threat, and while we can strengthen preparedness in advance, inevitably, we will sometimes be caught unaware by novel outbreaks. To address the challenge of rapidly identifying clinical research priorities in those circumstances, we developed and piloted a protocol for carrying out a systematic, rapid research needs appraisal (RRNA) of existing evidence within 5 days in response to outbreaks globally, with the aim to inform clinical research prioritization.MethodsThe protocol was derived from rapid review methodologies and optimized through effective use of pre-defined templates and global time zones. It was piloted using a Lassa fever (LF) outbreak scenario. Databases were searched from 1969 to July 2017. Systematic reviewers based in Canada, the UK, and the Philippines screened and extracted data using a systematic review software. The pilot was evaluated through internal analysis and by comparing the research priorities identified from the data, with those identified by an external LF expert panel.ResultsThe RRNA pilot was completed within 5 days. To accommodate the high number of articles identified, data extraction was prioritized by study design and year, and the clinical research prioritization done post-day 5. Of 118 potentially eligible articles, 52 met the data extraction criteria, of which 46 were extracted within the 5-day time frame. The RRNA team identified 19 clinical research priorities; the expert panel independently identified 21, of which 11 priorities overlapped. Each method identified a unique set of priorities, showing that combining both methods for clinical research prioritization is more robust than using either method alone.ConclusionsThis pilot study shows that it is feasible to carry out a systematic RRNA within 5 days in response to a (re-) emerging outbreak to identify gaps in existing evidence, as long as sufficient resources are identified, and reviewers are experienced and trained in advance. Use of an online systematic review software and global time zones effectively optimized resources. Another 3 to 5 days are recommended for review of the extracted data and to formulate clinical research priorities. The RRNA can be used for a “Disease X” scenario and should optimally be combined with an expert panel to ensure breadth and depth of coverage of clinical research priorities.

Highlights

  • Infectious disease epidemics are a constant threat, and while we can strengthen preparedness in advance, inevitably, we will sometimes be caught unaware by novel outbreaks

  • Screening of title and abstracts began before the end of day 1, started by the review team in Canada, followed by Coordinating team (CT)

  • Diagnostics Can we develop a diagnostic test that is highly sensitive and specific for all lineages? How does sequence variation/heterogeneity impact diagnostic methods and accuracy? What is the optimal sampling time frame for diagnostics using RT-polymerase chain reaction (PCR)? How many days after symptoms does Lassa virus become detectable by PCR? Can we develop a validated point-of-care test for use in different healthcare settings, including rural health posts?

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Summary

Introduction

Infectious disease epidemics are a constant threat, and while we can strengthen preparedness in advance, inevitably, we will sometimes be caught unaware by novel outbreaks. To address the challenge of rapidly identifying clinical research priorities in those circumstances, we developed and piloted a protocol for carrying out a systematic, rapid research needs appraisal (RRNA) of existing evidence within 5 days in response to outbreaks globally, with the aim to inform clinical research prioritization. There is no gold standard approach for rapid or scoping reviews, with methods varying greatly [5,6,7,8,9,10,11] This highlights a need for a robust methodology to rapidly and systematically identify key gaps in knowledge and evidence to inform research prioritization early in outbreaks. The aim is to identify important gaps in evidence and knowledge in a robust, systematic, and replicable manner to rapidly inform clinical research prioritization

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