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Background <p>The COVID-19 pandemic necessitated the rapid production, synthesis, and translation of best available evidence to inform public health policy and practice decisions. This presents a unique learning opportunity to understand the interventions and strategies used to promote evidence-informed decision-making at the science-policy interface during this public health emergency and to explore what hindered or facilitated these processes.</p> Objectives <p>To describe the interventions at the science-policy interface used to support knowledge translation during the COVID-19 pandemic, explore the barriers and facilitators to such interventions, and apply findings to formal knowledge translation principles to inform the development of a logic model.</p> Methods <p>A systematic literature search of Medline via OVID, Scopus, and Web of Science was conducted. Studies were assessed for eligibility and critically appraised. A narrative synthesis was conducted. Knowledge translation models and frameworks were identified via Google Scholar and analysed for their applicability to a public health emergency context.</p> Results <p>We included 18 articles. The most common interventions at the science-policy interface were advisory committees, knowledge translation platforms and hubs, knowledge translation activities (knowledge brokering, priority-setting, workshops) and products (data visualisation and summaries). Barriers included: data availability and accessibility, time constraints, underrepresentation in advisory committees, political influence, and lack of transparency. Facilitators included: research coordination, interdisciplinary collaboration, transparency in research methods, and actionable and accessible evidence. We identified 11 knowledge translation models that contributed to the logic model.</p> Conclusions <p>Our findings, developed from empirical findings and theoretical principles, offer valuable insights into how knowledge translation infrastructures and processes could be strengthened in preparation for future public health emergencies.</p>

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Barriers and facilitators to knowledge translation at the science-policy interface during the COVID-19 pandemic public health emergency: a rapid review and theoretical analysis to inform development of a logic model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月13日

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  • Anna Vittoria Porter,
  • Natalie Joseph-Williams,
  • Cara Leighton,
  • Micaela Gal,
  • Adrian Edwards,
  • Alison Cooper

摘要

Background

The COVID-19 pandemic necessitated the rapid production, synthesis, and translation of best available evidence to inform public health policy and practice decisions. This presents a unique learning opportunity to understand the interventions and strategies used to promote evidence-informed decision-making at the science-policy interface during this public health emergency and to explore what hindered or facilitated these processes.

Objectives

To describe the interventions at the science-policy interface used to support knowledge translation during the COVID-19 pandemic, explore the barriers and facilitators to such interventions, and apply findings to formal knowledge translation principles to inform the development of a logic model.

Methods

A systematic literature search of Medline via OVID, Scopus, and Web of Science was conducted. Studies were assessed for eligibility and critically appraised. A narrative synthesis was conducted. Knowledge translation models and frameworks were identified via Google Scholar and analysed for their applicability to a public health emergency context.

Results

We included 18 articles. The most common interventions at the science-policy interface were advisory committees, knowledge translation platforms and hubs, knowledge translation activities (knowledge brokering, priority-setting, workshops) and products (data visualisation and summaries). Barriers included: data availability and accessibility, time constraints, underrepresentation in advisory committees, political influence, and lack of transparency. Facilitators included: research coordination, interdisciplinary collaboration, transparency in research methods, and actionable and accessible evidence. We identified 11 knowledge translation models that contributed to the logic model.

Conclusions

Our findings, developed from empirical findings and theoretical principles, offer valuable insights into how knowledge translation infrastructures and processes could be strengthened in preparation for future public health emergencies.