Beyond linear models: science-policy interactions in pandemic governance

Background

Scientific advice in pandemics is often conceptualised as a linear process from evidence generation to policy decision-making. However, COVID-19 revealed that science-policy interaction is organised in diverse ways and involves ongoing negotiation between scientists, policymakers and political actors. This study examines how these interactions were structured and enacted across countries.

Methods

We conducted a comparative multiple-case study of scientific advisory mechanisms in seven Western European countries (Belgium, France, Germany, Ireland, the Netherlands, Switzerland, and the United Kingdom). Data included 30 semi-structured interviews with advisory members, policymakers, and researchers. Analysis focused on how interaction was organised, the roles of actors, and boundary arrangements between science and policy.

Results

Science-policy interaction was not linear but organised through distinct institutional arrangements. In some countries, policymakers were embedded within advisory committees; in others, interaction occurred through observer roles or external channels. Boundary actors, including committee chairs, chief medical officers and other brokerage roles, played a central role in translating knowledge and linking advisory and political arenas. Across cases, interaction was iterative and unfolded through both formal and informal channels, enabling continuous alignment between evidence, feasibility, and societal considerations. Integration of perspectives and the handling of independence and transparency depended on these arrangements, requiring ongoing mediation of roles and boundaries.

Conclusions

Pandemic governance is shaped by how science-policy interaction is organised in practice, rather than by a linear separation between science and policy. Designing effective advisory systems requires explicitly structuring interaction and boundary roles, rather than assuming that independence can be maintained through institutional separation alone.

Key messages

• Science–policy interaction during COVID-19 was iterative and context-dependent, rather than a linear transfer of evidence to policy.

• Effective pandemic governance requires designing advisory systems that manage interaction and boundary work, not just protect scientific independence.