Network evolution in subnational epistemic learning during crises: a mixed-methods study of the fifth wave of the COVID-19 outbreak in Hong Kong

In times of crisis, policy learning is crucial for updating related knowledge and solutions. Epistemic communities take a central lead in the learning process, creating epistemic learning within it. At the subnational level, crises draw both national and local experts into the process; their interactions with one another and with policymakers form policy networks. Rather than remaining static, subnational epistemic learning networks evolve across phases as knowledge systems and political motivations diverge across communities, yielding distinct policy outcomes. Despite its importance, this dynamic of epistemic learning has received limited attention. To fill this gap, we examine Hong Kong’s epistemic learning during the fifth wave of the COVID-19 outbreak. Our empirical analysis shows that subnational epistemic learning networks do evolve and that their evolution is driven by intergovernmental relations – specifically, the distribution of resources, shifting policy objectives, and strategies employed by the national government. These findings advance ongoing deliberations about the conditions under which policy learning translates into policy change.