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Abstract The disproportionate effects of the 2009 H1N1 pandemic on many Canadian Aboriginal communities have drawn attention to the vulnerability of these communities in terms of health outcomes in the face of emerging and reemerging infectious diseases. Exploring the particular challenges facing these communities is essential to improving public health planning. In alignment with the objectives of the Pandemic Influenza Outbreak Research Modelling (Pan-InfORM) team, a Canadian public health workshop was held at the Centre for Disease Modelling (CDM) to: (i) evaluate post-pandemic research findings; (ii) identify existing gaps in knowledge that have yet to be addressed through ongoing research and collaborative activities; and (iii) build upon existing partnerships within the research community to forge new collaborative links with Aboriginal health organizations. The workshop achieved its objectives in identifying main research findings and emerging information post pandemic, and highlighting key challenges that pose significant impediments to the health protection and promotion of Canadian Aboriginal populations. The health challenges faced by Canadian indigenous populations are unique and complex, and can only be addressed through active engagement with affected communities. The academic research community will need to develop a new interdisciplinary framework, building upon concepts from ‘Communities of Practice’, to ensure that the research priorities are identified and targeted, and the outcomes are translated into the context of community health to improve policy and practice.

Background: The COVID-19 pandemic brought the production of scientific knowledge onto the public agenda in real-time. News media and commentators analysed the successes and failures of the pandemic response in real-time, bringing the process of scientific inquiry, which is also fraught with uncertainty, onto the public agenda. We examine how Canadian newspapers framed scientific uncertainty in their initial coverage of the COVID-19 pandemic and how journalists made sense of the scientific process., Methods: We conducted a framing analysis of 1143 news stories and opinion during the first two waves of the COVID-19 pandemic. Using a qualitative analysis software, our analysis focused, first, on how scientific uncertainty was framed in hard news and opinion discourse (editorial, op-ed). Second, we compared how specialist health and science reporters discussed scientific evidence versus non-specialist reporters in hard news and columns., Results: Uncertainty emerged as a "master frame" across the sample, and four additional framing strategies were used by reporters and commentators when covering the pandemic: (1), evidence -focusing on presence or absence of it-; (2) transparency and leadership -focusing on the pandemic response-; (3) duelling experts - highlighting disagreement among experts or criticizing public health decisions for not adhering to expert recommendations-; and (4) mixed messaging -criticizing public health communication efforts. While specialist journalists understood that scientific knowledge evolves and the process is fraught with uncertainty, non-specialist reporters and commentators expressed frustration over changing public health guidelines, leading to the politicization of the pandemic response and condemnation of elected officials' decisions., Conclusions: Managing scientific uncertainty in evolving science-policy situations requires timely and clear communication. Public health officials and political leaders need to provide clear and consistent messages and access to data regarding infection prevention guidelines. Public health officials should quickly engage in communication course corrections if original messages are missing the intended mark, and clearly explain the shift. Finally, public health communicators should be aware of and more responsive to a variety of media reporters, who will bring different interpretative frames to their reporting. More care and effort are needed in these communication engagements to minimize inconsistencies, uncertainty, and politicization., (© 2021. The Author(s).)