Background Social media is a rich source where we can learn about people’s reactions to social issues. As COVID-19 has impacted people’s lives, it is essential to capture how people react to public health interventions and understand their concerns. Objective We aim to investigate people’s reactions and concerns about COVID-19 in North America, especially in Canada. Methods We analyzed COVID-19–related tweets using topic modeling and aspect-based sentiment analysis (ABSA), and interpreted the results with public health experts. To generate insights on the effectiveness of specific public health interventions for COVID-19, we compared timelines of topics discussed with the timing of implementation of interventions, synergistically including information on people’s sentiment about COVID-19–related aspects in our analysis. In addition, to further investigate anti-Asian racism, we compared timelines of sentiments for Asians and Canadians. Results Topic modeling identified 20 topics, and public health experts provided interpretations of the topics based on top-ranked words and representative tweets for each topic. The interpretation and timeline analysis showed that the discovered topics and their trend are highly related to public health promotions and interventions such as physical distancing, border restrictions, handwashing, staying home, and face coverings. After training the data using ABSA with human-in-the-loop, we obtained 545 aspect terms (eg, “vaccines,” “economy,” and “masks”) and 60 opinion terms such as “infectious” (negative) and “professional” (positive), which were used for inference of sentiments of 20 key aspects selected by public health experts. The results showed negative sentiments related to the overall outbreak, misinformation and Asians, and positive sentiments related to physical distancing. Conclusions Analyses using natural language processing techniques with domain expert involvement can produce useful information for public health. This study is the first to analyze COVID-19–related tweets in Canada in comparison with tweets in the United States by using topic modeling and human-in-the-loop domain-specific ABSA. This kind of information could help public health agencies to understand public concerns as well as what public health messages are resonating in our populations who use Twitter, which can be helpful for public health agencies when designing a policy for new interventions.

Background An infodemic is an overflow of information of varying quality that surges across digital and physical environments during an acute public health event. It leads to confusion, risk-taking, and behaviors that can harm health and lead to erosion of trust in health authorities and public health responses. Owing to the global scale and high stakes of the health emergency, responding to the infodemic related to the pandemic is particularly urgent. Building on diverse research disciplines and expanding the discipline of infodemiology, more evidence-based interventions are needed to design infodemic management interventions and tools and implement them by health emergency responders. Objective The World Health Organization organized the first global infodemiology conference, entirely online, during June and July 2020, with a follow-up process from August to October 2020, to review current multidisciplinary evidence, interventions, and practices that can be applied to the COVID-19 infodemic response. This resulted in the creation of a public health research agenda for managing infodemics. Methods As part of the conference, a structured expert judgment synthesis method was used to formulate a public health research agenda. A total of 110 participants represented diverse scientific disciplines from over 35 countries and global public health implementing partners. The conference used a laddered discussion sprint methodology by rotating participant teams, and a managed follow-up process was used to assemble a research agenda based on the discussion and structured expert feedback. This resulted in a five-workstream frame of the research agenda for infodemic management and 166 suggested research questions. The participants then ranked the questions for feasibility and expected public health impact. The expert consensus was summarized in a public health research agenda that included a list of priority research questions. Results The public health research agenda for infodemic management has five workstreams: (1) measuring and continuously monitoring the impact of infodemics during health emergencies; (2) detecting signals and understanding the spread and risk of infodemics; (3) responding and deploying interventions that mitigate and protect against infodemics and their harmful effects; (4) evaluating infodemic interventions and strengthening the resilience of individuals and communities to infodemics; and (5) promoting the development, adaptation, and application of interventions and toolkits for infodemic management. Each workstream identifies research questions and highlights 49 high priority research questions. Conclusions Public health authorities need to develop, validate, implement, and adapt tools and interventions for managing infodemics in acute public health events in ways that are appropriate for their countries and contexts. Infodemiology provides a scientific foundation to make this possible. This research agenda proposes a structured framework for targeted investment for the scientific community, policy makers, implementing organizations, and other stakeholders to consider.

ObjectiveOur aim is to review, and qualitatively evaluate, the aims and measures of social referral programmes. Our first objective is to identify the aims of social referral initiatives. Our second objective is to identify the measures used to evaluate whether the aims of social referral were met.DesignLiterature review.BackgroundSocial referral programmes, also called social prescribing and emergency case referral, link primary and secondary healthcare with community services, often under the guise of decreasing health system costs.MethodFollowing the PRISMA guidelines, we undertook a literature review to address that aim. We searched in five academic online databases and in one online non-academic search engine, including both academic and grey literature, for articles referring to ‘social prescribing’ or ‘community referral’.ResultsWe identified 41 relevant articles and reports. After extracting the aims, measures and type of study, we found that most social referral programmes aimed to address a wide variety of system and individual health problems. This included cost savings, resource reallocation and improved mental, physical and social well-being. Across the 41 studies and reports, there were 154 different kinds of measures or methods of evaluation identified. Of these, the most commonly used individual measure was the Warwick-Edinburgh Mental Well-being Scale, used in nine studies and reports.ConclusionsThese inconsistencies in aims and measures used pose serious problems when social prescribing and other referral programmes are often advertised as a solution to health services-budgeting constraints, as well as a range of chronic mental and physical health conditions. We recommend researchers and local community organisers alike to critically evaluate for whom, where and why their social referral programmes ‘work’.

This article presents findings from local government projects to realise the benefits of big data for policy. Through participatory action research with two local statutory authorities in the South West of England, we observed the activities of identifying, integrating and analysing multiple and diverse forms of data, including large administrative datasets, to generate insights on live policy priorities and inform decision-making. We reveal the significance of both data production and policymaking contexts in explaining how big data of this kind can be called upon and enacted in policy processes.

These findings support the hypothesis that offenders with mental illness experience higher mortality that is mediated by higher rates of criminal justice contact. The results of our study indicate that criminal justice diversion programmes are further warranted because they may contribute to the prevention of mortality among offenders with mental illness.