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Background Twitter has become a dominant source of public health data and a widely used method to investigate and understand public health–related issues internationally. By leveraging big data methodologies to mine Twitter for health-related data at the individual and community levels, scientists can use the data as a rapid and less expensive source for both epidemiological surveillance and studies on human behavior. However, limited reviews have focused on novel applications of language analyses that examine human health and behavior and the surveillance of several emerging diseases, chronic conditions, and risky behaviors. Objective The primary focus of this scoping review was to provide a comprehensive overview of relevant studies that have used Twitter as a data source in public health research to analyze users’ tweets to identify and understand physical and mental health conditions and remotely monitor the leading causes of mortality related to emerging disease epidemics, chronic diseases, and risk behaviors. Methods A literature search strategy following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extended guidelines for scoping reviews was used to search specific keywords on Twitter and public health on 5 databases: Web of Science, PubMed, CINAHL, PsycINFO, and Google Scholar. We reviewed the literature comprising peer-reviewed empirical research articles that included original research published in English-language journals between 2008 and 2021. Key information on Twitter data being leveraged for analyzing user language to study physical and mental health and public health surveillance was extracted. Results A total of 38 articles that focused primarily on Twitter as a data source met the inclusion criteria for review. In total, two themes emerged from the literature: (1) language analysis to identify health threats and physical and mental health understandings about people and societies and (2) public health surveillance related to leading causes of mortality, primarily representing 3 categories (ie, respiratory infections, cardiovascular disease, and COVID-19). The findings suggest that Twitter language data can be mined to detect mental health conditions, disease surveillance, and death rates; identify heart-related content; show how health-related information is shared and discussed; and provide access to users’ opinions and feelings. Conclusions Twitter analysis shows promise in the field of public health communication and surveillance. It may be essential to use Twitter to supplement more conventional public health surveillance approaches. Twitter can potentially fortify researchers’ ability to collect data in a timely way and improve the early identification of potential health threats. Twitter can also help identify subtle signals in language for understanding physical and mental health conditions.

Policy Points Health and civic engagement are reciprocally and longitudinally linked: Poor health is associated with less civic engagement. Well‐established social drivers of health and health inequality such as inadequate access to health care, poverty, racism, housing instability, and food insecurity are also drivers of lower civic engagement. A robust primary care system can play a key role in advancing civic engagement (e.g., voting, volunteerism, community service, and political involvement) at the population level but has received little attention. Policy and practice solutions at the individual and structural levels should support and leverage potential synergies among health equity, civic engagement, and primary care. ContextHealth and civic engagement are linked. Healthier people may be able to participate more fully in civic life, although those with poorer health may be motivated to address the roots of their health challenges using collective action. In turn, civically active people may experience better health, and societies with more equitable health and health care may experience healthier civic life. Importantly, a robust primary care system is linked to greater health equity. However, the role of primary care in advancing civic engagement has received little study.MethodsWe synthesize current literature on the links among health, civic engagement, and primary care. We propose a conceptual framework to advance research and policy on the role of primary care in supporting civic engagement as a means for individuals to actualize their health and civic futures.FindingsCurrent literature supports relationships between health equity and civic engagement. However, this literature is primarily cross‐sectional and confined to voting. Our integrative conceptual framework highlights the interconnectedness of primary care structures, health equity, and civic engagement and supports the crucial role of primary care in advancing both civic and health outcomes. Primary care is a potentially fruitful setting for cultivating community and individual health and power by supporting social connectedness, self‐efficacy, and collective action.ConclusionsHealth and civic engagement are mutually reinforcing. Commonalities between social determinants of health and civic engagement constitute an important convergence for policy, practice, and research. Responsibility for promoting both health and civic engagement is shared by providers, community organizations, educators, and policymakers, as well as democratic and health systems, yet these entities rarely work in concert. Future work can inform policy and practice to bolster primary care as a means for promoting health and civic engagement.

The covid-19 pandemic has pressured governments to respond with restrictive and health resource-oriented policies to contain the spread of the virus. The aim of this paper is to assess differential policy implementation due to state fragility with a spatial scope of the Middle Eastern region. The policies implemented by the four strongest and six most fragile Middle Eastern countries were extracted from the CoronaNet Government Response Database and grouped into restrictive and resource-oriented categories. Clustering based on these categories informed dyadic analysis. Drawing from the Oxford Government Response Policy Tracker and covid-19 World Symptom Survey, we found that fragile states tended to be characterized by a higher proportion of restrictive policies, lower government stringency, and lower compliance. The results identify sectors that would benefit most from humanitarian aid and raise the issue of whether restrictions are disproportionately implemented due to covert political agendas or lack of political and economic power.