Research has revealed both the benefits and harms of social media use, but the public has very little guidance on how best to use social media to maximize the benefits to their health and well-being while minimizing the potential harms. Given that social media is intricately embedded in our lives, and we now have an entire generation of social media natives, the time has come for a public health research agenda to guide not only the public’s use of social media but also the design of social media platforms in ways that improve health and well-being. In this viewpoint we propose such a public health agenda for social media research that is framed around three broad questions: (1) How much social media use is unhealthy and what individual and contextual factors shape that relationship; (2) What are ways social media can be used to improve physical and mental well-being; and (3) How does health (mis)information spread, how does it shape attitudes, beliefs and behavior, and what policies or public health strategies are effective in disseminating legitimate health information while curbing the spread of health misinformation? We also discuss four key challenges that impede progress on this research agenda: negative sentiment about social media among the public and scientific community, a poorly regulated research landscape, poor access to social media data, and the lack of a cohesive academic field. Social media has revolutionized modern communication in ways that bring us closer to a global society, but we currently stand at an inflection point. A public health agenda for social media research will serve as a compass to guide us toward social media becoming a powerful tool for the public good.

As one of the few operating retail sectors, the food retail industry is encountering unique challenges and opportunities during the 2019 Novel Coronavirus. The pandemic led to various transformations in the food retail industry, including changes in consumers perception and behavior. Although the pandemic has a situational nature, such transformations could have both temporary and long-lasting effects on reforms of the grocery retail industry. We examined consumers retail grocery shopping behaviors change during the pandemic using a survey among 2,500 U.S. adults. Survey results show that consumers now have higher expectations for in-store safety; they have reduced the frequency of store patronage, travel time, and in-store duration; they have shifted shopping schedule and shopping destinations; and they have spent more per shopping trip. The increased spending in-store also paralleled with the expanded transactions across various online grocery shopping platforms, which created a perfect competition in the emerging online grocery retail industry. Such perfect competition is unique in the overall monopoly ecommerce world and it creates new opportunities for platforms to reform and co-develop a sustainable online grocery retailing industry. We further came up with managerial implications in short- and long-term for the brick-and-mortar stores as well as online grocery vendors.

While much effort has gone into building predictive models of the COVID-19 pandemic, some have argued that early exponential growth combined with the stochastic nature of epidemics make the long-term prediction of contagion trajectories impossible. We conduct two complementary studies to assess model features supporting better long-term predictions. First, we leverage the diverse models contributing to the CDC repository of COVID-19 USA death projections to identify factors associated with prediction accuracy across different projection horizons. We find that better long-term predictions correlate with: (1) capturing the physics of transmission (instead of using black-box models); (2) projecting human behavioral reactions to an evolving pandemic; and (3) resetting state variables to account for randomness not captured in the model before starting projection. Second, we introduce a very simple model, SEIRb, that incorporates these features, and few other nuances, offers informative predictions for as far as 20-weeks ahead, with accuracy comparable with the best models in the CDC set. Key to the long-term predictive power of multi-wave COVID-19 trajectories is capturing behavioral responses endogenously: balancing feedbacks where the perceived risk of death continuously changes transmission rates through the adoption and relaxation of various Non-Pharmaceutical Interventions (NPIs).

In the United States, distribution plans for the COVID-19 vaccination were established at the state level. However, some states, such as Connecticut, followed an age-based strategy without considering occupations or co-morbid conditions due to its simplicity in implementation. This strategy raised concerns about exacerbating health inequities because it did not prioritize vulnerable communities, specifically, minorities and low-income groups. The study aims to examine the vaccination inequities among different population groups for people aged 65+. A cross-sectional analysis of quantile-based independent sample t-test was employed to examine the relationship between eight social vulnerability indices (SVIs, i.e., below poverty, unemployed, without high school diploma, disability, minority, speaks English less than well, no vehicle, and mobile homes) and vaccination rates at the town level in Connecticut during the second phase of the vaccine distribution plan when individuals aged 65 and over were eligible. Negative binomial regressions were employed to further justify the relationships between SVIs and vaccination rates. The report shows that the differences in vaccination rates were statistically significant between the most vulnerable and the least vulnerable towns with respect to six SVIs (i.e., below poverty, without high school diploma, disability, minority, speaks English less than well, and no vehicle). The vaccination gap was greater for people aged 75+ than people aged 65-74. Among the selected SVIs, below poverty was negatively correlated with the vaccination rate for 75+, and without high school diploma was negatively correlated with both rates. This report reveals the significant health inequities in COVID-19 vaccination among the elderly population at the early vaccination phase. It can shed insights into health policy initiatives to improve vaccination coverage in the elderly communities, such as promoting onsite scheduling and increasing at-home vaccination services.