INTRODUCTION: During the COVID-19 pandemic, grocery workers experienced new (in addition to existing) work-related stressors that put them at risk for psychological distress. This study uses the job demands-resources theory to identify and describe the job demands and resources associated with grocery worker distress. METHODS: This study analyzed data from 75 90-minute interviews focusing on grocery workers' experiences during the COVID-19 pandemic. During the interviews, participants also answered questions associated with the Patient Health Questionnaire 4, a validated measure of psychological distress. RESULTS: Overall, the study found that 36% of study participants exhibited mild to severe psychological distress at the time of their interviews, and a greater proportion of young, female, and White participants reported mild to severe psychological distress than did participants in other subgroups. Qualitative data suggest that the prevalence of psychological distress among participants was likely higher at the beginning of the pandemic and resulted from fear of SARS-CoV-2 exposure, conflict with customers, workplace discrimination, increased workload, and designation as an essential worker. Although about half of the participants in the sample said that their employers provided support to improve workers' mental health, the interviews suggest that more could be done. CONCLUSIONS: These findings may lead to opportunities to improve worker well-being during the COVID-19 pandemic and to prepare for future public health emergencies. Proposed strategies include implementing public health measures as advised by infectious disease experts; offering information and training; providing sick leave, long-term hazard pay, higher wages, and mental health benefits; and better distribution of workloads.

INTRODUCTION: The objective of this project was to investigate U.S. meat and poultry processing workers' knowledge of COVID-19, perceived ability to protect themselves from infection, and perspectives on COVID-19 vaccines to inform COVID-19 prevention efforts within this linguistically, racially, and ethnically diverse workforce. METHODS: Qualitative semi-structured in-depth interviews were conducted with Mexican, Central American, Congolese refugee, and Black or African American meat/poultry processing workers from Mississippi, Minnesota, Virginia, and Kentucky (N=40). Data were collected from December 5, 2020, to January 28, 2021. Interview audio was transcribed, and rapid qualitative data analysis was used to analyze transcripts. RESULTS: Most participants expressed receiving mixed messages about COVID-19 protection measures: they were told how to protect themselves (n=38), but workplace policies (such as lack of paid sick leave) often undermined their efforts. Participants who were asked about COVID-19 vaccines (n=31) were aware there were one or more vaccines available to protect them from COVID-19; one-third were eager to get vaccinated. CONCLUSIONS: Community-based efforts may consider supplementing large scale unified information campaigns in order to prevent mixed messages, address worker needs to accurately gauge the threat of illness to their families and communities and empower them to prevent infection.

Workers, particularly outdoor workers, are among the populations most disproportionately affected by climate-related hazards. However, scientific research and control actions to comprehensively address these hazards are notably absent. To assess this absence, a seven-category framework was developed in 2009 to characterize the scientific literature published from 1988 through 2008. Using this framework, a second assessment examined the literature published through 2014, and the current one examines literature from 2014 through 2021. The objectives were to present literature that updates the framework and related topics and increases awareness of the role of climate change in occupational safety and health. In general, there is substantial literature on worker hazards related to ambient temperatures, biological hazards, and extreme weather but less on air pollution, ultraviolet radiation, industrial transitions, and the built environment. There is growing literature on mental health and health equity issues related to climate change, but much more research is needed. The socioeconomic impacts of climate change also require more research. This study illustrates that workers are experiencing increased morbidity and mortality related to climate change. In all areas of climate-related worker risk, including geoengineering, research is needed on the causality and prevalence of hazards, along with surveillance to identify, and interventions for hazard prevention and control.

Despite significant improvements in occupational safety and health (OSH) over the past 50 years, there remain persistent inequities in the burden of injuries and illnesses. In this commen-tary, the authors assert that addressing these inequities, along with challenges associated with the fundamental reorganization of work, will require a more holistic approach that accounts for the social contexts within which occupational injuries and illnesses occur. A biopsychosocial approach explores the dynamic, multidirectional interactions between biological phenomena, psychological factors, and social contexts, and can be a tool for both deeper understanding of the social determinants of health and advancing health equity. This commentary suggests that reducing inequities will require OSH to adopt the biopsychosocial paradigm. Practices in at least three key areas will need to adopt this shift. Research that explicitly examines occupational health inequities should do more to elucidate the effects of social arrangements and the interaction of work with other social determinants on work-related risks, exposures, and outcomes. OSH studies regardless of focus should incorporate inclusive methods for recruitment, data collection, and analysis to reflect societal diversity and account for differing experiences of social conditions. OSH researchers should work across disciplines to integrate work into the broader health equity research agenda. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Current surveillance methods may not capture the full extent of COVID-19 spread in high-risk settings like food establishments. Thus, we propose a new method for surveillance that identifies COVID-19 cases among food establishment workers from news reports via web-scraping and natural language processing (NLP). First, we used web-scraping to identify a broader set of articles (n = 67,078) related to COVID-19 based on keyword mentions. In this dataset, we used an open-source NLP platform (ClarityNLP) to extract location, industry, case, and death counts automatically. These articles were vetted and validated by CDC subject matter experts (SMEs) to identify those containing COVID-19 outbreaks in food establishments. CDC and Georgia Tech Research Institute SMEs provided a human-labeled test dataset containing 388 articles to validate our algorithms. Then, to improve quality, we fine-tuned a pretrained RoBERTa instance, a bidirectional transformer language model, to classify articles containing ≥ 1 positive COVID-19 cases in food establishments. The application of RoBERTa decreased the number of articles from 67,078 to 1,112 and classified (≥ 1 positive COVID-19 cases in food establishments) articles with 88% accuracy in the human-labeled test dataset. Therefore, by automating the pipeline of web-scraping and COVID-19 case prediction using RoBERTa, we enable an efficient human in-the-loop process by which COVID-19 data could be manually collected from articles flagged by our model, thus reducing the human labor requirements. Furthermore, our approach could be used to predict and monitor locations of COVID-19 development by geography and could also be extended to other industries and news article datasets of interest. © 2021, Springer Nature Switzerland AG.