In the Spring of 2021, the COVID-19 vaccination was authorized for emergency use by the Food and Drug Administration. Healthcare workers (HCWs) are one of the most trusted sources of information for vaccination choices. However, HCWs at this time appeared to continue to have lower rates of COVID-19 vaccination uptake than expected in Arizona. The objective of this study was to examine factors that play a role in the vaccination decision-making process among Arizona HCWs. Between January and April 2021, 18 semi-structured interviews were conducted among physicians, emergency medical technicians and long-term care nurses in Pima County. The informed consent process was completed for each participant. The interview guide was informed by the Increasing Vaccination model to collect information on vaccination decision-making. A codebook was developed using an inductive approach. Coding and analysis was conducted using the software MAXQDA. Participants were primarily male (11/18, 61%) and white (11/18, 61%). Three participants identified as Hispanic. Initial themes that emerged included: mixed opinions concerning the innovations in COVID-19 vaccine development, access-related barriers, issues related to distribution inequities, concerns about misinformation and conspiracy theories, and dialogue concerning the benefits of requiring mandatory vaccination. The results gathered from this study indicate that there continues to be hesitancy among some healthcare professionals in Pima County. These results will be used to help Arizonan Health Departments promote rollout of novel vaccines more effectively through targeting relevant vaccination decision-making factors among HCWs.

Introduction: The Latinx population has the second highest COVID-19 death rate among racial/ethnic groups in the United States and less than half of Latinx youth aged 5–17 years old completed their COVID-19 primary vaccination series as of September 2022. COVID-19 vaccine misinformation detrimentally impacts vaccination rates. In this study, we examined factors that predicted Latinx youth COVID-19 vaccine hesitancy and vaccination status. Methods: A community-based sample of 290 Latinx parent and adolescent dyads from a Southwestern metropolitan area of the United States who were recruited to complete an online survey at baseline at T1 (August 2020 –March 2021) and one year later. We tested a longitudinal mediation model in which we examined individual and family factors that would predict youth COVID-19 vaccine hesitancy and vaccination status over time. Results: Youth’s pandemic disbelief (i.e., the belief that the COVID-19 pandemic is a conspiracy or not real) predicted greater youth’s COVID-19 vaccine hesitancy, and in turn, a lower likelihood of youth’s COVID-19 vaccination. Youth’s pandemic disbelief also predicted greater parent’s vaccination hesitancy which, in turn, predicted greater youth’s vaccination hesitancy and a lower likelihood of COVID-19 vaccination. Parents’ pandemic disbelief predicted their own COVID-19 hesitancy, but not youth hesitancy. Discussion: Our study findings provide initial evidence that general pandemic disbelief was a significant driver of vaccine hesitancy and vaccination among Latinx families. The study contributes to the limited research investigating COVID-19 vaccination in the Latinx community and among Latinx youth, further aiding how COVID-19 vaccine disparities can be mitigated among racial/ethnic populations.

Tobacco farm laborers are primarily women and children working for very low wages. The aim of this study was to explore occupational and reproductive health challenges faced by women tobacco farm laborers in Mysore District, India. We conducted interviews and six focus group discussions among 41 women tobacco farm laborers. Codes and themes were generated based on deductive and inductive approaches using the socioecological model. Participants reported symptoms of green tobacco sickness including headaches, back pain, gastric problems, weakness, and allergies during menstruation, pre-natal, and post-natal periods. Participants had poor awareness about the health effects of tobacco farming, and there were gender inequalities in wages and the use of personal protective equipment. Participants received support from family and community health workers during their pregnancy and post-natal period. Women reported wanting maternity benefits from the tobacco board, as well as monetary support and nutritional supplements. There is a need for health education about the environmental dangers of tobacco among farm laborers, and more supportive policies for women farmworkers during pregnancy and post-natal periods.

Background: Vaccine hesitancy has been ranked as one of the top 10 threats to global health by the World Health Organization. The 5C model (Confidence, Calculation of risk, Complacency, Collective Responsibility, and Constraints) and an accompanying tool to measure vaccine hesitancy, summarize several significant explanatory variables, and move beyond the most common explanatory variable, Confidence. Methods: From January to May 2021, we administered a cross-sectional survey among adults in Pima County, Arizona in collaboration with the local health department to assess psychological antecedents to (i.e., psychological factors that lead to) COVID-19 vaccination using the 5C Scale. Participants were recruited virtually for the survey using multiple recruitment methods. Unadjusted and adjusted hierarchical ordinal logistic regressions were conducted to determine if the 5C variables had an association with intention to vaccinate (or intent to vaccinate) against COVID-19. Results: Of the 1,823 participants who responded to the survey, 924 (76%) were included in the final analyses. Respondents were White (71%), non-Hispanic (59%), Female (68%), Liberal (37%) and Married (46%). The average age of the participants was 43.9 (±1.3) years. Based on the 5C Scale, Confidence (adjOR:3.64, CI [3.08–4.29]), Collective Responsibility (adjOR:1.94, CI [1.57–2.39]) and Complacency (adjOR:0.64, CI [0.51–0.80]) were significantly associated with intention to vaccinate against COVID-19. Conclusion: Three of the five 5C variables were associated with the intention to vaccinate, two positively and one negatively. A limitation of the study was that the sample was not weighted to be representative of Pima County. Future research should focus on determining which interventions can bolster Confidence and Collective Responsibility attitudes in communities, while dampening Complacency, to better promote vaccine uptake.

Background: In recent years, public health has confronted 2 formidable challenges: the devastating COVID-19 pandemic and the enduring threat of climate change. The convergence of these crises underscores the urgent need for resilient solutions. Resilience informatics (RI), an emerging discipline at the intersection of informatics and public health, leverages real-time data integration from health systems, environmental monitoring, and technological tools to develop adaptive responses to multifaceted crises. It offers promising avenues for mitigating and adapting to these challenges by proactively identifying vulnerabilities and fostering adaptive capacity in public health systems. Addressing critical questions regarding target audiences, privacy concerns, and scalability is paramount to fostering resilience in the face of evolving health threats. Objective: The University of Arizona held a workshop, titled Resilience Informatics in Public Health, in November 2023 to serve as a pivotal forum for advancing these discussions and catalyzing collaborative efforts within the field. This paper aims to present a qualitative thematic analysis of the findings from this workshop. Methods: A purposive sampling strategy was used to invite 40 experts by email from diverse fields, including public health, medicine, weather services, informatics, environmental science, and resilience, to participate in the workshop. The event featured presentations from key experts, followed by group discussions facilitated by experts. The attendees engaged in collaborative reflection and discussion on predetermined questions. Discussions were systematically recorded by University of Arizona students, and qualitative analysis was conducted. A detailed thematic analysis was performed using an inductive approach, supported by MAXQDA software to manage and organize data. Two independent researchers coded the transcripts; discrepancies in coding were resolved through consensus, ensuring a rigorous synthesis of the findings. Results: The workshop hosted 27 experts at the University of Arizona, 21 (78%) of whom were from public health–related fields. Of these 27 experts, 8 (30%) were from the field of resilience. In addition, participants from governmental agencies, American Indian groups, weather services, and a mobile health organization attended. Qualitative analysis identified major themes, including the potential of RI tools, threats to resilience (eg, health care access, infrastructure, and climate change), challenges with RI tools (eg, usability, funding, and real-time response), and standards for RI tools (eg, technological, logistical, and sociological). The attendees emphasized the importance of equitable access, community engagement, and iterative development in RI projects. Conclusions: The RI workshop emphasized the necessity for accessible, user-friendly tools bridging technical knowledge and community needs. The workshop’s conclusions provide a road map for future public health resilience, highlighting the need for scalable, culturally sensitive, community-driven interventions. Future directions include focused discussions to yield concrete outputs such as implementation guidelines and tool designs, reshaping public health strategies in the face of emerging threats.

Climate change, local epidemics, future pandemics, and forced displacements pose significant public health threats worldwide. To cope successfully, people and communities are faced with the challenging task of developing resilience to these stressors. Our viewpoint is that the powerful capabilities of modern informatics technologies including artificial intelligence, biomedical and environmental sensors, augmented or virtual reality, data science, and other digital hardware or software, have great potential to promote, sustain, and support resilience in people and communities. However, there is no “one size fits all” solution for resilience. Solutions must match the specific effects of the stressor, cultural dimensions, social determinants of health, technology infrastructure, and many other factors.