Using a Participatory Approach to Develop Research Priorities for Future Leaders in Cancer-Related Precision Public Health

Precision public health is an emerging discipline combining principles and frameworks of precision health with the goal of improving population health. The development of research priorities drawing on the strengths of precision and public health is critical to facilitate the growth of the discipline to improve health outcomes. We held an interactive workshop during a virtual conference bringing together early-career researchers across public health disciplines to identify research priorities in precision public health. The workshop participants discussed and voted to identify three priority areas for future research and capacity building including 1) enhancing equity and access to precision public health research and resources, 2) improving tools and metrics for evaluation and 3) applying principles of implementation science to support sustainable practices. Participants also developed future objectives for achieving each priority. Future efforts by working groups will continue the process of identifying, revising, and advancing critical research priorities to grow the impact of precision public health

Precision Public Health Initiatives in Cancer: Proceedings from the Transdisciplinary Conference for Future Leaders in Precision Public Health

Abstract Background Precision public health is an emergent field that requires transdisciplinary collaborations and leverages innovative approaches to improve population health. These opportunities have inspired a new generation of precision public health researchers. Despite burgeoning interest in precision public health, there are limited opportunities for researchers to convene and continue the momentum of this field. Methods The Transdisciplinary Conference for Future Leaders in Precision Public Health was the among the first events to bring together international researchers and practitioners to learn, network, and agenda set for the future of the field. The conference took place virtually on October 14 and 15, 2021. Results The conference spanned two days and featured a keynote address, speakers from public health disciplines who are international leaders in precision-based research, networking opportunities, a poster session, and research agenda setting activities. Conclusion The conference was a critical first step to creating a shared international conversation about precision public health, especially among early-stage investigators. This allowed attendees to continue building their individual skills and international collaborations to support the growth of the field of precision public health

Demographic Determinants and Geographical Variability of COVID-19 Vaccine Hesitancy in Underserved Communities

BACKGROUND: COVID-19 hospitalizations and deaths disproportionately affect underserved and minority populations, emphasizing that vaccine hesitancy can be an especially important public health risk factor in these populations. OBJECTIVE: To characterize COVID-19 vaccine hesitancy in underserved diverse populations. METHODS: The Minority and Rural Coronavirus Insights Study recruited a convenience sample of adults (ages ≥18, n=3,735) from Federally Qualified Health Centers in California, Midwest (Illinois/Ohio), Florida and Louisiana and collected baseline data in November 2020-April 2021. Vaccine hesitancy status was defined as responses no or undecided to the question Would you get a coronavirus vaccine, if it was available? ( yes categorized as not hesitant). The cross-sectional descriptive analyses and logistic regression models examined vaccine hesitancy prevalence by age, gender, race/ethnicity, and geography. The expected vaccine hesitancy estimates for the general population were calculated for the study counties using published county-level data. Crude associations with demographic characteristics within each region were assessed by the chi-squared test. The main effect model included age, gender, race/ethnicity, and geographical region to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Interactions between geography and each demographic characteristic were evaluated in separate models. RESULTS: The strongest vaccine hesitancy variability was by geographic region: in California 28.3% (26.5-31.1), the Midwest 36.1 % (32.1-40.2), Louisiana 59.1% (56.0-62.1), Florida 67.9% (65.0-70.8). The expected estimates for the general population were lower: 9.7% (California), 15.2 % (Midwest), 18.2% (Florida), and 27.0% (Louisiana). The demographic patterns also varied by geography. An inverted U-shape age pattern was found, with the highest prevalence among ages 25-34 in the Midwest (39.3%), Florida (79.5%,) and Louisiana (79.4%) (p \u3c0.05). Females were more hesitant than males in the Midwest (36.5% vs 23.9%), Florida (71.6% vs 59.4%), and Louisiana (66.5% vs. 46.4%) (p\u3c0.05). Racial/ethnic differences were found in California with the highest prevalence among non-Hispanic Black (45.8%) and in Florida with the highest among Hispanic (69.3%) participants (p\u3c0.05) but not in the Midwest and Louisiana. The main effect model confirmed the U-shape association with age: strongest association with age 25-34, OR=2.28 (1.74, 2.99). Statistical interactions of gender and race/ethnicity with the region were significant, following the pattern found by the crude analysis. The associations with the female gender were strongest in Florida and Louisiana: ORs were 7.83 (5.94, 10.33) and 6.04 (4.52, 8.06) compared to males in California, respectively. Compared to non-Hispanic White participants in California, the strongest associations were found with being Hispanic in Florida and Black in Louisiana: ORs were 11.18 (7.01, 17.85) and 8.94 (5.53, 14.47), respectively. However, the strongest race/ethnicity variability was observed within California and Florida: ORs varied 4.7- and 2-fold between racial/ethnic groups in these regions, respectively. CONCLUSIONS: These findings highlight the role of local contextual factors in driving vaccine hesitancy and its demographic patterns

Advancing genomics to improve health equity.

Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine

Advancing genomics to improve health equity.

Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine