Despite the high efficacy of pre-exposure prophylaxis (PrEP) in preventing HIV acquisition, PrEP uptake among Black cisgender women remains low. Our qualitative study assessed Black cisgender women’s perspectives, attitudes, and acceptability towards PrEP, in addition to exploring PrEP-related attitudes, facilitators, and barriers to PrEP access among health care staff. This study was conducted to ascertain data to inform the development of our HIV prevention app—Savvy HER—which is being designed for Black cisgender women. Our findings indicated that Black women had low levels of PrEP acceptability and high levels of misconceptions, inaccurate knowledge, and stigma towards PrEP. Health care providers in our sample confirmed barriers of stigma, misconceptions, and knowledge among their patients coupled with difficulty accessing PrEP due to structural barriers. Our study indicated that there is a critical need to heighten Black cisgender women’s PrEP knowledge and HIV risk perception in order to increase PrEP acceptability and uptake.

Background: Advancements in next-generation sequencing have allowed for a more complete understanding of the vaginal microbiome and its role in health and disease. The role of race/ethnicity in the composition of the vaginal microbiome and what is deemed normal/healthy microbiome is conflicting. Thus, the purpose of this review is to synthesize research that investigated the vaginal microbiome in Black women in the United States by using advanced 16S analysis. Methods: Searches of Pubmed, Google Scholar, and relevant journals for publications between January 2008 and July 2018 were conducted. Eligibility criteria were that the study: (1) used a molecular technique for sequencing of the vaginal microbiome, (2) reported the microbiome by race/ethnicity that included Black women, and (3) was conducted in the United States. Results: Our review selected 18 manuscripts that met the inclusion criteria for full review. Three themes emerged: the vaginal microbiome in healthy women versus women with bacterial vaginosis (BV); vaginal microbiome considerations in HIV; and vaginal microbiome considerations in preterm labor/birth. Overall, our review found that a majority of Black women (including HIV-positive women) have a Lactobacillus dominant group. Specifically, Lactobacillus iners was the most frequently reported Lactobacillus species. Non- Lactobacillus dominant groups were also reported to be found in healthy asymptomatic Black women. The vaginal microbiome's influence on preterm labor and/or birth among Black women was inconclusive and warrants further investigation. Conclusions: The role that the microbiome plays in health and disease among Black women warrants further research to better elucidate the definition of a healthy versus pathogenic microbiome. The wide variability in methods for BV diagnostics and defining preterm labor/birth are significant limitations that should be considered when conducting comparative studies.

Background: Cloud computing for microbiome data sets can significantly increase working efficiencies and expedite the translation of research findings into clinical practice. The Amazon Web Services (AWS) cloud provides an invaluable option for microbiome data storage, computation, and analysis. Objective: The goals of this study were to develop a microbiome data analysis pipeline by using AWS cloud and to conduct a proof-of-concept test for microbiome data storage, processing, and analysis. Methods: A multidisciplinary team was formed to develop and test a reproducible microbiome data analysis pipeline with multiple AWS cloud services that could be used for storage, computation, and data analysis. The microbiome data analysis pipeline developed in AWS was tested by using two data sets: 19 vaginal microbiome samples and 50 gut microbiome samples. Results: Using AWS features, we developed a microbiome data analysis pipeline that included Amazon Simple Storage Service for microbiome sequence storage, Linux Elastic Compute Cloud (EC2) instances (ie, servers) for data computation and analysis, and security keys to create and manage the use of encryption for the pipeline. Bioinformatics and statistical tools (ie, Quantitative Insights Into Microbial Ecology 2 and RStudio) were installed within the Linux EC2 instances to run microbiome statistical analysis. The microbiome data analysis pipeline was performed through command-line interfaces within the Linux operating system or in the Mac operating system. Using this new pipeline, we were able to successfully process and analyze 50 gut microbiome samples within 4 hours at a very low cost (a c4.4xlarge EC2 instance costs $0.80 per hour). Gut microbiome findings regarding diversity, taxonomy, and abundance analyses were easily shared within our research team. Conclusions: Building a microbiome data analysis pipeline with AWS cloud is feasible. This pipeline is highly reliable, computationally powerful, and cost effective. Our AWS-based microbiome analysis pipeline provides an efficient tool to conduct microbiome data analysis.

Background: When the COVID-19 pandemic hit in 2020, researchers in the P30 Center for the Study of Symptom Science, Metabolomics, and Multiple Chronic Conditions at Emory University’s Nell Hodgson Woodruff School of Nursing faced major challenges in recruitment and data collection because of limited access to the clinic and community facilities and the risk of COVID-19 exposure associated with in-person study contact. Objectives: The purpose of this article is to (a) describe how a cadre of pilot/supplement principal investigators adapted their studies to allow for safe and trustworthy data collection during the COVID-19 pandemic (March 2020 through date of publication) and (b) discuss steps that facilitated the technical aspects of remote data collection, especially involving biological specimens. Results: Four pilot studies and two administrative supplements within the center—all at different stages of execution—adopted various alternative remote recruitment, enrollment, and data and specimen collection approaches to continue their research endeavors in a way that maximized the safety of both the research participants and the research teams. Discussion: The article concludes with a discussion on the importance of a participant-centered approach when using remote methods, actions, or steps initiated to facilitate the technical aspects of remote data collection and reflections on the continued use of remote research strategies beyond the COVID-19 pandemic.