Syphilis infection has recently resurfaced as a significant public health problem. Although there has been a tremendous amount of research on the epidemiology of syphilis, there has been limited work done to synthesize the extensive body of research and systematically estimate patterns of disease within high-risk groups in the Americas. The purpose of this systematic review and meta-analysis is to (1) summarize recent patterns of syphilis infection in North and South America among four high-risk groups (MSM, transgender women, sex workers, and incarcerated individuals) from 1980 to 2016, (2) identify and differentiate regional geographic epidemiologic characteristics, and (3) compare the epidemics of the economically developed countries of North America from the developing countries and public health systems of Latin America and the Caribbean. Primary studies reporting syphilis prevalence and/or incidence in at least one of the four high-risk groups will be identified from Medline/PubMed, Embase, Lilacs, SciELO, The Cochrane Library, Web of Science, Scopus, ProQuest, CINAHL, Clase, and Periódica, as well as “gray” literature sources (conference abstracts, country reports, etc.). Studies published from 1980 through 2016 will be included. Data will be extracted from studies meeting inclusion and exclusion criteria and a random effects meta-analysis of prevalence and incidence estimates will be conducted. Heterogeneity, risk of bias, and publication bias will be assessed. Pooled prevalence and incidence estimates will be calculated for comparisons based on geographic region, risk factors, and time period. Our systematic review and meta-analysis aims to contribute to an improved understanding of global epidemiologic patterns of syphilis infection in most-at-risk populations. Through systematic classification of the existing literature, and comparison of disease patterns across regional, temporal and socio-behavioral differences, we hope to improve public health surveillance and improve efforts to control the spread of disease across the Americas. PROSPERO CRD42016047306.

Non-disclosure of human immunodeficiency virus (HIV) status can hinder optimal health outcomes for people living with HIV (PLHIV). We sought to explore experiences with and correlates of disclosure among PLHIV participating in a study of population mobility. Survey data were collected from 1081 PLHIV from 2015–16 in 12 communities in Kenya and Uganda participating in a test-and-treat trial (SEARCH, NCT#01864603). Pooled and sex-stratified multiple logistic regression models examined associations of disclosure with risk behaviors controlling for covariates and community clustering. At baseline, 91.0% (n = 984) of PLHIV had disclosed their serostatus. Amongst those who had never disclosed, 31% feared abandonment (47.4% men vs. 15.0% women; p = 0.005). Non-disclosure was associated with no condom use in the past 6 months (aOR = 2.44; 95%CI, 1.40–4.25) and with lower odds of receiving care (aOR = 0.8; 95%CI, 0.04–0.17). Unmarried versus married men had higher odds of non- disclosure (aOR = 4.65, 95%CI, 1.32–16.35) and no condom use in the past 6 months (aOR = 4.80, 95%CI, 1.74–13.20), as well as lower odds of receiving HIV care (aOR = 0.15; 95%CI, 0.04–50 0.49). Unmarried versus married women had higher odds of non-disclosure (aOR = 3.14, 95%CI, 1.47–6.73) and lower odds of receiving HIV care if they had never disclosed (aOR = 0.05, 95%CI, 0.02–0.14). Findings highlight gender differences in barriers to HIV disclosure, use of condoms, and engagement in HIV care. Interventions focused on differing disclosure support needs for women and men are needed and may help facilitate better care engagement for men and women and improve condom use in men.

In San Francisco (SF), many environmental factors drive the unequal burden of preterm birth outcomes for communities of color. Here, we examine the association between human exposure to lead (Pb) and preterm birth (PTB) in 19 racially diverse SF zip codes. Pb concentrations were measured in 109 hair samples donated by 72 salons and barbershops in 2018–2019. Multi-method data collection included randomly selecting hair salons stratified by zip code, administering demographic surveys, and measuring Pb in hair samples as a biomarker of environmental exposure to heavy metals. Concentrations of Pb were measured by atomic emission spectrometry. Aggregate neighborhood Pb levels were linked to PTB and demographic data using STATA 16 SE (StataCorp LLC, College Station, TX, USA). Pb varied by zip code (p < 0.001) and correlated with PTB (p < 0.01). Increases in unadjusted Pb concentration predicted an increase in PTB (β = 0.003; p < 0.001) and after adjusting for poverty (β = 0.002; p < 0.001). Confidence intervals contained the null after further adjustment for African American/Black population density (p = 0.16), suggesting that race is more indicative of high rates of PTB than poverty. In conclusion, Pb was found in every hair sample collected from SF neighborhoods. The highest concentrations were found in predominately African American/Black and high poverty neighborhoods, necessitating public health guidelines to eliminate this environmental injustice.

Since 2015, we have run a free 9-week summer program that provides non-computer science (CS) undergraduates at San Francisco State University (SFSU) with experience in coding and doing research. Undergraduate research experiences remain very limited at SFSU and elsewhere, so the summer program provides opportunities for many more students beyond the mentoring capacity of our university laboratories. In addition, we were concerned that many students from historically underrepresented (HU) groups may be unable to take advantage of traditional summer research programs because these programs require students to relocate or be available full time, which is not feasible for students who have family, work, or housing commitments. Our program, which is local and part-time, serves about 5 times as many students as a typical National Science Foundation (NSF) Research Experiences for Undergraduates (REU) program, on a smaller budget. Based on our experiences, we present 10 simple rules for busy faculty who want to create similar programs to engage non-CS HU undergraduates in computational research. Note that while some of the strategies we implement are based on evidence-based publications in the social sciences or education research literature, the original suggestions we make here are based on our trial-and-error experiences, rather than formal hypothesis testing.

The Pregnancy Village (PV) was created to deliver cross-sector services at a convenient time and location for Black pregnant and postpartum people. This study examines the accessibility and acceptability of PV among pregnant individuals and their families. We surveyed 116 participants (57 pregnant/postpartum individuals and 59 family members) and conducted 18 semi-structured interviews between July 2021 and June 2022. Accessibility was measured using a 3-item scale and acceptability with a 7-item scale based on the Theoretical Framework of Acceptability; scores were standardized to a 0-100 range. Descriptive, bivariate, and multivariate analyses were conducted, along with framework analysis of qualitative data. Mean accessibility was 76.0 ( SD =21.0), with mixed qualitative perspectives. Acceptability was high ( M =91.9, SD =14.4), though lower among participants reporting prenatal care discrimination. Qualitative findings supported high acceptability, highlighting PV’s welcoming, supportive atmosphere. Findings suggest PV is accessible and acceptable, with continued model iteration critical for ensuring community priorities and sustainability.