Multilevel regression models of overall and gender stratified 5-year HIV diagnoses rates.

Overall, male and female 5-year HIV diagnoses rates and independent variables by city.

Univariate negative binomial regression models of 5-year overall, male and female HIV diagnoses rates.

Spearman correlations among independent covariates and overall, male, and female 5-year HIV diagnoses rates.

The purpose of this study was to contribute to the conceptual understanding and practical application of social integration theory to health behaviors. The research aimed to investigate the protective effects of community involvement in HIV/AIDS and gay-related organizations for HIV/AIDS sexual risk behavior among Latino gay or bisexual men and transgender individuals in Chicago and San Francisco. As part of this, the study examined HIV prevalence and the socioeconomic correlates of HIV infection, sexual risk behaviors, and substance use. Further, the study tested whether community involvement in AIDS and LGBT organizations moderated the relationship of racial and homosexual stigma to sexual risk behavior. Data were collected from a sample of 643 individuals (Chicago: n=320; San Francisco: n=323) through respondent-driven sampling and computer-assisted self-administered interviews. Demographic variables included ethnic identification, sexual identification, ZIP code (only available in restricted use data), country of birth, years in the United States, employment status, income, family religion, age, and health/STD status.

BackgroundWashington DC has a high burden of HIV with a 2.0% HIV prevalence. The city is a national and international hub potentially containing a broad diversity of HIV variants; yet few sequences from DC are available on GenBank to assess the evolutionary history of HIV in the US capital. Towards this general goal, here we analyze extensive sequence data and investigate HIV diversity, phylodynamics, and drug resistant mutations (DRM) in DC.MethodsMolecular HIV-1 sequences were collected from participants infected through 2015 as part of the DC Cohort, a longitudinal observational study of HIV+ patients receiving care at 13 DC clinics. Sequences were paired with Cohort demographic, risk, and clinical data and analyzed using maximum likelihood, Bayesian and coalescent approaches of phylogenetic, network and population genetic inference. We analyzed 601 sequences from 223 participants for int (~864 bp) and 2,810 sequences from 1,659 participants for PR/RT (~1497 bp).ResultsNinety-nine and 94% of the int and PR/RT sequences, respectively, were identified as subtype B, with 14 non-B subtypes also detected. Phylodynamic analyses of US born infected individuals showed that HIV population size varied little over time with no significant decline in diversity. Phylogenetic analyses grouped 13.5% of the int sequences into 14 clusters of 2 or 3 sequences, and 39.0% of the PR/RT sequences into 203 clusters of 2–32 sequences. Network analyses grouped 3.6% of the int sequences into 4 clusters of 2 sequences, and 10.6% of the PR/RT sequences into 76 clusters of 2–7 sequences. All network clusters were detected in our phylogenetic analyses. Higher proportions of clustered sequences were found in zip codes where HIV prevalence is highest (r = 0.607; P<0.00001). We detected a high prevalence of DRM for both int (17.1%) and PR/RT (39.1%), but only 8 int and 12 PR/RT amino acids were identified as under adaptive selection. We observed a significant (P<0.0001) association between main risk factors (men who have sex with men and heterosexuals) and genotypes in the five well-supported clusters with sufficient sample size for testing.DiscussionPairing molecular data with clinical and demographic data provided novel insights into HIV population dynamics in Washington, DC. Identification of populations and geographic locations where clustering occurs can inform and complement active surveillance efforts to interrupt HIV transmission.

ObjectiveWe identified potential geographic “hotspots” for drug-injecting transmission of HIV and hepatitis C virus (HCV) among persons who inject drugs (PWID) in New York City. The HIV epidemic among PWID is currently in an “end of the epidemic” stage, while HCV is in a continuing, high prevalence (> 50%) stage.MethodsWe recruited 910 PWID entering Mount Sinai Beth Israel substance use treatment programs from 2011–2015. Structured interviews and HIV/ HCV testing were conducted. Residential ZIP codes were used as geographic units of analysis. Potential “hotspots” for HIV and HCV transmission were defined as 1) having relatively large numbers of PWID 2) having 2 or more HIV (or HCV) seropositive PWID reporting transmission risk—passing on used syringes to others, and 3) having 2 or more HIV (or HCV) seronegative PWID reporting acquisition risk—injecting with previously used needles/syringes. Hotspots for injecting drug use initiation were defined as ZIP codes with 5 or more persons who began injecting within the previous 6 years.ResultsAmong PWID, 96% injected heroin, 81% male, 34% White, 15% African-American, 47% Latinx, mean age 40 (SD = 10), 7% HIV seropositive, 62% HCV seropositive. Participants resided in 234 ZIP codes. No ZIP codes were identified as potential hotspots due to small numbers of HIV seropositive PWID reporting transmission risk. Four ZIP codes were identified as potential hotspots for HCV transmission. 12 ZIP codes identified as hotspots for injecting drug use initiation.DiscussionFor HIV, the lack of potential hotspots is further validation of widespread effectiveness of efforts to reduce injecting-related HIV transmission. Injecting-related HIV transmission is likely to be a rare, random event. HCV prevention efforts should include focus on potential hotspots for transmission and on hotspots for initiation into injecting drug use. We consider application of methods for the current opioid epidemic in the US.

HCV prevalence by years injecting.

BackgroundTuberculosis (TB) is caused by members of the Mycobacterium tuberculosis complex (MTBC). Although the MTBC is highly clonal, between-strain genetic diversity has been observed. In low TB incidence settings, immigration may facilitate the importation of MTBC strains with a potential to complicate TB control efforts.MethodsWe investigated the genetic diversity and spatiotemporal clustering of 2,510 MTBC strains isolated in Florida, United States, between 2009 and 2013 and genotyped using spoligotyping and 24-locus MIRU-VNTR. We mapped the genetic diversity to the centroid of patient residential zip codes using a geographic information system (GIS). We assessed transmission dynamics and the influence of immigration on genotype clustering using space-time permutation models adjusted for foreign-born population density and county-level HIV risk and multinomial models stratified by country of birth and timing of immigration in SaTScan.Principal FindingsAmong the 2,510 strains, 1,245 were reported among foreign-born persons; including 408 recent immigrants (

Characteristics of Cases inside the Multinomial Haarlem Clusters.

Characteristics of Genotyped Tuberculosis Cases in Florida, 2009–2013.