Dataset Information

Early Presence of HIV-1 Subtype C in Washington, D.C.

ABSTRACT: The presence of non-B HIV subtypes in the USA has been documented during the epidemic, although the timing of early introductions of different subtypes remains uncertain. Subtype C, the most common HIV variant worldwide, was first reported in the USA in 1996-97, after subtype C had expanded greatly in sub-Saharan Africa. In this study, we report a patient with subtype C infection acquired by mother-to-child transmission, born in the USA in 1990 to a Washington, D.C. resident who never traveled outside the USA, demonstrating that subtype C was present in the USA much earlier. Comparative analysis of the sequence from this patient and subtype C sequences in the USA and elsewhere suggest multiple independent introductions of this subtype into the USA have taken place, many of which are traced to sub-Saharan or East Africa. These data indicate subtype C HIV was already present in the USA years earlier than previously reported, and during the early period of subtype C expansion.

SUBMITTER: Grossman Z

PROVIDER: S-EPMC6080110 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Early Presence of HIV-1 Subtype C in Washington, D.C.

Grossman Zehava Z Rico Sheryl-Vi SV Cone Katherine K Shao Wei W Rehm Catherine C Jones Sara S Bozzi Giorgio G Dean Sophie S Dewar Robin R Rehman Tauseef T Purdy Julia J Hadigan Colleen C Pau Alice K AK Maldarelli Frank F

AIDS research and human retroviruses 20180801 8

The presence of non-B HIV subtypes in the USA has been documented during the epidemic, although the timing of early introductions of different subtypes remains uncertain. Subtype C, the most common HIV variant worldwide, was first reported in the USA in 1996-97, after subtype C had expanded greatly in sub-Saharan Africa. In this study, we report a patient with subtype C infection acquired by mother-to-child transmission, born in the USA in 1990 to a Washington, D.C. resident who never traveled o ...[more]

PMID: 29936863

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Project description:Justice-involved (JI) populations bear a disproportionate burden of HIV infection and are at risk of poor treatment outcomes. Drug resistance prevalence and emergence, and phylogenetic inference of transmission networks, understudied in vulnerable JI populations, can inform care and prevention interventions, particularly around the critical community reentry period. We analyzed banked blood specimens from CARE+ Corrections study participants in Washington, D.C. (DC) across three time points and conducted HIV drug resistance testing using next-generation sequencing (NGS) at 20% and 5% thresholds to identify prevalent and evolving resistance during community reentry. Phylogenetic analysis was used to identify molecular clusters within participants, and in an extended analysis between participants and publicly available DC sequences. HIV sequence data from 54 participants (99 specimens) were analyzed. The prevalence of transmitted drug resistance was 14% at both thresholds, and acquired drug resistance was 47% at 20%, and 57% at 5% NGS thresholds, respectively. The overall prevalence of drug resistance was 43% at 20%, and 52% at 5% NGS thresholds, respectively. Among 34 participants sampled longitudinally, 21%-35% accumulated 10-17 new resistance mutations during a mean 4.3 months. In phylogenetic analysis within the JI population, 11% were found in three molecular clusters. The extended phylogenetic analysis identified 46% of participants in 22 clusters, of which 21 also included publicly-available DC sequences, and one JI-only unique dyad. This is the first study to identify a high prevalence of HIV drug resistance and its accumulation in a JI population during community reentry and suggests phylogenetic integration of this population into the non-JI DC HIV community. These data support the need for new, effective, and timely interventions to improve HIV treatment during this vulnerable period, and for JI populations to be included in broader surveillance and prevention efforts.

Project description:The COVID-19 pandemic and its associated mitigation strategies have significant psychosocial, behavioral, socioeconomic, and health impacts, particularly in vulnerable US populations. Different factors have been identified as influencers of the transmission rate; however, the effects of area deprivation index (as a measure of social determinants of health, SDoH) as a factor on COVID-19 disease early dynamics have not been established. We determined the effects of area deprivation index (ADI) and demographic factors on COVID-19 outcomes in Washington, D.C. This retrospective study used publicly available data on COVID-19 cases and mortality of Washington, D.C., during March 31st-July 4th, 2020. The main predictors included area deprivation index (ADI), age, and race/ethnicity. The ADI of each census block groups in D.C. (n=433) were obtained from Neighborhood Atlas map. Using a machine learning-based algorithm, the outcome variables were partitioned into time intervals: time duration (Pi, days), rate of change coefficient (Ei), and time segment load (Pi×Ei) for transmission rate and mortality. Correlation analysis and multiple linear regression models were used to determine associations between predictors and outcome variables. COVID-19 early transmission rate (E1) was highly correlated with ADI (SDoH; r= 0.88, p=0.0044) of the Washington, D.C. community. We also found positive association between ADI, age (0-17 years, r=0.91, p=0.0019), and race (African American/Black, r=0.86; p=0.0068) and COVID-19 outcomes. There was high variability in early transmission across the geographic regions (i.e., wards) of Washington, D.C., and this variability was driven by race/ethnic composition and ADI. Understanding the association of COVID-19 disease early transmission and mortality dynamics and key socio-demographic risk factors such as age, race, and ADI, as a measure of social determinants, will contribute to health equity/equality and distribution of economic resources/assistance and is essential for future predictive modeling of the COVID-19 pandemic to limit morbidity and mortality.

Dataset Information

Early Presence of HIV-1 Subtype C in Washington, D.C.

Publications

Early Presence of HIV-1 Subtype C in Washington, D.C.

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