Evidence map›Paper›PMID 32644119›Full record

ArticleThe Journal of infectious diseases2021

Sociodemographic, Ecological, and Spatiotemporal Factors Associated with Human Immunodeficiency Virus Drug Resistance in Florida: A Retrospective Analysis.

Shannan N Rich, Karalee Poschman, Hui Hu, Carla Mavian, Robert L Cook, Marco Salemi, Emma C Spencer, Mattia Prosperi

Open access · greenAbstract read
In one paragraph

Article in The Journal of infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.2field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Shannan N RichDepartment of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA.
Karalee PoschmanFlorida Department of Health, Division of Disease Control and Health Protection, Bureau of Communicable Diseases, HIV/AIDS Section, Tallahassee, Florida, USA.
Hui HuDepartment of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA.
Carla MavianEmerging Pathogens Institute, University of Florida, Gainesville, Florida, USA.
Robert L CookDepartment of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA.
Marco SalemiEmerging Pathogens Institute, University of Florida, Gainesville, Florida, USA.
Emma C SpencerFlorida Department of Health, Division of Disease Control and Health Protection, Bureau of Communicable Diseases, HIV/AIDS Section, Tallahassee, Florida, USA.
Mattia ProsperiDepartment of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, Florida, USA.
University of Florida · USCenters for Disease Control and Prevention · USFlorida Department of Health · US

Funding

Forecasting trajectories of HIV transmission networks with a novel phylodynamic and deep learning frameworkR01AI145552 · NIAID · UNIVERSITY OF FLORIDA · PI Simone Marini, Mattia Prosperi · 2020 to 2026
$3.6M
HIV Dynamic Modelling for Identification of Transmission Epicenters (HIV-DYNAMITE)R21AI138815 · NIAID · UNIVERSITY OF FLORIDA · PI PROSPERI, MATTIA, SALEMI, MARCO · 2018 to 2019
$419k
NIAID NIH HHS R01 AI145552NIAID NIH HHS R21 AI138815
6 · The paper itself

Abstract

backgroundPersons living with human immunodeficiency virus (HIV) with resistance to antiretroviral therapy are vulnerable to adverse HIV-related health outcomes and can contribute to transmission of HIV drug resistance (HIVDR) when nonvirally suppressed. The degree to which HIVDR contributes to disease burden in Florida-the US state with the highest HIV incidence- is unknown.

methodsWe explored sociodemographic, ecological, and spatiotemporal associations of HIVDR. HIV-1 sequences (n = 34 447) collected during 2012-2017 were obtained from the Florida Department of Health. HIVDR was categorized by resistance class, including resistance to nucleoside reverse-transcriptase , nonnucleoside reverse-transcriptase , protease , and integrase inhibitors. Multidrug resistance and transmitted drug resistance were also evaluated. Multivariable fixed-effects logistic regression models were fitted to associate individual- and county-level sociodemographic and ecological health indicators with HIVDR.

resultsThe HIVDR prevalence was 19.2% (nucleoside reverse-transcriptase inhibitor resistance), 29.7% (nonnucleoside reverse-transcriptase inhibitor resistance), 6.6% (protease inhibitor resistance), 23.5% (transmitted drug resistance), 13.2% (multidrug resistance), and 8.2% (integrase strand transfer inhibitor resistance), with significant variation by Florida county. Individuals who were older, black, or acquired HIV through mother-to-child transmission had significantly higher odds of HIVDR. HIVDR was linked to counties with lower socioeconomic status, higher rates of unemployment, and poor mental health.

conclusionsOur findings indicate that HIVDR prevalence is higher in Florida than aggregate North American estimates with significant geographic and socioecological heterogeneity.

Indexed as

Anti-HIV AgentsDrug Resistance, ViralHIV-1HIV InfectionsDNA-Directed RNA PolymerasesFloridaHumansInfectious Disease Transmission, VerticalMutationNucleosidesRetrospective StudiesReverse Transcriptase InhibitorsSociodemographic FactorsSpatio-Temporal AnalysisAnti-HIV AgentsDNA-Directed RNA PolymerasesNucleosidesReverse Transcriptase InhibitorsAntiretroviral therapyHIV drug resistanceHIV in the South

Identifiers

PMID32644119
PMCPMC7938178
OpenAlexW3040788964

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.