Evidence map›Paper›PMID 38459461›Full record

ArticleBMC public health2024

Spatial and temporal analysis of HIV clinical outcomes in Florida reveals counties with persistent racial and ethnic disparities during 2012-2019.

Shannan N Rich, Yiyang Liu, Rebecca Fisk-Hoffman, Yi Zheng, Hui Hu, Emma E Spencer, Robert L Cook, Mattia Prosperi

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 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 5 institutions in 1 country.

Shannan N Rich *Department of Epidemiology, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL, 32603, USA.
Yiyang Liu *Department of Epidemiology, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL, 32603, USA. yliu26@ufl.edu.
Rebecca Fisk-HoffmanDepartment of Epidemiology, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL, 32603, USA.
Yi ZhengChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Hui HuChanning Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA.
Emma E SpencerFlorida Department of Health, Division of Disease Control and Health Protection, Bureau of Communicable Diseases, HIV/AIDS Section, Tallahassee, FL, 32399, USA.
Robert L CookDepartment of Epidemiology, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL, 32603, USA.
Mattia ProsperiDepartment of Epidemiology, Colleges of Public Health and Health Professions and Medicine, University of Florida, Gainesville, FL, 32603, USA.
University of Florida · USBrigham and Women's Hospital · USFlorida College · USFlorida Department of Health · USHarvard University · 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
Artificial Intelligence and Counterfactually Actionable Responses to End HIV (AI-CARE-HIV)R01AI172875 · NIAID · UNIVERSITY OF FLORIDA · PI Jiang Bian, Mattia Prosperi · 2023 to 2026
$2.8M
NIAID NIH HHS R01 AI145552NIAID NIH HHS R01 AI172875
6 · The paper itself

Abstract

backgroundRacial/ethnic disparities in the HIV care continuum have been well documented in the US, with especially striking inequalities in viral suppression rates between White and Black persons with HIV (PWH). The South is considered an epicenter of the HIV epidemic in the US, with the largest population of PWH living in Florida. It is unclear whether any disparities in viral suppression or immune reconstitution-a clinical outcome highly correlated with overall prognosis-have changed over time or are homogenous geographically. In this analysis, we 1) investigate longitudinal trends in viral suppression and immune reconstitution among PWH in Florida, 2) examine the impact of socio-ecological factors on the association between race/ethnicity and clinical outcomes, 3) explore spatial and temporal variations in disparities in clinical outcomes.

methodsData were obtained from the Florida Department of Health for 42,369 PWH enrolled in the Ryan White program during 2008-2020. We linked the data to county-level socio-ecological variables available from County Health Rankings. GEE models were fit to assess the effect of race/ethnicity on immune reconstitution and viral suppression longitudinally. Poisson Bayesian hierarchical models were fit to analyze geographic variations in racial/ethnic disparities while adjusting for socio-ecological factors.

resultsProportions of PWH who experienced viral suppression and immune reconstitution rose by 60% and 45%, respectively, from 2008-2020. Odds of immune reconstitution and viral suppression were significantly higher among White [odds ratio =2.34, 95% credible interval=2.14-2.56; 1.95 (1.85-2.05)], and Hispanic [1.70 (1.54-1.87); 2.18(2.07-2.31)] PWH, compared with Black PWH. These findings remained unchanged after accounting for socio-ecological factors. Rural and urban counties in north-central Florida saw the largest racial/ethnic disparities.

conclusionsThere is persistent, spatially heterogeneous, racial/ethnic disparity in HIV clinical outcomes in Florida. This disparity could not be explained by socio-ecological factors, suggesting that further research on modifiable factors that can improve HIV outcomes among Black and Hispanic PWH in Florida is needed.

Indexed as

EthnicityHIV InfectionsBayes TheoremBlack or African AmericanFloridaHealthcare DisparitiesHispanic or LatinoHumansWhiteClinical outcomesHIVHIV in the SouthRacial disparitiesSpatial-temporal epidemiology

Identifiers

PMID38459461
PMCPMC10924316
OpenAlexW4392764285

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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.