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Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model

INTRODUCTION: Social network strategies have been used by health departments to identify undiagnosed cases of HIV. Heterosexual cycle (HET4) of National HIV Behavioral Surveillance (NHBS) is a social network strategy implemented in jurisdictions. The main objectives of this research are to 1) evalua...

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Autores principales: Das, Suparna, Medina, Richard, Nicolosi, Emily, Agopian, Anya, Kuo, Irene, Opoku, Jenevieve, Allston, Adam, Kharfen, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297872/
https://www.ncbi.nlm.nih.gov/pubmed/34292969
http://dx.doi.org/10.1371/journal.pone.0253594
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author Das, Suparna
Medina, Richard
Nicolosi, Emily
Agopian, Anya
Kuo, Irene
Opoku, Jenevieve
Allston, Adam
Kharfen, Michael
author_facet Das, Suparna
Medina, Richard
Nicolosi, Emily
Agopian, Anya
Kuo, Irene
Opoku, Jenevieve
Allston, Adam
Kharfen, Michael
author_sort Das, Suparna
collection PubMed
description INTRODUCTION: Social network strategies have been used by health departments to identify undiagnosed cases of HIV. Heterosexual cycle (HET4) of National HIV Behavioral Surveillance (NHBS) is a social network strategy implemented in jurisdictions. The main objectives of this research are to 1) evaluate the utility of the NHBS HET cycle data for network analysis; 2) to apply statistical analysis in support of previous HIV research, as well as to develop new research results focused on demographic variables and prevention/intervention with respect to heterosexual HIV risk; and 3) to employ NHBS data to inform policy with respect to the EHE plan. METHOD: We used data from the 2016 NHBS HET4 (DC). A total of 747 surveys were collected. We used the free social-network analysis package, GEPHI, for all network visualization using adjacency matrix representation. We additionally conducted logistic regression analysis to examine the association of selected variables with HIV status in three models representing 1) demographic and economic effects, 2) behavioral effects, and 3) prevention-intervention effects. RESULTS: The results showed 3% were tested positive. Seed 1 initiated the largest networks with 426 nodes (15 positives); seed 4 with 273 nodes (6 positives). Seed 3 had 35 nodes (2 positives). All 23 HIV diagnoses were recruited from 4 zip-codes across DC. The risk of testing positive was higher among people high-school dropouts (Relative Risk (RR) (25.645); 95 CI% 5.699, 115.987), unemployed ((4.267); 1.295, 14.064), returning citizens ((14.319); 4.593, 44.645). We also found in the final model higher association of pre-exposure prophylaxis (PrEP) awareness among those tested negative ((4.783); 1.042, 21.944) and HIV intervention in the past 12 months with those tested positive ((17.887); 2.350,136.135). CONCLUSION: The network visualization was used to address the primary aim of the analysis-evaluate the success of the implementation of the NHBS as a social network strategy to find new diagnoses. NHBS remains one of the strongest behavioral supplements for DC’s HIV planning activities. As part of the evaluation process our analysis helps to understand the impact of demographic, behavioral, and prevention efforts on peoples’ HIV status. We strongly recommend other jurisdictions use network visualizations to evaluate the efficacy in reaching hidden populations.
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spelling pubmed-82978722021-07-31 Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model Das, Suparna Medina, Richard Nicolosi, Emily Agopian, Anya Kuo, Irene Opoku, Jenevieve Allston, Adam Kharfen, Michael PLoS One Research Article INTRODUCTION: Social network strategies have been used by health departments to identify undiagnosed cases of HIV. Heterosexual cycle (HET4) of National HIV Behavioral Surveillance (NHBS) is a social network strategy implemented in jurisdictions. The main objectives of this research are to 1) evaluate the utility of the NHBS HET cycle data for network analysis; 2) to apply statistical analysis in support of previous HIV research, as well as to develop new research results focused on demographic variables and prevention/intervention with respect to heterosexual HIV risk; and 3) to employ NHBS data to inform policy with respect to the EHE plan. METHOD: We used data from the 2016 NHBS HET4 (DC). A total of 747 surveys were collected. We used the free social-network analysis package, GEPHI, for all network visualization using adjacency matrix representation. We additionally conducted logistic regression analysis to examine the association of selected variables with HIV status in three models representing 1) demographic and economic effects, 2) behavioral effects, and 3) prevention-intervention effects. RESULTS: The results showed 3% were tested positive. Seed 1 initiated the largest networks with 426 nodes (15 positives); seed 4 with 273 nodes (6 positives). Seed 3 had 35 nodes (2 positives). All 23 HIV diagnoses were recruited from 4 zip-codes across DC. The risk of testing positive was higher among people high-school dropouts (Relative Risk (RR) (25.645); 95 CI% 5.699, 115.987), unemployed ((4.267); 1.295, 14.064), returning citizens ((14.319); 4.593, 44.645). We also found in the final model higher association of pre-exposure prophylaxis (PrEP) awareness among those tested negative ((4.783); 1.042, 21.944) and HIV intervention in the past 12 months with those tested positive ((17.887); 2.350,136.135). CONCLUSION: The network visualization was used to address the primary aim of the analysis-evaluate the success of the implementation of the NHBS as a social network strategy to find new diagnoses. NHBS remains one of the strongest behavioral supplements for DC’s HIV planning activities. As part of the evaluation process our analysis helps to understand the impact of demographic, behavioral, and prevention efforts on peoples’ HIV status. We strongly recommend other jurisdictions use network visualizations to evaluate the efficacy in reaching hidden populations. Public Library of Science 2021-07-22 /pmc/articles/PMC8297872/ /pubmed/34292969 http://dx.doi.org/10.1371/journal.pone.0253594 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Das, Suparna
Medina, Richard
Nicolosi, Emily
Agopian, Anya
Kuo, Irene
Opoku, Jenevieve
Allston, Adam
Kharfen, Michael
Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model
title Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model
title_full Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model
title_fullStr Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model
title_full_unstemmed Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model
title_short Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model
title_sort ending the hiv epidemic using national hiv behavioral surveillance (nhbs): recommendations based on dc model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8297872/
https://www.ncbi.nlm.nih.gov/pubmed/34292969
http://dx.doi.org/10.1371/journal.pone.0253594
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