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Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs
Human Immunodeficiency Virus (HIV) interventions among people who use drugs (PWUD) often have spillover, also known as interference or dissemination, which occurs when one participant’s exposure affects another participant’s outcome. PWUD are often members of networks defined by social, sexual, and...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967280/ https://www.ncbi.nlm.nih.gov/pubmed/36839598 http://dx.doi.org/10.3390/pathogens12020326 |
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author | Buchanan, Ashley L. Katenka, Natallia Lee, Youjin Wu, Jing Pantavou, Katerina Friedman, Samuel R. Halloran, M. Elizabeth Marshall, Brandon D. L. Forastiere, Laura Nikolopoulos, Georgios K. |
author_facet | Buchanan, Ashley L. Katenka, Natallia Lee, Youjin Wu, Jing Pantavou, Katerina Friedman, Samuel R. Halloran, M. Elizabeth Marshall, Brandon D. L. Forastiere, Laura Nikolopoulos, Georgios K. |
author_sort | Buchanan, Ashley L. |
collection | PubMed |
description | Human Immunodeficiency Virus (HIV) interventions among people who use drugs (PWUD) often have spillover, also known as interference or dissemination, which occurs when one participant’s exposure affects another participant’s outcome. PWUD are often members of networks defined by social, sexual, and drug-use partnerships and their receipt of interventions can affect other members in their network. For example, HIV interventions with possible spillover include educational training about HIV risk reduction, pre-exposure prophylaxis, or treatment as prevention. In turn, intervention effects frequently depend on the network structure, and intervention coverage levels and spillover can occur even if not measured in a study, possibly resulting in an underestimation of intervention effects. Recent methodological approaches were developed to assess spillover in the context of network-based studies. This tutorial provides an overview of different study designs for network-based studies and related methodological approaches for assessing spillover in each design. We also provide an overview of other important methodological issues in network studies, including causal influence in networks and missing data. Finally, we highlight applications of different designs and methods from studies of PWUD and conclude with an illustrative example from the Transmission Reduction Intervention Project (TRIP) in Athens, Greece. |
format | Online Article Text |
id | pubmed-9967280 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99672802023-02-26 Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs Buchanan, Ashley L. Katenka, Natallia Lee, Youjin Wu, Jing Pantavou, Katerina Friedman, Samuel R. Halloran, M. Elizabeth Marshall, Brandon D. L. Forastiere, Laura Nikolopoulos, Georgios K. Pathogens Tutorial Human Immunodeficiency Virus (HIV) interventions among people who use drugs (PWUD) often have spillover, also known as interference or dissemination, which occurs when one participant’s exposure affects another participant’s outcome. PWUD are often members of networks defined by social, sexual, and drug-use partnerships and their receipt of interventions can affect other members in their network. For example, HIV interventions with possible spillover include educational training about HIV risk reduction, pre-exposure prophylaxis, or treatment as prevention. In turn, intervention effects frequently depend on the network structure, and intervention coverage levels and spillover can occur even if not measured in a study, possibly resulting in an underestimation of intervention effects. Recent methodological approaches were developed to assess spillover in the context of network-based studies. This tutorial provides an overview of different study designs for network-based studies and related methodological approaches for assessing spillover in each design. We also provide an overview of other important methodological issues in network studies, including causal influence in networks and missing data. Finally, we highlight applications of different designs and methods from studies of PWUD and conclude with an illustrative example from the Transmission Reduction Intervention Project (TRIP) in Athens, Greece. MDPI 2023-02-15 /pmc/articles/PMC9967280/ /pubmed/36839598 http://dx.doi.org/10.3390/pathogens12020326 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Tutorial Buchanan, Ashley L. Katenka, Natallia Lee, Youjin Wu, Jing Pantavou, Katerina Friedman, Samuel R. Halloran, M. Elizabeth Marshall, Brandon D. L. Forastiere, Laura Nikolopoulos, Georgios K. Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs |
title | Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs |
title_full | Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs |
title_fullStr | Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs |
title_full_unstemmed | Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs |
title_short | Methods for Assessing Spillover in Network-Based Studies of HIV/AIDS Prevention among People Who Use Drugs |
title_sort | methods for assessing spillover in network-based studies of hiv/aids prevention among people who use drugs |
topic | Tutorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967280/ https://www.ncbi.nlm.nih.gov/pubmed/36839598 http://dx.doi.org/10.3390/pathogens12020326 |
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