Literature DB >> 29910531

Statistical adjustment of network degree in respondent-driven sampling estimators: venue attendance as a proxy for network size among young MSM.

Kayo Fujimoto1, Ming Cao1, Lisa M Kuhns2, Dennis Li1, John A Schneider3.   

Abstract

We introduce a new venue-informed network degree measure, which we applied to respondent-driven sampling (RDS) estimators. Using data collected from 746 young MSM in 2014-2016 in Chicago, IL, and Houston, TX, we estimated the population seroprevalence of HIV and syphilis and risk/protective behaviors, using RDS estimates with self-reported network size as a standard degree measure as well as our proposed venue-informed degree measure. The results indicate that the venue-informed degree measure tended to be more efficient (smaller variance) and less biased than the other measure in both cities sampled. Venue attendance-adjusted network size may provide a more reliable and accurate degree measure for RDS estimates of the outcomes of interest.

Entities:  

Keywords:  HIV; Respondent-driven sampling method (RDS); pre-exposure prophylaxis (PrEP); risky sexual behavior; sexually transmitted infections; two-mode affiliation networks; venue affiliation; young men who have sex with men (MSM)

Year:  2018        PMID: 29910531      PMCID: PMC6001287          DOI: 10.1016/j.socnet.2018.01.003

Source DB:  PubMed          Journal:  Soc Networks        ISSN: 0378-8733


  54 in total

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8.  Socioeconomic Disconnection as a Risk Factor for Increased HIV Infection in Young Men Who Have Sex with Men.

Authors:  Travis A Gayles; Lisa M Kuhns; Soyang Kwon; Brian Mustanski; Robert Garofalo
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Authors:  Harriet L Mills; Samuel Johnson; Matthew Hickman; Nick S Jones; Caroline Colijn
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  7 in total

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3.  Network context matters: graph convolutional network model over social networks improves the detection of unknown HIV infections among young men who have sex with men.

Authors:  Yang Xiang; Kayo Fujimoto; John Schneider; Yuxi Jia; Degui Zhi; Cui Tao
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4.  Stimulant use interventions may strengthen 'Getting to Zero' HIV elimination initiatives in Illinois: Insights from a modeling study.

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6.  Identifying influential neighbors in social networks and venue affiliations among young MSM: a data science approach to predict HIV infection.

Authors:  Yang Xiang; Kayo Fujimoto; Fang Li; Qing Wang; Natascha Del Vecchio; John Schneider; Degui Zhi; Cui Tao
Journal:  AIDS       Date:  2021-05-01       Impact factor: 4.632

7.  Friend of a Friend with Benefits ontology (FOAF+): extending a social network ontology for public health.

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  7 in total

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