Evidence map›Paper›PMID 32004795›Full record

ArticleEpidemics2020

Egocentric sexual networks of men who have sex with men in the United States: Results from the ARTnet study.

Kevin M Weiss, Steven M Goodreau, Martina Morris, Pragati Prasad, Ramya Ramaraju, Travis Sanchez, Samuel M Jenness

Open access · goldAbstract read
In one paragraph

Article in Epidemics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 11% 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 70 citations in OpenAlex.

  1. A Review of Network Models for HIV Spread.Journal of acquired immune deficiency syndromes (1999) · 2025
    Pooled it
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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

7 authors at 2 institutions in 1 country.

Kevin M WeissDepartment of Epidemiology, Emory University, Atlanta, Georgia, United States.
Steven M GoodreauDepartment of Anthropology, University of Washington, Seattle, Washington, United States.
Martina MorrisDepartments of Statistics and Sociology, University of Washington, Seattle, Washington, United States.
Pragati PrasadDepartment of Epidemiology, Emory University, Atlanta, Georgia, United States.
Ramya RamarajuDepartment of Epidemiology, Emory University, Atlanta, Georgia, United States.
Travis SanchezDepartment of Epidemiology, Emory University, Atlanta, Georgia, United States.
Samuel M JennessDepartment of Epidemiology, Emory University, Atlanta, Georgia, United States. Electronic address: samuel.m.jenness@emory.edu.
Emory University · USUniversity of Washington · US

Funding

University of Washington/Fred Hutch Center for AIDS ResearchP30AI027757 · NIAID · UNIVERSITY OF WASHINGTON · PI EDWIN ROBERTO ORELLANA · 1988 to 2026
$104.9M
Virology and Molecular Biomarkers CoreP30AI050409 · NIAID · EMORY UNIVERSITY · PI Ann M Chahroudi, Colleen F Kelley · 2002 to 2026
$74.0M
EpiModel 2.0: Integrated Network Models for HIV/STI Prevention ScienceR01AI138783 · NIAID · EMORY UNIVERSITY · PI JENNESS, SAMUEL · 2018 to 2021
$3.0M
Modeling Antiretroviral-Based Prevention among MSM in the USR21MH112449 · NIMH · EMORY UNIVERSITY · PI JENNESS, SAMUEL · 2017 to 2018
$442k
NIAID NIH HHS P30 AI027757NIAID NIH HHS P30 AI050409NIAID NIH HHS R01 AI138783NIMH NIH HHS R21 MH112449
6 · The paper itself

Abstract

In this paper, we present an overview and descriptive results from one of the first egocentric network studies of men who have sex with men (MSM) from across the United States: the ARTnet study. ARTnet was designed to support prevention research for human immunodeficiency virus (HIV) and other sexually transmitted infections (STIs) that are transmitted across partnership networks. ARTnet implemented a population-based egocentric network study design that sampled egos from the target population and asked them to report on the number, attributes, and timing of their sexual partnerships. Such data provide the foundation needed for parameterizing stochastic network models that are used for disease projection and intervention planning. ARTnet collected data online from 2017 to 2019, with a final sample of 4904 participants who reported on 16198 sexual partnerships. The aims of this paper were to characterize the joint distribution of three network parameters needed for modeling: degree distributions, assortative mixing, and partnership age, with heterogeneity by partnership type (main, casual and one-time), demography, and geography. Participants had an average of 1.19 currently active partnerships ("mean degree"), which was higher for casual partnerships (0.74) than main partnerships (0.45). The mean rate of one-time partnership acquisition was 0.16 per week (8.5 partners per year). Main partnerships lasted 272.5 weeks on average, while casual partnerships lasted 133.0 weeks. There was strong but heterogenous assortative mixing by race/ethnicity for all groups. The mean absolute age difference for all partnership types was 9.5 years, with main partners differing by 6.3 years compared to 10.8 years for casual partners. Our analysis suggests that MSM may be at sustained risk for HIV/STI acquisition and transmission through high network degree of sexual partnerships. The ARTnet network study provides a robust and reproducible foundation for understanding the dynamics of HIV/STI epidemiology among U.S. MSM and supporting the implementation science that seeks to address persistent challenges in HIV/STI prevention.

Indexed as

Mathematical modelingMen who have sex with menNetwork modelingNetwork scienceSexual networks

Identifiers

PMID32004795
PMCPMC7089812
OpenAlexW3001478529

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.