ArticlePloS one2021
Network centrality for the identification of biomarkers in respondent-driven sampling datasets.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed.
- Leveraging injection networks to prevent HIV and other blood borne infections among people who inject drugs in Kenya: design and rationale.BMC infectious diseases · 2025Article
- Context-Dependent Effects of HIV Disclosure on Social Isolation Among Rural PLHIV: A Pilot Configurational Study.International journal of environmental research and public health · 2025Article
- Intersectional Barriers Among PLHIV in Rural Illinois: Insights from a Pilot QCA Study.International journal of environmental research and public health · 2025Article
- Inferred networks, machine learning, and health data.PloS one · 2023Article
- Abnormal hubs in global network as neuroimaging biomarker in right temporal lobe epilepsy at rest.Frontiers in psychiatry · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Networks science techniques are frequently used to provide meaningful insights into the populations underlying medical and social data. This paper examines SATHCAP, a dataset related to HIV and drug use in three US cities. In particular, we use network measures such as betweenness centrality, closeness centrality, and eigenvector centrality to find central, important nodes in a network derived from SATHCAP data. We evaluate the attributes of these important nodes and create an exceptionality score based on the number of nodes that share a particular attribute. This score, along with the underlying network itself, is used to reveal insight into the attributes of groups that can be effectively targeted to slow the spread of disease. Our research confirms a known connection between homelessness and HIV, as well as drug abuse and HIV, and shows support for the theory that individuals without easy access to transportation are more likely to be central to the spread of HIV in urban, high risk populations.
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Registered trials
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.