Network centrality for the identification of biomarkers in respondent-driven sampling datasets

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, closen...

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Bibliographic Details
Published in:PloS one 2021-08, Vol.16 (8), p.e0256601
Main Authors: Grubb, Jacob, Lopez, Derek, Mohan, Bhuvaneshwar, Matta, John
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Biological markers
Biology and Life Sciences
Biomarkers
Cities
Computer and Information Sciences
Computer science
Databases, Factual
Datasets
Diagnosis
Disease transmission
Drug abuse
Drug use
Earth Sciences
Eigenvectors
Engineering and Technology
Epidemics
Health risks
HIV
HIV infection
HIV Infections - pathology
HIV Infections - transmission
Homeless people
Homeless Persons
Homelessness
Human immunodeficiency virus
Humans
Information sources
Medical diagnosis
Medicine and Health Sciences
Nodes
Physical Sciences
Populations
Seeds
Severe acute respiratory syndrome coronavirus 2
Social Network Analysis
Social research
Social Sciences
Substance-Related Disorders - pathology
Urban populations
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Summary: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.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0256601