Lost and found: applying network analysis to public health contact tracing for HIV.


Infectious disease surveillance is often case-based, focused on people diagnosed and their contacts in a predefined time window, and treated as independent across infections. Network analysis of partners and contacts joining multiple investigations and infections can reveal social or temporal trends, providing opportunities for epidemic control within broader networks. We constructed a sociosexual network of all HIV and early syphilis cases and contacts investigated among residents of 11 contiguous counties in North Carolina over a two-year period (2012-2013). We anchored the analysis on new HIV diagnoses ("indexes"), but also included nodes and edges from syphilis investigations that were within the same network component as any new HIV index. After adding syphilis investigations and deduplicating people included in multiple investigations (entity resolution), the final network comprised 1470 people: 569 HIV indexes, 700 contacts to HIV indexes who were not also new cases themselves, and 201 people who were either indexes or contacts in eligible syphilis investigations. Among HIV indexes, nearly half (48%; n = 273) had no located contacts during single-investigation contact tracing, though 25 (9%) of these were identified by other network members and thus not isolated in the final multiple investigation network. Constructing a sociosexual network from cases and contacts across multiple investigations mitigated some effects of unobserved partnerships underlying the HIV epidemic and demonstrated the HIV and syphilis overlap in these networks.





Published Version (Please cite this version)


Publication Info

Pasquale, Dana K, Irene A Doherty, Peter A Leone, Ann M Dennis, Erika Samoff, Constance S Jones, John Barnhart, William C Miller, et al. (2021). Lost and found: applying network analysis to public health contact tracing for HIV. Applied network science, 6(1). p. 13. 10.1007/s41109-021-00355-w Retrieved from https://hdl.handle.net/10161/23876.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.



Dana Kristine Pasquale

Assistant Professor in Population Health Sciences

Dr. Dana K Pasquale earned a PhD in infectious disease epidemiology from UNC-Chapel Hill, earned an MPH in health behavior from East Carolina University, and completed three years as a postdoc in the Duke University Department of Sociology.  She combines social network and pathogen genetic data to study infectious disease transmission networks.  The majority of Dana’s work is domestic, examining HIV and syphilis transmission in North Carolina.  She also uses clonal bacterial data, pathogen genetic data, and location information to study hospital-acquired multi-drug resistant infections.  Dana is the PI of Duke RDS^2:  Respondent-Driven Sampling for Respiratory Disease Surveillance, a CDC-funded snowball sampling study to locate active, undiagnosed SARS-CoV-2 cases in Durham County.  She is also externally funded by NIH and NSF as a co-Investigator.

Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.