Prospective Evaluation of Routine Statewide Integration of Molecular Epidemiology and Contact Tracing to Disrupt Human Immunodeficiency Virus Transmission.
HIV
contact tracing
molecular epidemiology
public health
transmission networks
Journal
Open forum infectious diseases
ISSN: 2328-8957
Titre abrégé: Open Forum Infect Dis
Pays: United States
ID NLM: 101637045
Informations de publication
Date de publication:
Oct 2024
Oct 2024
Historique:
received:
30
08
2024
accepted:
04
10
2024
medline:
30
10
2024
pubmed:
30
10
2024
entrez:
30
10
2024
Statut:
epublish
Résumé
Human immunodeficiency virus (HIV) remains a global challenge and novel measures for transmission disruption are needed. Contact tracing is limited by reluctance or inability of newly diagnosed individuals to name at-risk contacts. Molecular cluster analysis is mostly used for outbreak investigations, and its role in routine public health activities remains uncertain. We conducted a 2-year prospective statewide study in Rhode Island to evaluate integration of HIV cluster analyses into routine contact tracing, by attempting to reinterview all new diagnoses who clustered, notifying them of clustering, and evaluating benefits of this strategy. Clustering was compared between a phylogenetic ensemble versus distance-based HIV-TRACE. Of 100 new diagnoses during 2021-2022, 52 individuals clustered, of whom only 31% were reinterviewed. Reinterviewing did not improve contact tracing beyond initial interviews, and the study was stopped early for futility. Clustering concordance within the phylogenetic ensemble was high (88%-89%), but lower (74%) for HIV-TRACE. Despite hypothesis rejection, we established a public health-academic partnership, developed a bioinformatics pipeline enabling near real-time cluster analysis, and identified gaps and unique opportunities for intervention. Attempting to reinterview all statewide new HIV diagnoses in molecular clusters showed no evidence of improving contact tracing. However, a strong academic-public health partnership enabled near real-time, longitudinal integration of molecular cluster analysis into routine public health activities, and identified barriers and opportunities tailoring data-driven approaches to unique individual and community characteristics, guiding future work on optimal use of molecular epidemiology to disrupt HIV transmission.
Sections du résumé
Background
UNASSIGNED
Human immunodeficiency virus (HIV) remains a global challenge and novel measures for transmission disruption are needed. Contact tracing is limited by reluctance or inability of newly diagnosed individuals to name at-risk contacts. Molecular cluster analysis is mostly used for outbreak investigations, and its role in routine public health activities remains uncertain.
Methods
UNASSIGNED
We conducted a 2-year prospective statewide study in Rhode Island to evaluate integration of HIV cluster analyses into routine contact tracing, by attempting to reinterview all new diagnoses who clustered, notifying them of clustering, and evaluating benefits of this strategy. Clustering was compared between a phylogenetic ensemble versus distance-based HIV-TRACE.
Results
UNASSIGNED
Of 100 new diagnoses during 2021-2022, 52 individuals clustered, of whom only 31% were reinterviewed. Reinterviewing did not improve contact tracing beyond initial interviews, and the study was stopped early for futility. Clustering concordance within the phylogenetic ensemble was high (88%-89%), but lower (74%) for HIV-TRACE. Despite hypothesis rejection, we established a public health-academic partnership, developed a bioinformatics pipeline enabling near real-time cluster analysis, and identified gaps and unique opportunities for intervention.
Conclusions
UNASSIGNED
Attempting to reinterview all statewide new HIV diagnoses in molecular clusters showed no evidence of improving contact tracing. However, a strong academic-public health partnership enabled near real-time, longitudinal integration of molecular cluster analysis into routine public health activities, and identified barriers and opportunities tailoring data-driven approaches to unique individual and community characteristics, guiding future work on optimal use of molecular epidemiology to disrupt HIV transmission.
Identifiants
pubmed: 39474444
doi: 10.1093/ofid/ofae599
pii: ofae599
pmc: PMC11521326
doi:
Types de publication
Journal Article
Langues
eng
Pagination
ofae599Informations de copyright
© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America.
Déclaration de conflit d'intérêts
Potential conflicts of interest. All authors: No reported conflicts.
Références
J Infect Dis. 2018 Nov 5;218(12):1943-1953
pubmed: 30010850
Sex Transm Dis. 2018 Apr;45(4):222-228
pubmed: 29465708
J Acquir Immune Defic Syndr. 2024 Sep 1;97(1):48-54
pubmed: 39116331
JAMA. 2019 Mar 5;321(9):844-845
pubmed: 30730529
Open Forum Infect Dis. 2021 Dec 07;9(1):ofab587
pubmed: 34988256
AIDS. 2023 Sep 1;37(11):1739-1746
pubmed: 37289578
Nucleic Acids Res. 2014 Oct;42(18):e144
pubmed: 25120265
Lancet HIV. 2016 May;3(5):e231-8
pubmed: 27126490
BMC Health Serv Res. 2018 Jan 31;18(1):75
pubmed: 29386023
Stat Commun Infect Dis. 2020 Sep;12(Suppl 1):
pubmed: 34733405
J Acquir Immune Defic Syndr. 2022 Jan 1;89(1):49-55
pubmed: 34878434
Nucleic Acids Res. 2003 Jan 1;31(1):298-303
pubmed: 12520007
Viruses. 2020 Sep 12;12(9):
pubmed: 32932642
Infect Genet Evol. 2016 Dec;46:159-168
pubmed: 27312102
Viruses. 2023 Mar 13;15(3):
pubmed: 36992446
Curr Opin HIV AIDS. 2019 May;14(3):213-220
pubmed: 30882486
AIDS. 2013 Nov 28;27(18):2961-3
pubmed: 24189585
AIDS. 2021 Sep 1;35(11):1711-1722
pubmed: 34033589
Open Forum Infect Dis. 2021 Apr 24;8(6):ofab211
pubmed: 34159215
BMJ Open. 2022 Apr 21;12(4):e060184
pubmed: 35450916
Sci Rep. 2020 Oct 29;10(1):18547
pubmed: 33122765
AIDS. 2023 Mar 1;37(3):389-399
pubmed: 36695355
EClinicalMedicine. 2021 Jun 17;37:100968
pubmed: 34195581
Sex Transm Dis. 2006 May;33(5):320-8
pubmed: 16505750
AIDS Res Hum Retroviruses. 2023 May;39(5):241-252
pubmed: 36785940
Mol Biol Evol. 2018 Jul 1;35(7):1812-1819
pubmed: 29401317
AIDS Res Hum Retroviruses. 2012 Aug;28(8):894-901
pubmed: 21916749
Curr Opin HIV AIDS. 2014 Mar;9(2):126-33
pubmed: 24384502
Clin Infect Dis. 2021 Sep 7;73(5):842-849
pubmed: 34492694
Infect Genet Evol. 2013 Oct;19:337-48
pubmed: 23660484