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. 2018 Dec 15;79(5):543-550.
doi: 10.1097/QAI.0000000000001856.

Identifying Clusters of Recent and Rapid HIV Transmission Through Analysis of Molecular Surveillance Data

Alexandra M Oster  1 , Anne Marie France  1 , Nivedha Panneer  1 , M Cheryl Bañez Ocfemia  1 , Ellsworth Campbell  1 , Sharoda Dasgupta  1   2 , William M Switzer  1 , Joel O Wertheim  3 , Angela L Hernandez  1
Affiliations

Identifying Clusters of Recent and Rapid HIV Transmission Through Analysis of Molecular Surveillance Data

Alexandra M Oster et al. J Acquir Immune Defic Syndr. .

Abstract

Background: Detecting recent and rapid spread of HIV can help prioritize prevention and early treatment for those at highest risk of transmission. HIV genetic sequence data can identify transmission clusters, but previous approaches have not distinguished clusters of recent, rapid transmission. We assessed an analytic approach to identify such clusters in the United States.

Methods: We analyzed 156,553 partial HIV-1 polymerase sequences reported to the National HIV Surveillance System and inferred transmission clusters using 2 genetic distance thresholds (0.5% and 1.5%) and 2 periods for diagnoses (all years and 2013-2015, ie, recent diagnoses). For rapidly growing clusters (with ≥5 diagnoses during 2015), molecular clock phylogenetic analysis estimated the time to most recent common ancestor for all divergence events within the cluster. Cluster transmission rates were estimated using these phylogenies.

Results: A distance threshold of 1.5% identified 103 rapidly growing clusters using all diagnoses and 73 using recent diagnoses; at 0.5%, 15 clusters were identified using all diagnoses and 13 using recent diagnoses. Molecular clock analysis estimated that the 13 clusters identified at 0.5% using recent diagnoses had been diversifying for a median of 4.7 years, compared with 6.5-13.2 years using other approaches. The 13 clusters at 0.5% had a transmission rate of 33/100 person-years, compared with previous national estimates of 4/100 person-years.

Conclusions: Our approach identified clusters with transmission rates 8 times those of previous national estimates. This method can identify groups involved in rapid transmission and help programs effectively direct and prioritize limited public health resources.

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Conflict of interest statement

Conflicts of interest:The authors report no conflicts of interest.

Figures

Figure 1.
Figure 1.
Map of jurisdictions participating in molecular HIV surveillance, 2013–2017. These jurisdictions reported 70% of HIV diagnoses occurring in 2015. Stars indicate cities/counties that are separately funded for HIV surveillance activities.
Figure 2.
Figure 2.
a) Examples of clusters that would not (i) and would (ii) meet criteria for this analysis. Clusters of recent and rapid transmission are defined as those with at least five diagnoses during the last 12 months of the analysis period. b) Example phylogenetic tree and example calculation of transmission rate.
See this image and copyright information in PMC

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