Viruses 2023, 15, 68. https://doi.org/10.3390/v15010068 www.mdpi.com/journal/viruses Article Insights into HIV-1 Transmission Dynamics Using Routinely Collected Data in the Mid-Atlantic United States Seble G. Kassaye 1, *, Zehava Grossman 2,3, *, Priyanka Vengurlekar 1 , William Chai 4 , Megan Wallace 1 , Soo-Yon Rhee 5 , William A. Meyer III 6 , Harvey W. Kaufman 6 , Amanda Castel 7 , Jeanne Jordan 7 , Keith A. Crandall 8 , Alisa Kang 1 , Princy Kumar 1 , David K. Katzenstein 5 , Robert W. Shafer 5 and Frank Maldarelli 2 1 Department of Medicine, Georgetown University, Washington, DC 20057, USA 2 HIV Dynamics and Replication Program, National Cancer Institute, Frederick, MD 21702, USA 3 School of Public Health, Tel Aviv University, Tel Aviv 69978, Israel 4 Warren Alpert Medical School, Brown University, Providence, RI 02912, USA 5 Department of Medicine, Stanford University, Stanford, CA 94305, USA 6 Quest Diagnostics, Secaucus, NJ 07094, USA 7 Department of Epidemiology, George Washington University, Washington, DC 20052, USA 8 Computational Biology Institute, George Washington University, Ashburn, VA 20147, USA * Correspondence: sgk23@georgetown.edu (S.G.K.); zehava.grossman@gmail.com (Z.G.) Abstract: Background: Molecular epidemiological approaches provide opportunities to characterize HIV transmission dynamics. We analyzed HIV sequences and virus load (VL) results obtained dur- ing routine clinical care, and individual’s zip-code location to determine utility of this approach. Methods: HIV-1 pol sequences aligned using ClustalW were subtyped using REGA. A maximum likelihood (ML) tree was generated using IQTree. Transmission clusters with ≤3% genetic distance (GD) and ≥90% bootstrap support were identified using ClusterPicker. We conducted Bayesian analysis using BEAST to confirm transmission clusters. The proportion of nucleotides with ambigu- ity ≤0.5% was considered indicative of early infection. Descriptive statistics were applied to charac- terize clusters and group comparisons were performed using chi-square or t-test. Results: Among 2775 adults with data from 2014–2015, 2589 (93%) had subtype B HIV-1, mean age was 44 years (SD 12.7), 66.4% were male, and 25% had nucleotide ambiguity ≤0.5. There were 456 individuals in 193 clusters: 149 dyads, 32 triads, and 12 groups with ≥ four individuals per cluster. More commonly in clusters were males than females, 349 (76.5%) vs. 107 (23.5%), p < 0.0001; younger individuals, 35.3 years (SD 12.1) vs. 44.7 (SD 12.3), p < 0.0001; and those with early HIV-1 infection by nucleotide ambiguity, 202/456 (44.3%) vs. 442/2133 (20.7%), p < 0.0001. Members of 43/193 (22.3%) of clusters included individuals in different jurisdictions. Clusters ≥ four individuals were similarly found us- ing BEAST. HIV-1 viral load (VL) ≥3.0 log10 c/mL was most common among individuals in clusters ≥ four, 18/21, (85.7%) compared to 137/208 (65.8%) in clusters sized 2-3, and 927/1169 (79.3%) who were not in a cluster (p < 0.0001). Discussion: HIV sequence data obtained for HIV clinical manage- ment provide insights into regional transmission dynamics. Our findings demonstrate the addi- tional utility of HIV-1 VL data in combination with phylogenetic inferences as an enhanced contact tracing tool to direct HIV treatment and prevention services. Trans-jurisdictional approaches are needed to optimize efforts to end the HIV epidemic. Citation: Kassaye, S.G.; Grossman, Z.; Vengurlekar, P.; Chai, W.; Wallace, M.; Rhee, S.-Y.; Meyer, W.A., III; Kaufman, H.W.; Castel, A.; Jordan, J.; et al. Insights into HIV-1 Transmission Dynamics Using Rou- tinely Collected Data in the Mid-At- lantic United States. Viruses 2023, 15, 68. https://doi.org/10.3390/v15010068 Academic Editor: Ester Ballana Guix Received: 21 October 2022 Revised: 21 December 2022 Accepted: 23 December 2022 Published: 25 December 2022 Copyright: © 2022 by the authors. Li- censee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and con- ditions of the Creative Commons At- tribution (CC BY) license (https://cre- ativecommons.org/licenses/by/4.0/).