Phylodynamic Analysis Complements Partner Services by Identifying Acute and Unreported HIV Transmission

Investigation of Presumptive HIV Transmission Associated with Receipt of Platelet-Rich Plasma Microneedling Facials at a Spa Among Former Spa Clients - New Mexico, 2018-2023

HIV transmitted through cosmetic injection services via contaminated blood has not been previously documented. During summer 2018, the New Mexico Department of Health (NMDOH) was notified of a diagnosis of HIV infection in a woman with no known HIV risk factors who reported exposure to needles from cosmetic platelet-rich plasma microneedling facials (vampire facials) received at a spa in spring 2018. An investigation of the spa's services began in summer 2018, and NMDOH and CDC identified four former spa clients, and one sexual partner of a spa client, all of whom received HIV infection diagnoses during 2018-2023, despite low reported behavioral risks associated with HIV acquisition. Nucleotide sequence analysis revealed highly similar HIV strains among all cases. Although transmission of HIV via unsterile injection practices is a known risk, determining novel routes of HIV transmission among persons with no known HIV risk factors is important. This investigation identified an HIV cluster associated with receipt of cosmetic injection services at an unlicensed facility that did not follow recommended infection control procedures or maintain client records. Requiring adequate infection control practices and maintenance of client records at spa facilities offering cosmetic injection services can help prevent the transmission of HIV and other bloodborne pathogens and ensure adequate traceback and notification in the event of adverse clinical outcomes, respectively.

HantaNet: A New MicrobeTrace Application for Hantavirus Classification, Genomic Surveillance, Epidemiology and Outbreak Investigations

Hantaviruses zoonotically infect humans worldwide with pathogenic consequences and are mainly spread by rodents that shed aerosolized virus particles in urine and feces. Bioinformatics methods for hantavirus diagnostics, genomic surveillance and epidemiology are currently lacking a comprehensive approach for data sharing, integration, visualization, analytics and reporting. With the possibility of hantavirus cases going undetected and spreading over international borders, a significant reporting delay can miss linked transmission events and impedes timely, targeted public health interventions. To overcome these challenges, we built HantaNet, a standalone visualization engine for hantavirus genomes that facilitates viral surveillance and classification for early outbreak detection and response. HantaNet is powered by MicrobeTrace, a browser-based multitool originally developed at the Centers for Disease Control and Prevention (CDC) to visualize HIV clusters and transmission networks. HantaNet integrates coding gene sequences and standardized metadata from hantavirus reference genomes into three separate gene modules for dashboard visualization of phylogenetic trees, viral strain clusters for classification, epidemiological networks and spatiotemporal analysis. We used 85 hantavirus reference datasets from GenBank to validate HantaNet as a classification and enhanced visualization tool, and as a public repository to download standardized sequence data and metadata for building analytic datasets. HantaNet is a model on how to deploy MicrobeTrace-specific tools to advance pathogen surveillance, epidemiology and public health globally.

Combining molecular network analysis and field epidemiology to quantify local HIV transmission and highlight ongoing epidemics

OBJECTIVES

This study aimed to establish a collaborative approach to quantify local HIV transmission, which is an issue of great concern to public health.

METHODS

We linked HIV-1 pol gene sequences to demographic information and epidemiological investigations in Hangzhou (a central city in East China). We estimated local acquisition rates from a collaboration of molecular network analysis (with a distance-based approach) and epidemiological investigations.

RESULTS

Among 1064 newly diagnosed patients with HIV, 857 pol sequences were acquired and subsequently analyzed. Multiple subtypes were identified, with circulating recombinant form (CRF)07_BC (42.5%) and CRF01_AE (39.2%) predominating, followed by 13 other subtypes and 26 unique recombinant forms. By integrating the molecular network analysis and epidemiological investigations, we estimated that the proportion of local infection was 63.2%. The multivariable analyses revealed that individuals in clusters were more likely to be local residents, be aged 50 years or older, work as farmers, and have a higher first cluster of differentiation 4 count level (P <0.05). The proportions of local acquisitions over 70% were observed in local residents (79.9%, 242/303), individuals aged 50 years or older (73.6%, 181/246), and farmers (75.6%, 99/131).

CONCLUSION

The molecular network analysis can augment traditional HIV epidemic surveillance. This study establishes a paradigm for quantifying local HIV transmission for generalization in other areas.

HIV Response Interventions that Integrate HIV Molecular Cluster and Social Network Analysis: A Systematic Review

Due to improved efficiency and reduced cost of viral sequencing, molecular cluster analysis can be feasibly utilized alongside existing human immunodeficiency virus (HIV) prevention strategies. The goal of this paper is to elucidate how HIV molecular cluster and social network analyses are being integrated to implement HIV response interventions. We searched PubMed, Scopus, PsycINFO, and Cochrane Library databases for studies incorporating both HIV molecular cluster and social network data. We identified 32 articles that combined analyses of HIV molecular sequences and social or sexual networks. All studies were descriptive. Six studies described network interventions informed by molecular and social data but did not fully evaluate their efficacy. There is no current standard for incorporating molecular and social network analyses to inform interventions or data demonstrating its utility. More research must be conducted to delineate benefits and best practices for leveraging molecular data for network-based interventions.

Transmission Clusters, Predominantly Associated With Men Who Have Sex With Men, Play a Main Role in the Propagation of HIV-1 in Northern Spain (2013–2018)

Viruses of HIV-1-infected individuals whose transmission is related group phylogenetically in transmission clusters (TCs). The study of the phylogenetic relations of these viruses and the factors associated with these individuals is essential to analyze the HIV-1 epidemic. In this study, we examine the role of TCs in the epidemiology of HIV-1 infection in Galicia and the Basque County, two regions of northern Spain. A total of 1,158 HIV-1-infected patients from both regions with new diagnoses (NDs) in 2013–2018 were included in the study. Partial HIV-1 pol sequences were analyzed phylogenetically by approximately maximum-likelihood with FastTree 2. In this analysis, 10,687 additional sequences from samples from HIV-1-infected individuals collected in Spain in 1999–2019 were also included to assign TC membership and to determine TCs’ sizes. TCs were defined as those which included viruses from ≥4 individuals, at least 50% of them Spaniards, and with ≥0.95 Shimodaira-Hasegawa-like node support in the phylogenetic tree. Factors associated to TCs were evaluated using odds ratios (OR) and their 95% CI. Fifty-one percent of NDs grouped in 162 TCs. Male patients (OR: 2.6; 95% CI: 1.5–4.7) and men having sex with men (MSM; OR: 2.1; 95% CI: 1.4–3.2) had higher odds of belonging to a TC compared to female and heterosexual patients, respectively. Individuals from Latin America (OR: 0.3; 95% CI: 0.2–0.4), North Africa (OR: 0.4; 95% CI: 0.2–1.0), and especially Sub-Saharan Africa (OR: 0.02; 95% CI: 0.003–0.2) were inversely associated to belonging to TCs compared to native Spaniards. Our results show that TCs are important components of the HIV-1 epidemics in the two Spanish regions studied, where transmission between MSM is predominant. The majority of migrants were infected with viruses not belonging to TCs that expand in Spain. Molecular epidemiology is essential to identify local peculiarities of HIV-1 propagation. The early detection of TCs and prevention of their expansion, implementing effective control measures, could reduce HIV-1 infections.

Non-student young men put students at high risk of human immunodeficiency virus acquisition in Guangxi, China: a phylogenetic analysis of surveillance data

Background

We sought to identify students and their sexual partners in a molecular transmission network.

Methods

We obtained 5996 HIV protease and reverse transcriptase gene sequences in Guangxi (165 from students and 5831 from the general populations) and the relevant demographic data. We constructed a molecular transmission network and introduced a permutation test to assess the robust genetic linkages. We calculated the centrality measures to describe the transmission patterns in clusters.

Results

At the network level, 68 (41.2%) students fell within the network across 43 (8.1%) clusters. Of 141 genetic linkages between students and their partners, only 25 (17.7%) occurred within students. Students were more likely than random permutations to link to other students (odds ratio [OR], 7.2; P < .001), private company employees aged 16–24 years (OR, 3.3; P = .01), private company or government employees aged 25–49 years (OR, 1.7; P = .03), and freelancers or unemployed individuals aged 16–24 years (OR, 5.0; P < .001). At the cluster level, the median age of nonstudents directly linked to students (interquartile range) was 25 (22–30) years, and 80.3% of them had a high school or higher education background. Compared with students, they showed a significantly higher median degree (4.0 vs 2.0; P < .001) but an equivalent median Eigenvector Centrality (0.83 vs 0.81; P = .60).

Conclusions

The tendency of genetic linkage between students and nonstudent young men and their important position in the HIV transmission network emphasizes the urgent need for 2-pronged public health interventions based on both school and society.

Identification of a Human Immunodeficiency Virus Type 1 and Neurosyphilis Cluster in Vermont

BACKGROUND

Rates of syphilis in the United States have more than doubled over the last several decades, largely among men who have sex with men (MSM). Our study characterizes a cluster of neurosyphilis cases among people with human immunodeficiency virus 1 (HIV-1) in Vermont in 2017-2018.

METHODS

Vermont Department of Health disease intervention specialists conduct interviews with newly diagnosed HIV-1 cases and pursue sexual networking analyses. Phylogenetic and network analyses of available Vermont HIV-1 polymerase (pol) sequences identified clusters of infection. Fishers-exact and independent t-tests were used to compare people with HIV-1 within or outside an identified cluster.

RESULTS

Between 1 January 2017 and 31 December 2018, 38 residents were diagnosed with HIV-1 infection. The mean age was 35.5 years, 79% were male and 82% were White. Risk factors for HIV-1 included MSM status (79%) and methamphetamine use (21%). Eighteen cases (49%) had HIV-1 viral loads (VLs) >100 000 copies/mL and 47% had CD4 cell counts <200/mm3. Eleven of the 38 (29%) had positive syphilis serology, including four (36%) with neurosyphilis. Sexual networking analysis revealed a ten-person cluster with higher VLs at diagnosis (90% with VLs > 100 000 copies/mL vs 33%, P = 0.015). Phylogenetic analysis of pol sequences showed a cluster of 14 cases with sequences that shared 98%-100% HIV-1 nucleotide identity.

CONCLUSIONS

This investigation of newly infected HIV-1 cases in Vermont led to identification of a cluster that appeared more likely to have advanced HIV-1 disease and neurosyphilis, supported by phylogenetic and network analyses.

MicrobeTrace: Retooling molecular epidemiology for rapid public health response

Outbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions. We developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. MicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully operational without an internet connection. Using publicly available data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. Users can email microbetrace@cdc.gov for support. The source code is available at https://github.com/cdcgov/microbetrace.

Rapid advances in the fields of data science and bioinformatics have significantly improved molecular epidemiology tools used in public health and have led to major changes in the way outbreak investigation and pathogen transmission studies are conducted. However, the need for specialized computer skills often impedes the use of many of these tools in the public heath domain. We bridge this knowledge gap by development of an intuitive, standalone tool called MicrobeTrace to securely integrate, visualize and explore pathogen epidemiologic data. MicrobeTrace is an easy to use browser-based tool which can effectively merge contact tracing and/or microbial genomic data with demographic or behavioral information, resulting in elegant and informative networks as well as multiple customizable visualizations. MicrobeTrace can be used offline, with analyses being performed locally in the field, ensuring secure and confidential use of personally identifiable information (PII). We provide real world examples of how MicrobeTrace has been used in public health, including COVID outbreak investigations.

Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment

HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting genetically similar genotyped viral sequences in the network implying epidemiological transmissions. This technique relies on genotype data which is collected only from HIV diagnosed and in-care populations and leaves many persons with HIV (PWH) who have no access to consistent care out of the tracking process. We use machine learning algorithms to learn the non-linear correlation patterns between patient metadata and transmissions between HIV-positive cases. This enables us to expand the transmission network reconstruction beyond the molecular network. We employed multiple commonly used supervised classification algorithms to analyze the San Diego Primary Infection Resource Consortium (PIRC) cohort dataset, consisting of genotypes and nearly 80 additional non-genetic features. First, we trained classification models to determine genetically unrelated individuals from related ones. Our results show that random forest and decision tree achieved over 80% in accuracy, precision, recall, and F1-score by only using a subset of meta-features including age, birth sex, sexual orientation, race, transmission category, estimated date of infection, and first viral load date besides genetic data. Additionally, both algorithms achieved approximately 80% sensitivity and specificity. The Area Under Curve (AUC) is reported 97% and 94% for random forest and decision tree classifiers respectively. Next, we extended the models to identify clusters of similar viral sequences. Support vector machine demonstrated one order of magnitude improvement in accuracy of assigning the sequences to the correct cluster compared to dummy uniform random classifier. These results confirm that metadata carries important information about the dynamics of HIV transmission as embedded in transmission clusters. Hence, novel computational approaches are needed to apply the non-trivial knowledge collected from inter-individual genetic information to metadata from PWH in order to expand the estimated transmissions. We note that feature extraction alone will not be effective in identifying patterns of transmission and will result in random clustering of the data, but its utilization in conjunction with genetic data and the right algorithm can contribute to the expansion of the reconstructed network beyond individuals with genetic data.

The Role of Phylogenetics in Unravelling Patterns of HIV Transmission towards Epidemic Control: The Quebec Experience (2002-2020)

Phylogenetics has been advanced as a structural framework to infer evolving trends in the regional spread of HIV-1 and guide public health interventions. In Quebec, molecular network analyses tracked HIV transmission dynamics from 2002-2020 using MEGA10-Neighbour-joining, HIV-TRACE, and MicrobeTrace methodologies. Phylogenetics revealed three patterns of viral spread among Men having Sex with Men (MSM, n = 5024) and heterosexuals (HET, n = 1345) harbouring subtype B epidemics as well as B and non-B subtype epidemics (n = 1848) introduced through migration. Notably, half of new subtype B infections amongst MSM and HET segregating as solitary transmissions or small cluster networks (2-5 members) declined by 70% from 2006-2020, concomitant to advances in treatment-as-prevention. Nonetheless, subtype B epidemic control amongst MSM was thwarted by the ongoing genesis and expansion of super-spreader large cluster variants leading to micro-epidemics, averaging 49 members/cluster at the end of 2020. The growth of large clusters was related to forward transmission cascades of untreated early-stage infections, younger at-risk populations, more transmissible/replicative-competent strains, and changing demographics. Subtype B and non-B subtype infections introduced through recent migration now surpass the domestic epidemic amongst MSM. Phylodynamics can assist in predicting and responding to active, recurrent, and newly emergent large cluster networks, as well as the cryptic spread of HIV introduced through migration.

Intersection of Syphilis and HIV Networks to Identify Opportunities to Enhance HIV Prevention

BACKGROUND

HIV and syphilis infection continue at disproportionate rates among minority men who have sex with men (MSM) in the United States. The integration of HIV genetic clustering with partner services can provide important insight into local epidemic trends to guide interventions and control efforts.

METHODS

We evaluated contact networks of index persons defined as minority men and transgender women diagnosed with early syphilis and/or HIV infection between 2018-2020 in two North Carolina regions. HIV clusters were constructed from pol sequences collected through statewide surveillance. A combined "HIV-risk" network, which included persons with any links (genetic or sexual contact) to HIV-positive persons, was evaluated by component size, demographic factors, and HIV viral suppression.

RESULTS

In total, 1,289 index persons were identified and 55% named 1,153 contacts. Most index persons were Black (88%) and young (median age 30 years); 70% had early syphilis and 43% had prevalent HIV infection. Most people with HIV (65%) appeared in an HIV cluster. The combined HIV-risk network (1,590 contact network and 1,500 cluster members) included 287 distinct components; however, 1,586 (51%) were in a single component. Fifty-five percent of network members with HIV had no evidence of viral suppression. Overall, fewer index persons needed to be interviewed to identify one HIV-positive member without viral suppression (1.3 versus 4.0 for contact tracing).

CONCLUSIONS

Integration of HIV clusters and viral loads illuminate networks with high HIV prevalence, indicating recent and ongoing transmission. Interventions intensified towards these networks may efficiently reach persons for HIV prevention and care re-engagement.

Molecular Epidemiological Analysis of the Origin and Transmission Dynamics of the HIV-1 CRF01_AE Sub-Epidemic in Bulgaria

HIV-1 subtype CRF01_AE is the second most predominant strain in Bulgaria, yet little is known about the molecular epidemiology of its origin and transmissibility. We used a phylodynamics approach to better understand this sub-epidemic by analyzing 270 HIV-1 polymerase (pol) sequences collected from persons diagnosed with HIV/AIDS between 1995 and 2019. Using network analyses at a 1.5% genetic distance threshold (d), we found a large 154-member outbreak cluster composed mostly of persons who inject drugs (PWID) that were predominantly men. At d = 0.5%, which was used to identify more recent transmission, the large cluster dissociated into three clusters of 18, 12, and 7 members, respectively, five dyads, and 107 singletons. Phylogenetic analysis of the Bulgarian sequences with publicly available global sequences showed that CRF01_AE likely originated from multiple Asian countries, with Vietnam as the likely source of the outbreak cluster between 1988 and 1990. Our findings indicate that CRF01_AE was introduced into Bulgaria multiple times since 1988, and infections then rapidly spread among PWID locally with bridging to other risk groups and countries. CRF01_AE continues to spread in Bulgaria as evidenced by the more recent large clusters identified at d = 0.5%, highlighting the importance of public health prevention efforts in the PWID communities.

Subtype-specific differences in transmission cluster dynamics of HIV-1 B and CRF01_AE in New South Wales, Australia

INTRODUCTION

The human immunodeficiency virus 1 (HIV-1) pandemic is characterized by numerous distinct sub-epidemics (clusters) that continually fuel local transmission. The aims of this study were to identify active growing clusters, to understand which factors most influence the transmission dynamics, how these vary between different subtypes and how this information might contribute to effective public health responses.

METHODS

We used HIV-1 genomic sequence data linked to demographic factors that accounted for approximately 70% of all new HIV-1 notifications in New South Wales (NSW). We assessed differences in transmission cluster dynamics between subtype B and circulating recombinant form 01_AE (CRF01_AE). Separate phylogenetic trees were estimated using 2919 subtype B and 473 CRF01_AE sequences sampled between 2004 and 2018 in combination with global sequence data and NSW-specific clades were classified as clusters, pairs or singletons. Significant differences in demographics between subtypes were assessed with Chi-Square statistics.

RESULTS

We identified 104 subtype B and 11 CRF01_AE growing clusters containing a maximum of 29 and 11 sequences for subtype B and CRF01_AE respectively. We observed a > 2-fold increase in the number of NSW-specific CRF01_AE clades over time. Subtype B clusters were associated with individuals reporting men who have sex with men (MSM) as their transmission risk factor, being born in Australia, and being diagnosed during the early stage of infection (p < 0.01). CRF01_AE infections clusters were associated with infections among individuals diagnosed during the early stage of infection (p < 0.05) and CRF01_AE singletons were more likely to be from infections among individuals reporting heterosexual transmission (p < 0.05). We found six subtype B clusters with an above-average growth rate (>1.5 sequences / 6-months) and which consisted of a majority of infections among MSM. We also found four active growing CRF01_AE clusters containing only infections among MSM. Finally, we found 47 subtype B and seven CRF01_AE clusters that contained a large gap in time (>1 year) between infections and may be indicative of intermediate transmissions via undiagnosed individuals.

CONCLUSIONS

The large number of active and growing clusters among MSM are the driving force of the ongoing epidemic in NSW for subtype B and CRF01_AE.

Empirical comparison of analytical approaches for identifying molecular HIV-1 clusters

Public health interventions guided by clustering of HIV-1 molecular sequences may be impacted by choices of analytical approaches. We identified commonly-used clustering analytical approaches, applied them to 1886 HIV-1 Rhode Island sequences from 2004-2018, and compared concordance in identifying molecular HIV-1 clusters within and between approaches. We used strict (topological support ≥ 0.95; distance 0.015 substitutions/site) and relaxed (topological support 0.80-0.95; distance 0.030-0.045 substitutions/site) thresholds to reflect different epidemiological scenarios. We found that clustering differed by method and threshold and depended more on distance than topological support thresholds. Clustering concordance analyses demonstrated some differences across analytical approaches, with RAxML having the highest (91%) mean summary percent concordance when strict thresholds were applied, and three (RAxML-, FastTree regular bootstrap- and IQ-Tree regular bootstrap-based) analytical approaches having the highest (86%) mean summary percent concordance when relaxed thresholds were applied. We conclude that different analytical approaches can yield diverse HIV-1 clustering outcomes and may need to be differentially used in diverse public health scenarios. Recognizing the variability and limitations of commonly-used methods in cluster identification is important for guiding clustering-triggered interventions to disrupt new transmissions and end the HIV epidemic.