In-depth Sampling of High-risk Populations to Characterize HIV Transmission Epidemics Among Young MSM Using PrEP in France and Quebec

Characteristics and growth of the genetic HIV transmission network of Mexico City during 2020

INTRODUCTION

Molecular surveillance systems could provide public health benefits to focus strategies to improve the HIV care continuum. Here, we infer the HIV genetic network of Mexico City in 2020, and identify actively growing clusters that could represent relevant targets for intervention.

METHODS

All new diagnoses, referrals from other institutions, as well as persons returning to care, enrolling at the largest HIV clinic in Mexico City were invited to participate in the study. The network was inferred from HIV pol sequences, using pairwise genetic distance methods, with a locally hosted, secure version of the HIV-TRACE tool: Seguro HIV-TRACE. Socio-demographic, clinical and behavioural metadata were overlaid across the network to design focused prevention interventions.

RESULTS

A total of 3168 HIV sequences from unique individuals were included. One thousand and one-hundred and fifty (36%) sequences formed 1361 links within 386 transmission clusters in the network. Cluster size varied from 2 to 14 (63% were dyads). After adjustment for covariates, lower age (adjusted odds ratio [aOR]: 0.37, p<0.001; >34 vs. <24 years), being a man who has sex with men (MSM) (aOR: 2.47, p = 0.004; MSM vs. cisgender women), having higher viral load (aOR: 1.28, p<0.001) and higher CD4+ T cell count (aOR: 1.80, p<0.001; ≥500 vs. <200 cells/mm3 ) remained associated with higher odds of clustering. Compared to MSM, cisgender women and heterosexual men had significantly lower education (none or any elementary: 59.1% and 54.2% vs. 16.6%, p<0.001) and socio-economic status (low income: 36.4% and 29.0% vs. 18.6%, p = 0.03) than MSM. We identified 10 (2.6%) clusters with constant growth, for prioritized intervention, that included intersecting sexual risk groups, highly connected nodes and bridge nodes between possible sub-clusters with high growth potential.

CONCLUSIONS

HIV transmission in Mexico City is strongly driven by young MSM with higher education level and recent infection. Nevertheless, leveraging network inference, we identified actively growing clusters that could be prioritized for focused intervention with demographic and risk characteristics that do not necessarily reflect the ones observed in the overall clustering population. Further studies evaluating different models to predict growing clusters are warranted. Focused interventions will have to consider structural and risk disparities between the MSM and the heterosexual populations.

Longitudinal typing of molecular HIV clusters in a statewide epidemic

BACKGROUND

HIV molecular epidemiology is increasingly integrated into public health prevention. We conducted cluster typing to enhance characterization of a densely sampled statewide epidemic towards informing public health.

METHODS

We identified HIV clusters, categorized them into types, and evaluated their dynamics between 2004 and 2019 in Rhode Island. We grouped sequences by diagnosis year, assessed cluster changes between paired phylogenies, t0 and t1, representing adjacent years and categorized clusters as stable (cluster in t0 phylogeny = cluster in t1 phylogeny) or unstable (cluster in t0 ≠ cluster in t1). Unstable clusters were further categorized as emerging (t1 phylogeny only) or growing (larger in t1 phylogeny). We determined proportions of each cluster type, of individuals in each cluster type, and of newly diagnosed individuals in each cluster type, and assessed trends over time.

RESULTS

A total of 1727 individuals with available HIV-1 subtype B pol sequences were diagnosed in Rhode Island by 2019. Over time, stable clusters and individuals in them dominated the epidemic, increasing over time, with reciprocally decreasing unstable clusters and individuals in them. Conversely, proportions of newly diagnosed individuals in unstable clusters significantly increased. Within unstable clusters, proportions of emerging clusters and of individuals in them declined; whereas proportions of newly diagnosed individuals in growing clusters significantly increased over time.

CONCLUSION

Distinct molecular cluster types were identified in the Rhode Island epidemic. Cluster dynamics demonstrated increasing stable and decreasing unstable clusters driven by growing, rather than emerging clusters, suggesting consistent in-state transmission networks. Cluster typing could inform public health beyond conventional approaches and direct interventions.

Surveillance of HIV-1 primary infections in France from 2014 to 2016: toward stable resistance, but higher diversity, clustering and virulence?

OBJECTIVES

Patients with primary HIV-1 infection (PHI) are a particular population, giving important insight about ongoing evolution of transmitted drug resistance-associated mutation (TDRAM) prevalence, HIV diversity and clustering patterns. We describe these evolutions of PHI patients diagnosed in France from 2014 to 2016.

METHODS

A total of 1121 PHI patients were included. TDRAMs were characterized using the 2009 Stanford list and the French ANRS algorithm. Viral subtypes and recent transmission clusters (RTCs) were also determined.

RESULTS

Patients were mainly MSM (70%) living in the Paris area (42%). TDRAMs were identified among 10.8% of patients and rose to 18.6% when including etravirine and rilpivirine TDRAMs. Prevalences of PI-, NRTI-, first-generation NNRTI-, second-generation NNRTI- and integrase inhibitor-associated TDRAMs were 2.9%, 5.0%, 4.0%, 9.4% and 5.4%, respectively. In a multivariable analysis, age >40 years and non-R5 tropic viruses were associated with a >2-fold increased risk of TDRAMs. Regarding HIV diversity, subtype B and CRF02_AG (where CRF stands for circulating recombinant form) were the two main lineages (56% and 20%, respectively). CRF02_AG was associated with higher viral load than subtype B (5.83 versus 5.40 log10 copies/mL, P=0.004). We identified 138 RTCs ranging from 2 to 14 patients and including overall 41% from the global population. Patients in RTCs were younger, more frequently born in France and more frequently MSM.

CONCLUSIONS

Since 2007, the proportion of TDRAMs has been stable among French PHI patients. Non-B lineages are increasing and may be associated with more virulent CRF02_AG strains. The presence of large RTCs highlights the need for real-time cluster identification to trigger specific prevention action to achieve better control of the epidemic.

Priority Intervention Targets Identified Using an In-Depth Sampling HIV Molecular Network in a Non-Subtype B Epidemics Area

Molecular network analysis based on the genetic similarity of HIV-1 is increasingly used to guide targeted interventions. Nevertheless, there is a lack of experience regarding molecular network inferences and targeted interventions in combination with epidemiological information in areas with diverse epidemic strains of HIV-1.We collected 2,173 pol sequences covering 84% of the total newly diagnosed HIV-1 infections in Shenyang city, Northeast China, between 2016 and 2018. Molecular networks were constructed using the optimized genetic distance threshold for main subtypes obtained using sensitivity analysis of plausible threshold ranges. The transmission rates (TR) of each large cluster were assessed using Bayesian analyses. Molecular clusters with the characteristics of ≥5 newly diagnosed cases in 2018, high TR, injection drug users (IDUs), and transmitted drug resistance (TDR) were defined as priority clusters. Several HIV-1 subtypes were identified, with a predominance of CRF01_AE (71.0%, 1,542/2,173), followed by CRF07_BC (18.1%, 393/2,173), subtype B (4.5%, 97/2,173), other subtypes (2.6%, 56/2,173), and unique recombinant forms (3.9%, 85/2,173). The overall optimal genetic distance thresholds for CRF01_AE and CRF07_BC were both 0.007 subs/site. For subtype B, it was 0.013 subs/site. 861 (42.4%) sequences of the top three subtypes formed 239 clusters (size: 2-77 sequences), including eight large clusters (size ≥10 sequences). All the eight large clusters had higher TR (median TR = 52.4/100 person-years) than that of the general HIV infections in Shenyang (10.9/100 person-years). A total of ten clusters including 231 individuals were determined as priority clusters for targeted intervention, including eight large clusters (five clusters with≥5 newly diagnosed cases in 2018, one cluster with IDUs, and two clusters with TDR (K103N, Q58E/V179D), one cluster with≥5 newly diagnosed cases in 2018, and one IDUs cluster. In conclusion, a comprehensive analysis combining in-depth sampling HIV-1 molecular networks construction using subtype-specific optimal genetic distance thresholds, and baseline epidemiological information can help to identify the targets of priority intervention in an area epidemic for non-subtype B.

Dynamics of HIV-1 Molecular Networks Reveal Effective Control of Large Transmission Clusters in an Area Affected by an Epidemic of Multiple HIV Subtypes

This study reconstructed molecular networks of human immunodeficiency virus (HIV) transmission history in an area affected by an epidemic of multiple HIV-1 subtypes and assessed the efficacy of strengthened early antiretroviral therapy (ART) and regular interventions in preventing HIV spread. We collected demographic and clinical data of 2221 treatment-naïve HIV-1–infected patients in a long-term cohort in Shenyang, Northeast China, between 2008 and 2016. HIV pol gene sequencing was performed and molecular networks of CRF01_AE, CRF07_BC, and subtype B were inferred using HIV-TRACE with separate optimized genetic distance threshold. We identified 168 clusters containing ≥ 2 cases among CRF01_AE-, CRF07_BC-, and subtype B-infected cases, including 13 large clusters (≥ 10 cases). Individuals in large clusters were characterized by younger age, homosexual behavior, more recent infection, higher CD4 counts, and delayed/no ART (P < 0.001). The dynamics of large clusters were estimated by proportional detection rate (PDR), cluster growth predictor, and effective reproductive number (R_e). Most large clusters showed decreased or stable during the study period, indicating that expansion was slowing. The proportion of newly diagnosed cases in large clusters declined from 30 to 8% between 2008 and 2016, coinciding with an increase in early ART within 6 months after diagnosis from 24 to 79%, supporting the effectiveness of strengthened early ART and continuous regular interventions. In conclusion, molecular network analyses can thus be useful for evaluating the efficacy of interventions in epidemics with a complex HIV profile.

Comparative Circulation Dynamics of the Five Main HIV Types in China

The HIV epidemic in China accounts for 3% of the global HIV incidence. We compared the patterns and determinants of interprovincial spread of the five most prevalent circulating types. HIV pol sequences sampled across China were used to identify relevant transmission networks of the five most relevant HIV-1 types (B and circulating recombinant forms [CRFs] CRF01_AE, CRF07_BC, CRF08_BC, and CRF55_01B) in China. From these, the dispersal history across provinces was inferred. A generalized linear model (GLM) was used to test the association between migration rates among provinces and several measures of human mobility. A total of 10,707 sequences were collected between 2004 and 2017 across 26 provinces, among which 1,962 are newly reported here. A mean of 18 (minimum and maximum, 1 and 54) independent transmission networks involving up to 17 provinces were identified. Discrete phylogeographic analysis largely recapitulates the documented spread of the HIV types, which in turn, mirrors within-China population migration flows to a large extent. In line with the different spatiotemporal spread dynamics, the identified drivers thereof were also heterogeneous but are consistent with a central role of human mobility. The comparative analysis of the dispersal dynamics of the five main HIV types circulating in China suggests a key role of large population centers and developed transportation infrastructures as hubs of HIV dispersal. This advocates for coordinated public health efforts in addition to local targeted interventions.IMPORTANCE While traditional epidemiological studies are of great interest in describing the dynamics of epidemics, they struggle to fully capture the geospatial dynamics and factors driving the dispersal of pathogens like HIV as they have difficulties capturing linkages between infections. To overcome this, we used a discrete phylogeographic approach coupled to a generalized linear model extension to characterize the dynamics and drivers of the across-province spread of the five main HIV types circulating in China. Our results indicate that large urbanized areas with dense populations and developed transportation infrastructures are facilitators of HIV dispersal throughout China and highlight the need to consider harmonized country-wide public policies to control local HIV epidemics.

Molecular network-based intervention brings us closer to ending the HIV pandemic

Precise identification of HIV transmission among populations is a key step in public health responses. However, the HIV transmission network is usually difficult to determine. HIV molecular networks can be determined by phylogenetic approach, genetic distance-based approach, and a combination of both approaches. These approaches are increasingly used to identify transmission networks among populations, reconstruct the history of HIV spread, monitor the dynamics of HIV transmission, guide targeted intervention on key subpopulations, and assess the effects of interventions. Simulation and retrospective studies have demonstrated that these molecular network-based interventions are more cost-effective than random or traditional interventions. However, we still need to address several challenges to improve the practice of molecular network-guided targeting interventions to finally end the HIV epidemic. The data remain limited or difficult to obtain, and more automatic real-time tools are required. In addition, molecular and social networks must be combined, and technical parameters and ethnic issues warrant further studies.