Exploring Evolutionary and Transmission Dynamics of HIV Epidemic in Serbia: Bridging Socio-Demographic With Phylogenetic Approach

Application progress of latent class growth models in dynamic prevention and control strategies for acquired immunodeficiency syndrome

The prevention and control requirements for HIV/AIDS vary significantly among different populations, posing substantial challenges to the formulation and implementation of intervention strategies. Dynamically assessing the heterogeneity and disease progression trajectories of various groups is crucial. Latent class growth model (LCGM) serves as a statistical approach that fits a longitudinal data into N subgroups of individual development trajectories, identifying and analyzing the progression paths of different subgroups, thereby offering a novel perspective for disease control strategies. LCGM has shown significant advantages in the application of HIV/AIDS prevention and control, especially in gaining a deeper understanding and analysis of epidemiological characteristics, risk behaviors, psychological research, heterogeneity in testing, and dynamic changes. Summarizing the advantages and limitations of applying LCGM can provide a reliable basis for precise prevention and control of HIV/AIDS.

Distinct Rates and Transmission Patterns of Major HIV-1 Subtypes among Men who Have Sex with Men in Guangxi, China

The diversity and transmission patterns of major HIV-1 subtypes among MSM population in Guangxi remains unknown. Understanding the characteristics is crucial for effective intervention strategies. Between 2016 and 2021, we recruited individuals newly diagnosed with HIV-1 from MSM population in Guangxi. HIV-1 pol region was amplified and sequenced, and constructed molecular network, assessed clustering rate, cluster growth rate, spatial clustering, and calculating the basic reproductive number (R0) based on sequences data. We identified 16 prevalent HIV-1 subtypes among Guangxi MSM, with CRF07_BC (53.1%), CRF01_AE (26.23%), and CRF55_01B (12.96%) predominating. In the network, 618 individuals (66.17%) formed 59 clusters. Factors contributing to clustering included age < 30 years (AOR = 1.35), unmarried status (AOR = 1.67), CRF07_BC subtype (AOR = 3.21), and high viral load (AOR = 1.43). CRF07_BC had a higher likelihood of forming larger clusters and having higher degree than CRF01_AE and CRF55_01B. Notably, CRF07_BC has higher cluster growth rate and higher basic reproductive number than CRF01_AE and CRF55_01B. Our findings underscore CRF07_BC as a prominent driver of HIV-1 spread among Guangxi's MSM population, highlighting the viability of targeted interventions directed at specific subtypes and super clusters to control HIV-1 transmission within this population.

Characterization of Human Immunodeficiency Virus-1 Transmission Clusters and Transmitted Drug-Resistant Mutations in Croatia from 2019 to 2022

Molecular epidemiology of HIV-1 infection is challenging due to the highly diverse HIV-genome. We investigated the genetic diversity and prevalence of transmitted drug resistance (TDR) followed by phylogenetic analysis in 270 HIV-1 infected, treatment-naïve individuals from Croatia in the period 2019-2022. The results of this research confirmed a high overall prevalence of TDR of 16.7%. Resistance to nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside RTIs (NNRTIs), and protease inhibitors (PIs) was found in 9.6%, 7.4%, and 1.5% of persons, respectively. No resistance to integrase strand-transfer inhibitors (INSTIs) was found. Phylogenetic analysis revealed that 173/229 sequences (75.5%) were part of transmission clusters, and the largest identified was T215S, consisting of 45 sequences. Forward transmission was confirmed in several clusters. We compared deep sequencing (DS) with Sanger sequencing (SS) on 60 randomly selected samples and identified additional surveillance drug resistance mutations (SDRMs) in 49 of them. Our data highlight the need for baseline resistance testing in treatment-naïve persons. Although no major INSTIs were found, monitoring of SDRMs to INSTIs should be continued due to the extensive use of first- and second-generation INSTIs.

Not all clusters are equal: dynamics of molecular HIV-1 clusters in a statewide Rhode Island epidemic

OBJECTIVES

Molecular epidemiology is a powerful tool to characterize HIV epidemics and prioritize public health interventions. Typically, HIV clusters are assumed to have uniform patterns over time. We hypothesized that assessment of cluster evolution would reveal distinct cluster behavior, possibly improving molecular epidemic characterization, towards disrupting HIV transmission.

DESIGN

Retrospective cohort.

METHODS

Annual phylogenies were inferred by cumulative aggregation of all available HIV-1 pol sequences of individuals with HIV-1 in Rhode Island (RI) between 1990 and 2020, representing a statewide epidemic. Molecular clusters were detected in annual phylogenies by strict and relaxed cluster definition criteria, and the impact of annual newly-diagnosed HIV-1 cases to the structure of individual clusters was examined over time.

RESULTS

Of 2153 individuals, 31% (strict criteria) - 47% (relaxed criteria) clustered. Longitudinal tracking of individual clusters identified three cluster types: normal, semi-normal and abnormal. Normal clusters (83-87% of all identified clusters) showed predicted growing/plateauing dynamics, with approximately three-fold higher growth rates in large (15-18%) vs. small (∼5%) clusters. Semi-normal clusters (1-2% of all clusters) temporarily fluctuated in size and composition. Abnormal clusters (11-16% of all clusters) demonstrated collapses and re-arrangements over time. Borderline values of cluster-defining parameters explained dynamics of non-normal clusters.

CONCLUSIONS

Comprehensive tracing of molecular HIV clusters over time in a statewide epidemic identified distinct cluster types, likely missed in cross-sectional analyses, demonstrating that not all clusters are equal. This knowledge challenges current perceptions of consistent cluster behavior over time and could improve molecular surveillance of local HIV epidemics to better inform public health strategies.

HIV-1 subtype B spread through cross-border clusters in the Balkans: a molecular analysis in view of incidence trends

OBJECTIVES

To analyze phylogenetic relations and assess the role of cross-border clusters in the spread of HIV-1 subtype B across the Balkans, given the general trends of new HIV diagnoses in seven Balkan countries.

DESIGN

Retrospective phylogenetic and trend analysis.

METHODS

In-depth phylogenetic, phylodynamic and phylogeographic analysis performed on 2415 HIV-1 subtype B sequences from 1999 to 2019 using maximal likelihood and Bayesian methods. The joinpoint regression analysis of new HIV diagnoses by country and modes of transmission using 2004-2019 ECDC data.

RESULTS

Ninety-three HIV-1 Subtype B transmission clusters (68% of studied sequences) were detected of which four cross-border clusters (11% of studied sequences). Phylodynamic analysis showed activity of cross-border clusters up until the mid-2000s, with a subsequent stationary growth phase. Phylogeography analyses revealed reciprocal spread patterns between Serbia, Slovenia and Montenegro and several introductions to Romania from these countries and Croatia. The joinpoint analysis revealed a reduction in new HIV diagnoses in Romania, Greece and Slovenia, whereas an increase in Serbia, Bulgaria, Croatia and Montenegro, predominantly among MSM.

CONCLUSION

Differing trends of new HIV diagnoses in the Balkans mirror differences in preventive policies implemented in participating countries. Regional spread of HIV within the countries of former Yugoslavia has continued to play an important role even after country break-up, whereas the spread of subtype B through multiple introductions to Romania suggested the changing pattern of travel and migration linked to European integration of Balkan countries in the early 2000s.

Reconstructing the Temporal Origin and the Transmission Dynamics of the HIV Subtype B Epidemic in St. Petersburg, Russia

The HIV/AIDS epidemic in Russia is among the fastest growing in the world. HIV epidemic burden is non-uniform in different Russian regions and diverse key populations. An explosive epidemic has been documented among people who inject drugs (PWID) starting from the mid-1990s, whereas presently, the majority of new infections are linked to sexual transmission. Nationwide, HIV sub-subtype A6 (previously called A_FSU) predominates, with the increasing presence of other subtypes, namely subtype B and CRF063_02A. This study explores HIV subtype B sequences from St. Petersburg, collected from 2006 to 2020, in order to phylogenetically investigate and characterize transmission clusters, focusing on their evolutionary dynamics and potential for further growth, along with a socio-demographic analysis of the available metadata. In total, 54% (107/198) of analyzed subtype B sequences were found grouped in 17 clusters, with four transmission clusters with the number of sequences above 10. Using Bayesian MCMC inference, tMRCA of HIV-1 subtype B was estimated to be around 1986 (95% HPD 1984-1991), whereas the estimated temporal origin for the four large clusters was found to be more recent, between 2001 and 2005. The results of our study imply a complex pattern of the epidemic spread of HIV subtype B in St. Petersburg, Russia, still in the exponential growth phase, and in connection to the men who have sex with men (MSM) transmission, providing a useful insight needed for the design of public health priorities and interventions.

Integrating Phylogenetic Biomarker Data and Qualitative Approaches: An example of HIV Transmission Clusters as a Sampling Frame for Semistructured Interviews and Implications for the COVID-19 Era

Mixed methods studies of human disease that combine surveillance, biomarker, and qualitative data can help elucidate what drives epidemiological trends. Viral genetic data are rarely coupled with other types of data due to legal and ethical concerns about patient privacy. We developed a novel approach to integrate phylogenetic and qualitative methods in order to better target HIV prevention efforts. The overall aim of our mixed methods study was to characterize HIV transmission clusters. We combined surveillance data with HIV genomic data to identify cases whose viruses share enough similarities to suggest a recent common source of infection or participation in linked transmission chains. Cases were recruited through a multi-phase process to obtain consent for recruitment to semi-structured interviews. Through linkage of viral genetic sequences with epidemiological data, we identified individuals in large transmission clusters, which then served as a sampling frame for the interviews. In this article, we describe the multi-phase process and the limitations and challenges encountered. Our approach contributes to the mixed methods research field by demonstrating that phylogenetic analysis and surveillance data can be harnessed to generate a sampling frame for subsequent qualitative data collection, using an explanatory sequential design. The process we developed also respected protections of patient confidentiality. The novel method we devised may offer an opportunity to implement a sampling frame that allows for the recruitment and interview of individuals in high-transmission clusters to better understand what contributes to spread of other infectious diseases, including COVID-19.

Analysis of the Driving Factors of Active and Rapid Growth Clusters Among CRF07_BC-Infected Patients in a Developed Area in Eastern China

Background

The purpose of this study was to research the molecular transmission and genetic evolutionary characteristics among CRF07_BC-infected patients in a developed area in Eastern China.

Methods

Plasma samples from newly diagnosed HIV-1-positive patients from 2015–2018 and basic demographic and epidemiological information were obtained. Pol sequences from CRF07_BC-infected patients were selected for phylogenetic, molecular transmission network, and Bayesian evolutionary analyses.

Results

Pol sequences were successfully obtained from 258 samples of CRF07_BC. Phylogenetic analysis revealed 2 distinct lineages: lineage 1 (66.3%, 171/258), primarily from men who have sex with men (MSM) and some heterosexual individuals, and lineage 2 (33.7%, 87/258), primarily from heterosexual individuals. Under an optimal genetic distance of 0.01 substitutions/site, 163 individuals (63.2%, 163/258) formed 23 groups comprising 6 clusters and 17 dyads in the networks. A distinctly large and rapidly growing cluster (C1) containing 105 individuals was identified, in which MSM with ≥4 links had quite a high transmission risk (low educational background, active sexual behavior, low sexual protection awareness, etc.). According to Bayesian analyses, most C1 clades formed from 2005 to 2009, most of which were closely geographically related to CRF07_BC epidemic strains from Anhui province.

Conclusions

Here, we elucidated the local transmission characteristics and epidemic pattern of HIV-1 CRF07_BC, revealing that MSM (especially with ≥4 links) may be a significant driver in the formation of active and rapid growth networks in regional CRF07_BC epidemics. Thus, unique region– and risk group–specific transmission network analysis based on a molecular approach can provide critical and insightful information for more effective intervention strategies to limit future HIV-1 transmission.

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.

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.

Analysis of HIV-1 diversity, primary drug resistance and transmission networks in Croatia

Molecular epidemiology of HIV-1 infection in treatment-naive HIV-1 infected persons from Croatia was investigated. We included 403 persons, representing 92.4% of all HIV-positive individuals entering clinical care in Croatia in 2014–2017. Overall prevalence of transmitted drug resistance (TDR) was estimated at 16.4%. Resistance to nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside RTI (NNRTIs) and protease inhibitors (PIs) was found in 11.4%, 6.7% and 2.5% of persons, respectively. Triple-class resistance was determined in 2.2% of individuals. In addition, a single case (1.0%) of resistance to integrase strand-transfer inhibitors (InSTIs) was found. Deep sequencing was performed on 48 randomly selected samples and detected additional TDR mutations in 6 cases. Phylogenetic inference showed that 347/403 sequences (86.1%) were part of transmission clusters and identified forward transmission of resistance in Croatia, even that of triple-class resistance. The largest TDR cluster of 53 persons with T215S was estimated to originate in the year 1992. Our data show a continuing need for pre-treatment HIV resistance testing in Croatia. Even though a low prevalence of resistance to InSTI was observed, surveillance of TDR to InSTI should be continued.