HIV-TRACE (TRAnsmission Cluster Engine): a Tool for Large Scale Molecular Epidemiology of HIV-1 and Other Rapidly Evolving Pathogens

Molecular transmission network analysis of newly diagnosed HIV-1 infections in Nanjing from 2019 to 2021

OBJECTIVE

The objective of this study was to conduct a comprehensive analysis of the molecular transmission networks and transmitted drug resistance (TDR) patterns among individuals newly diagnosed with HIV-1 in Nanjing.

METHODS

Plasma samples were collected from newly diagnosed HIV patients in Nanjing between 2019 and 2021. The HIV pol gene was amplified, and the resulting sequences were utilized for determining TDR, identifying viral subtypes, and constructing molecular transmission network. Logistic regression analyses were employed to investigate the epidemiological characteristics associated with molecular transmission clusters.

RESULTS

A total of 1161 HIV pol sequences were successfully extracted from newly diagnosed individuals, each accompanied by reliable epidemiologic information. The analysis revealed the presence of multiple HIV-1 subtypes, with CRF 07_BC (40.57%) and CRF01_AE (38.42%) being the most prevalent. Additionally, six other subtypes and unique recombinant forms (URFs) were identified. The prevalence of TDR among the newly diagnosed cases was 7.84% during the study period. Employing a genetic distance threshold of 1.50%, the construction of the molecular transmission network resulted in the identification of 137 clusters, encompassing 613 nodes, which accounted for approximately 52.80% of the cases. Multivariate analysis indicated that individuals within these clusters were more likely to be aged ≥ 60, unemployed, baseline CD4 cell count ≥ 200 cells/mm3, and infected with the CRF119_0107 (P < 0.05). Furthermore, the analysis of larger clusters revealed that individuals aged ≥ 60, peasants, those without TDR, and individuals infected with the CRF119_0107 were more likely to be part of these clusters.

CONCLUSIONS

This study revealed the high risk of local HIV transmission and high TDR prevalence in Nanjing, especially the rapid spread of CRF119_0107. It is crucial to implement targeted interventions for the molecular transmission clusters identified in this study to effectively control the HIV epidemic.

Enhancements to the National HIV Surveillance System, United States, 2013-2023

HIV infection is monitored through the National HIV Surveillance System (NHSS) to help improve the health of people with HIV and reduce transmission. NHSS data are routinely used at federal, state, and local levels to monitor the distribution and transmission of HIV, plan and evaluate prevention and care programs, allocate resources, inform policy development, and identify and respond to rapid transmission in the United States. We describe the expanded use of HIV surveillance data since the 2013 NHSS status update, during which time the Centers for Disease Control and Prevention (CDC) coordinated to revise the HIV surveillance case definition to support the detection of early infection and reporting of laboratory data, expanded data collection to include information on sexual orientation and gender identity, enhanced data deduplication processes to improve quality, and expanded reporting to include social determinants of health and health equity measures. CDC maximized the effects of federal funding by integrating funding for HIV prevention and surveillance into a single program; the integration of program funding has expanded the use of HIV surveillance data and strengthened surveillance, resulting in enhanced cluster response capacity and intensified data-to-care activities to ensure sustained viral suppression. NHSS data serve as the primary source for monitoring HIV trends and progress toward achieving national initiatives, including the US Department of Health and Human Services' Ending the HIV Epidemic in the United States initiative, the White House's National HIV/AIDS Strategy (2022-2025), and Healthy People 2030. The NHSS will continue to modernize, adapt, and broaden its scope as the need for high-quality HIV surveillance data remains.

Optimization of genetic distance threshold for inferring the CRF01_AE molecular network based on next-generation sequencing

Introduction

HIV molecular network based on genetic distance (GD) has been extensively utilized. However, the GD threshold for the non-B subtype differs from that of subtype B. This study aimed to optimize the GD threshold for inferring the CRF01_AE molecular network.

Methods

Next-generation sequencing data of partial CRF01_AE pol sequences were obtained for 59 samples from 12 transmission pairs enrolled from a high-risk cohort during 2009 and 2014. The paired GD was calculated using the Tamura-Nei 93 model to infer a GD threshold range for HIV molecular networks.

Results

2,019 CRF01_AE pol sequences and information on recent HIV infection (RHI) from newly diagnosed individuals in Shenyang from 2016 to 2019 were collected to construct molecular networks to assess the ability of the inferred GD thresholds to predict recent transmission events. When HIV transmission occurs within a span of 1-4 years, the mean paired GD between the sequences of the donor and recipient within the same transmission pair were as follow: 0.008, 0.011, 0.013, and 0.023 substitutions/site. Using these four GD thresholds, it was found that 98.9%, 96.0%, 88.2%, and 40.4% of all randomly paired GD values from 12 transmission pairs were correctly identified as originating from the same transmission pairs. In the real world, as the GD threshold increased from 0.001 to 0.02 substitutions/site, the proportion of RHI within the molecular network gradually increased from 16.6% to 92.3%. Meanwhile, the proportion of links with RHI gradually decreased from 87.0% to 48.2%. The two curves intersected at a GD of 0.008 substitutions/site.

Discussion

A suitable range of GD thresholds, 0.008-0.013 substitutions/site, was identified to infer the CRF01_AE molecular transmission network and identify HIV transmission events that occurred within the past three years. This finding provides valuable data for selecting an appropriate GD thresholds in constructing molecular networks for non-B subtypes.

DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction

In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks and patterns of spread is critical to inform public health programs. Projections of transmission growth or decline among specific risk groups can aid in optimizing interventions, particularly when resources are limited. Phylogenetic trees have been widely used in the detection of transmission chains and high-risk populations. Moreover, tree topology and the incorporation of population parameters (phylodynamics) can be useful in reconstructing the evolutionary dynamics of an epidemic across space and time among individuals. We now demonstrate the utility of phylodynamic trees for transmission modeling and forecasting, developing a phylogeny-based deep learning system, referred to as DeepDynaForecast. Our approach leverages a primal-dual graph learning structure with shortcut multi-layer aggregation, which is suited for the early identification and prediction of transmission dynamics in emerging high-risk groups. We demonstrate the accuracy of DeepDynaForecast using simulated outbreak data and the utility of the learned model using empirical, large-scale data from the human immunodeficiency virus epidemic in Florida between 2012 and 2020. Our framework is available as open-source software (MIT license) at github.com/lab-smile/DeepDynaForcast.

Simulation of Full HIV Cluster Networks in a Nationally Representative Model Indicates Intervention Opportunities

BACKGROUND

Clusters of rapid HIV transmission in the United States are increasingly recognized through analysis of HIV molecular sequence data reported to the National HIV Surveillance System. Understanding the full extent of cluster networks is important to assess intervention opportunities. However, full cluster networks include undiagnosed and other infections that cannot be systematically observed in real life.

METHODS

We replicated HIV molecular cluster networks during 2015-2017 in the United States using a stochastic dynamic network simulation model of sexual transmission of HIV. Clusters were defined at the 0.5% genetic distance threshold. Ongoing priority clusters had growth of ≥3 diagnoses/year in multiple years; new priority clusters first had ≥3 diagnoses/year in 2017. We assessed the full extent, composition, and transmission rates of new and ongoing priority clusters.

RESULTS

Full clusters were 3-9 times larger than detected clusters, with median detected cluster sizes in new and ongoing priority clusters of 4 (range 3-9) and 11 (range 3-33), respectively, corresponding to full cluster sizes with a median of 14 (3-74) and 94 (7-318), respectively. A median of 36.3% (range 11.1%-72.6%) of infections in the full new priority clusters were undiagnosed. HIV transmission rates in these clusters were >4 times the overall rate observed in the entire simulation.

CONCLUSIONS

Priority clusters reflect networks with rapid HIV transmission. The substantially larger full extent of these clusters, high proportion of undiagnosed infections, and high transmission rates indicate opportunities for public health intervention and impact.

AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained hetero-sexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

Developing a next level integrated genomic surveillance: Advances in the molecular epidemiology of HIV in Germany

Advances in the molecular epidemiological studies of the Human Immunodeficiency Virus (HIV) at the Robert Koch Institute (RKI) by laboratory and bioinformatic automation should allow the processing of larger numbers of samples and more comprehensive and faster data analysis in order to provide a higher resolution of the current HIV infection situation in near real-time and a better understanding of the dynamic of the German HIV epidemic. The early detection of the emergence and transmission of new HIV variants is important for the adaption of diagnostics and treatment guidelines. Likewise, the molecular epidemiological detection and characterization of spatially limited HIV outbreaks or rapidly growing sub-epidemics is of great importance in order to interrupt the transmission pathways by regionally adapting prevention strategies. These aims are becoming even more important in the context of the SARS-CoV2 pandemic and the Ukrainian refugee movement, which both have effects on the German HIV epidemic that should be monitored to identify starting points for targeted public health measures in a timely manner. To this end, a next level integrated genomic surveillance of HIV is to be established.

The origin, dissemination, and molecular networks of HIV-1 CRF65_cpx strain in Hainan Island, China

BACKGROUND

HIV-1 CRF65_cpx strain carries drug-resistant mutations, which raises concerns about its potential for causing virologic failure. The CRF65_cpx ranks as the fourth most prevalent on Hainan Island, China. However, the origin and molecular epidemiology of CRF65_cpx strains in this area remain unclear. This study aims to estimate the spatial origins and dissemination patterns of HIV-1 CRF65_cpx in this specific region.

METHODS

Between 2018 and 2021, a total of 58 pol sequences of the CRF65_cpx were collected from HIV-positive patients on Hainan Island. The available CRF65_cpx pol sequences from public databases were compiled. The HIV-TRACE tool was used to construct transmission networks. The evolutionary history of the introduction and dissemination of HIV-1 CRF65_cpx on Hainan Island were analyzed using phylogenetic analysis and the Bayesian coalescent-based approach.

RESULTS

Among the 58 participants, 89.66% were men who have sex with men (MSM). The median age was 25 years, and 43.10% of the individuals had a college degree or above. The results indicated that 39 (67.24%) sequences were interconnected within a single transmission network. A consistent expansion was evident from 2019 to 2021, with an incremental annual addition of four sequences into the networks. Phylodynamic analyses showed that the CRF65_cpx on Hainan Island originated from Beijing (Bayes factor, BF = 17.4), with transmission among MSM on Hainan Island in 2013.2 (95%HPD: 2012.4, 2019.5), subsequently leading to an outbreak. Haikou was the local center of the CRF65_cpx epidemic. This strain propagated from Haikou to other locations, including Sanya (BF > 1000), Danzhou (BF = 299.3), Chengmai (BF = 27.0) and Tunchang (BF = 16.3). The analyses of the viral migration patterns between age subgroups and risk subgroups revealed that the viral migration directions were from "25-40 years old" to "17-24 years old" (BF = 14.6) and to "over 40 years old" (BF = 17.6), and from MSM to heterosexuals (BF > 1000) on Hainan Island.

CONCLUSION

Our analyses elucidate the transmission dynamics of CRF65_cpx strain on Hainan Island. Haikou is identified as the potential hotspot for CRF65_cpx transmission, with middle-aged MSM identified as the key population. These findings suggest that targeted interventions in hotspots and key populations may be more effective in controlling the HIV epidemic.

Molecular epidemiology to aid virtual elimination of HIV transmission in Australia

The Global UNAIDS 95/95/95 targets aim to increase the percentage of persons who know their HIV status, receive antiretroviral therapy, and have achieved viral suppression. Achieving these targets requires efforts to improve the public health response to increase access to care for those living with HIV, identify those yet undiagnosed with HIV early, and increase access to prevention for those most at risk of HIV acquisition. HIV infections in Australia are among the lowest globally having recorded significant declines in new diagnoses in the last decade. However, the HIV epidemic has changed with an increasing proportion of newly diagnosed infections among those born outside Australia observed in the last five years. Thus, the current prevention efforts are not enough to achieve the UNAIDS targets and virtual elimination across all population groups. We believe both are possible by including molecular epidemiology in the public health response. Molecular epidemiology methods have been crucial in the field of HIV prevention, particularly in demonstrating the efficacy of treatment as prevention. Cluster detection using molecular epidemiology can provide opportunities for the real-time detection of new outbreaks before they grow, and cluster detection programs are now part of the public health response in the USA and Canada. Here, we review what molecular epidemiology has taught us about HIV evolution and spread. We summarize how we can use this knowledge to improve public health measures by presenting case studies from the USA and Canada. We discuss the successes and challenges of current public health programs in Australia, and how we could use cluster detection as an add-on to identify gaps in current prevention measures easier and respond quicker to growing clusters. Lastly, we raise important ethical and legal challenges that need to be addressed when HIV genotypic data is used in combination with personal data.

ViralWasm: a client-side user-friendly web application suite for viral genomics

MOTIVATION

The genomic surveillance of viral pathogens such as SARS-CoV-2 and HIV-1 has been critical to modern epidemiology and public health, but the use of sequence analysis pipelines requires computational expertise, and web-based platforms require sending potentially sensitive raw sequence data to remote servers.

RESULTS

We introduce ViralWasm, a user-friendly graphical web application suite for viral genomics. All ViralWasm tools utilize WebAssembly to execute the original command line tools client-side directly in the web browser without any user setup, with a cost of just 2-3x slowdown with respect to their command line counterparts.

AVAILABILITY AND IMPLEMENTATION

The ViralWasm tool suite can be accessed at: https://niema-lab.github.io/ViralWasm.

Demographics of sources of HIV-1 transmission in Zambia: a molecular epidemiology analysis in the HPTN 071 PopART study

BACKGROUND

In the last decade, universally available antiretroviral therapy (ART) has led to greatly improved health and survival of people living with HIV in sub-Saharan Africa, but new infections continue to appear. The design of effective prevention strategies requires the demographic characterisation of individuals acting as sources of infection, which is the aim of this study.

METHODS

Between 2014 and 2018, the HPTN 071 PopART study was conducted to quantify the public health benefits of ART. Viral samples from 7124 study participants in Zambia were deep-sequenced as part of HPTN 071-02 PopART Phylogenetics, an ancillary study. We used these sequences to identify likely transmission pairs. After demographic weighting of the recipients in these pairs to match the overall HIV-positive population, we analysed the demographic characteristics of the sources to better understand transmission in the general population.

FINDINGS

We identified a total of 300 likely transmission pairs. 178 (59·4%) were male to female, with 130 (95% CI 110-150; 43·3%) from males aged 25-40 years. Overall, men transmitted 2·09-fold (2·06-2·29) more infections per capita than women, a ratio peaking at 5·87 (2·78-15·8) in the 35-39 years source age group. 40 (26-57; 13·2%) transmissions linked individuals from different communities in the trial. Of 288 sources with recorded information on drug resistance mutations, 52 (38-69; 18·1%) carried viruses resistant to first-line ART.

INTERPRETATION

HIV-1 transmission in the HPTN 071 study communities comes from a wide range of age and sex groups, and there is no outsized contribution to new infections from importation or drug resistance mutations. Men aged 25-39 years, underserved by current treatment and prevention services, should be prioritised for HIV testing and ART.

FUNDING

National Institute of Allergy and Infectious Diseases, US President's Emergency Plan for AIDS Relief, International Initiative for Impact Evaluation, Bill & Melinda Gates Foundation, National Institute on Drug Abuse, and National Institute of Mental Health.

Use of Next-Generation Sequencing in a State-Wide Strategy of HIV-1 Surveillance: Impact of the SARS-COV-2 Pandemic on HIV-1 Diagnosis and Transmission

BACKGROUND

The ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic posed an unpreceded threat to the management of other pandemics such as human immunodeficiency virus-1 (HIV-1) in the United States. The full impact of the SARS-CoV-2 pandemic on the HIV-1 pandemic needs to be evaluated.

METHODS

All individuals with newly reported HIV-1 diagnoses from NC State Laboratory of Public Health were enrolled in this prospective observational study, 2018-2021. We used a sequencing-based recency assay to identify recent HIV-1 infections and to determine the days postinfection (DPI) for each person at the time of diagnosis.

RESULTS

Sequencing used diagnostic serum samples from 814 individuals with new HIV-1 diagnoses spanning this 4-year period. Characteristics of individuals diagnosed in 2020 differed from those in other years. People of color diagnosed in 2021 were on average 6 months delayed in their diagnosis compared to those diagnosed in 2020. There was a trend that genetic networks were more known for individuals diagnosed in 2021. We observed no major integrase resistance mutations over the course of the study.

CONCLUSIONS

SARS-CoV-2 pandemic may contribute to the spread of HIV-1. Public health resources need to focus on restoring HIV-1 testing and interrupting active, ongoing, transmission.

Predicting Impacts of Contact Tracing on Epidemiological Inference from Phylogenetic Data

Robust sampling methods are foundational to many inference problems in the phylodynamic field, yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications, is not well understood. To investigate and quantify how this non-uniform sampling method influences recovered phylogenetic tree structure, we developed a new simulation tool called SEEPS (Sequence Evolution and Epidemiological Process Simulator) that allows for the simulation of contact tracing and the resulting transmission tree, pathogen phylogeny, and corresponding virus genetic sequences. Importantly, SEEPS takes within-host evolution into account when generating pathogen phylogenies and sequences from transmission histories. Using SEEPS, we demonstrate that contact tracing can significantly impact the structure of the resulting tree as described by popular tree statistics. Contact tracing generates phylogenies that are less balanced than the underlying transmission process, less representative of the larger epidemiological process, and affects the internal/external branch length ratios that characterize specific epidemiological scenarios. We also examine a 2007-2008 Swedish HIV-1 outbreak and the broader 1998-2010 European HIV-1 epidemic to highlight the differences in contact tracing and expected phylogenies. Aided by SEEPS, we show that the Swedish outbreak was strongly influenced by contact tracing even after downsampling, while the broader European Union epidemic showed little evidence of universal contact tracing, agreeing with the known epidemiological information about sampling and spread. SEEPS is available at github.com/MolEvolEpid/SEEPS.

Transmission network and phylogenetic analysis reveal older male-centered transmission of CRF01_AE and CRF07_BC in Guangxi, China

In China, the number of newly reported HIV infections in older people is increasing rapidly. However, clear information on the impact of older people on HIV transmission is limited. This study aims to reveal the local HIV transmission patterns, especially how older people affect virus transmission. Subtype analysis based on available pol sequences obtained from HIV patients revealed that CRF01_AE and CRF08_BC were predominant in patients aged <50 years, whereas CRF01_AE was predominant in older people aged ≥50 years (χ²= 29.299, P < 0.001). A total of 25 patients (5.2%, 25/484) were identified with recent HIV infection (RHI). Transmission network analysis found 267 genetically linked individuals forming 55 clusters (2-63 individuals), including 5 large transmission clusters and 12 transmission clusters containing RHI. Bayesian phylogenetic analysis suggested that transmission events in CRF01_AE and CRF07_BC were centred on older males, while transmission events in CRF08_BC were centred on younger males. Multivariable logistic regression analysis showed that older people were more likely to cluster within networks (AOR = 2.303, 95% CI: 1.012-5.241) and that RHI was a significant factor associated with high linkage (AOR = 3.468, 95% CI: 1.315-9.146). This study provides molecular evidence that older males play a central role in the local transmission of CRF01_AE and CRF07_BC in Guangxi. Given the current widespread of CRF01_AE and CRF07_BC in Guangxi, there is a need to recommend HIV screening as part of free national medical examinations for older people to improve early detection, timely treatment, and further reduce second-generation transmission.

Pretreatment HIV Drug Resistance and the Molecular Transmission Network Among HIV-Positive Individuals in China in 2022: Multicenter Observational Study

BACKGROUND

Emerging HIV drug resistance caused by increased usage of antiretroviral drugs (ARV) could jeopardize the success of standardized HIV management protocols in resource-limited settings.

OBJECTIVE

We aimed to characterize pretreatment HIV drug resistance (PDR) among HIV-positive individuals and risk factors in China in 2022.

METHODS

This cross-sectional study was conducted using 2-stage systematic sampling according to the World Health Organization's surveillance guidelines in 8 provincial-level administrative divisions in 2022. Demographic information and plasma samples were obtained from study participants. PDR was analyzed using the Stanford HIV drug resistance database, and the Tamura-Nei 93 model in HIV-TRACE was used to calculate pairwise matches with a genetic distance of 0.01 substitutions per site. Logistic regression was used to identify and estimate factors associated with PDR.

RESULTS

PDR testing was conducted on 2568 participants in 2022. Of the participants, 34.8% (n=893) were aged 30-49 years, 81.4% (n=2091) were male, and 3.2% (n=81) had prior ARV exposure. The prevalence of PDR to protease and reverse transcriptase regions, nonnucleoside reverse transcriptase inhibitors, nucleoside reverse transcriptase inhibitors, and protease inhibitors were 7.4% (n=190), 6.3% (n=163), 1.2% (n=32), and 0.2% (n=5), respectively. Yunnan, Jilin, and Zhejiang had much higher PDR incidence than did Sichuan. The prevalence of nonnucleoside reverse transcriptase inhibitor-related drug resistance was 6.1% (n=157) for efavirenz and 6.3% (n=163) for nevirapine. Multivariable logistic regression models indicated that participants who had prior ARV exposure (odds ratio [OR] 7.45, 95% CI 4.50-12.34) and the CRF55_01B HIV subtype (OR 2.61, 95% CI 1.41-4.83) were significantly associated with PDR. Among 618 (24.2%) sequences (nodes) associated with 253 molecular transmission clusters (size range 2-13), drug resistance mutation sites included K103, E138, V179, P225, V106, V108, L210, T215, P225, K238, and A98.

CONCLUSIONS

The overall prevalence of PDR in China in 2022 was modest. Targeted genotypic PDR testing and medication compliance interventions must be urgently expanded to address PDR among newly diagnosed people living with HIV in China.

Molecular HIV Clustering Among Individuals with Mpox and HIV Co-Morbidity in New York State, Excluding New York City

The 2022 global mpox outbreak created an opportunity to test the utility of molecular HIV surveillance (MHS) to identify high-risk transmission networks. Individuals diagnosed with mpox in New York State (NYS) outside New York City-[Rest of State (ROS)] were matched to the NYS HIV and sexually transmitted infection registries. The demographic characteristics of individuals diagnosed with mpox in ROS mirror national trends. HIV-mpox comorbid individuals were more likely to be included in HIV molecular clusters compared to persons living with diagnosed HIV in ROS overall, men who have sex with men (MSM) in ROS, and age-adjusted MSM (to match individuals with mpox diagnosis) in ROS. For the 3-year 0.5% clusters, which are used to define national priority clusters, the HIV-mpox comorbid individuals clustered 2.4 times more frequently than the age/risk-adjusted control group. This study supports the use of HIV MHS to identify populations for priority public health interventions.

Epidemiological characteristics of HIV transmission in southeastern China from 2015 to 2020 based on HIV molecular network

Objective

HIV/AIDS remains a global public health problem, and understanding the structure of social networks of people living with HIV/AIDS is of great importance to unravel HIV transmission, propose precision control and reduce new infections. This study aimed to investigate the epidemiological characteristics of HIV transmission in Fujian province, southeastern China from 2015 to 2020 based on HIV molecular network.

Methods

Newly diagnosed, treatment-naive HIV/AIDS patients were randomly sampled from Fujian province in 2015 and 2020. Plasma was sampled for in-house genotyping resistance test, and HIV molecular network was created using the HIV-TRACE tool. Factors affecting the inclusion of variables in the HIV molecular network were identified using univariate and multivariate logistic regression analyses.

Results

A total of 1,714 eligible cases were finally recruited, including 806 cases in 2015 and 908 cases in 2020. The dominant HIV subtypes were CRF01_AE (41.7%) and CRF07_BC (38.3%) in 2015 and CRF07_BC (53. 3%) and CRF01_AE (29.1%) in 2020, and the prevalence of HIV drug resistance was 4.2% in 2015 and 5.3% in 2020. Sequences of CRF07_BC formed the largest HIV-1 transmission cluster at a genetic distance threshold of both 1.5 and 0.5%. Univariate and multivariate logistic regression analyses showed that ages of under 20 years and over 60 years, CRF07_BC subtype, Han ethnicity, sampling in 2015, absence of HIV drug resistance, married with spouse, sampling from three cities of Jinjiang, Nanping and Quanzhou resulted in higher proportions of sequences included in the HIV transmission molecular network at a genetic distance threshold of 1.5% (p < 0.05).

Conclusion

Our findings unravel the HIV molecular transmission network of newly diagnosed HIV/AIDS patients in Fujian province, southeastern China, which facilitates the understanding of HIV transmission patterns in the province.

Network typologies predict future molecular linkages in the network of HIV transmission

OBJECTIVE

HIV molecular transmission network typologies have previously demonstrated associations to transmission risk; however, few studies have evaluated their predictive potential in anticipating future transmission events. To assess this, we tested multiple models on statewide surveillance data from the Florida Department of Health.

DESIGN

This was a retrospective, observational cohort study examining the incidence of new HIV molecular linkages within the existing molecular network of persons with HIV (PWH) in Florida.

METHODS

HIV-1 molecular transmission clusters were reconstructed for PWH diagnosed in Florida from 2006 to 2017 using the HIV-TRAnsmission Cluster Engine (HIV-TRACE). A suite of machine-learning models designed to predict linkage to a new diagnosis were internally and temporally externally validated using a variety of demographic, clinical, and network-derived parameters.

RESULTS

Of the 9897 individuals who received a genotype within 12 months of diagnosis during 2012-2017, 2611 (26.4%) were molecularly linked to another case within 1 year at 1.5% genetic distance. The best performing model, trained on two years of data, was high performing (area under the receiving operating curve = 0.96, sensitivity = 0.91, and specificity = 0.90) and included the following variables: age group, exposure group, node degree, betweenness, transitivity, and neighborhood.

CONCLUSIONS

In the molecular network of HIV transmission in Florida, individuals' network position and connectivity predicted future molecular linkages. Machine-learned models using network typologies performed superior to models using individual data alone. These models can be used to more precisely identify subpopulations for intervention.

Transmitted drug resistance and transmission clusters among ART-naïve HIV-1-infected individuals from 2019 to 2021 in Nanjing, China

Background

Transmitted drug resistance (TDR) is an increasingly prevalent problem worldwide, which will significantly compromise the effectiveness of HIV treatments. However, in Nanjing, China, there is still a dearth of research on the prevalence and transmission of TDR among ART-naïve HIV-1-infected individuals. This study aimed to understand the prevalence and transmission of TDR in Nanjing.

Methods

A total of 1,393 participants who were newly diagnosed with HIV-1 and had not received ART between January 2019 and December 2021 were enrolled in this study. HIV-1 pol gene sequence was obtained by viral RNA extraction and nested PCR amplification. Genotypes, TDR and transmission cluster analyses were conducted using phylogenetic tree, Stanford HIV database algorithm and HIV-TRACE, respectively. Univariate and multivariate logistic regression analyses were performed to identify the factors associated with TDR.

Results

A total of 1,161 sequences were successfully sequenced, of which CRF07_BC (40.6%), CRF01_AE (38.4%) and CRF105_0107 (6.3%) were the main HIV-1 genotypes. The overall prevalence of TDR was 7.8%, with 2.0% to PIs, 1.0% to NRTIs, and 4.8% to NNRTIs. No sequence showed double-class resistance. Multivariate logistic regression analysis revealed that compared with CRF01_AE, subtype B (OR = 2.869, 95%CI: 1.093-7.420) and female (OR = 2.359, 95%CI: 1.182-4.707) were risk factors for TDR. Q58E was the most prevalent detected protease inhibitor (PI) -associated mutation, and V179E was the most frequently detected non-nucleoside reverse transcriptase inhibitor (NNRTI) -associated mutation. A total of 613 (52.8%) sequences were segregated into 137 clusters, ranging from 2 to 74 sequences. Among 44 individuals with TDR (48.4%) within 21 clusters, K103N/KN was the most frequent TDR-associated mutation (31.8%), followed by Q58E/QE (20.5%) and G190A (15.9%). Individuals with the same TDR-associated mutations were usually cross-linked in transmission clusters. Moreover, we identified 9 clusters in which there was a transmission relationship between drug-resistant individuals, and 4 clusters in which drug-resistant cases increased during the study period.

Conclusion

The overall prevalence of TDR in Nanjing was at a moderate level during the past 3 years. However, nearly half of TDR individuals were included in the transmission clusters, and some drug-resistant individuals have transmitted in the clusters. Therefore, HIV drug-resistance prevention, monitoring and response efforts should be sustained and expanded to reduce the prevalence and transmission of TDR in Nanjing.

Assessing the reliability of the CD4 depletion model in the presence of Ending the HIV Epidemic initiatives

BACKGROUND

Accurate estimates of HIV incidence are necessary to monitor progress towards Ending the HIV Epidemic (EHE) initiative targets (90% decline by 2030). U.S. incidence estimates are derived from a CD4 depletion model (CD4 model). We performed simulation-based analyses to investigate the ability of this model to estimate HIV incidence when implementing EHE interventions that have the potential to shorten the duration between HIV infection and diagnosis (diagnosis delay).

METHODS

Our simulation study evaluates the impact of three parameters on the accuracy of incidence estimates derived from the CD4 model: rate of HIV incidence decline, length of diagnosis delay, and sensitivity of using CD4 + cell counts to identify new infections (recency error). We model HIV incidence and diagnoses after the implementation of a theoretical prevention intervention and compare HIV incidence estimates derived from the CD4 model to simulated incidence.

RESULTS

Theoretical interventions that shortened the diagnosis delay (10-50%) result in overestimation of HIV incidence by the CD4 model (10-92%) in the first year and by more than 10% for the first 6 years after implementation of the intervention. Changes in the rate of HIV incidence decline and the presence of recency error had minimal impact on the accuracy of incidence estimates derived from the CD4 model.

CONCLUSION

In the setting of EHE interventions to identify persons with HIV earlier during infection, the CD4 model overestimates HIV incidence. Alternative methods to estimate incidence based on objective measures of incidence are needed to assess and monitor EHE interventions.

Predictors of HIV Molecular Cluster Membership and Implications for Partner Services

Public health surveillance data used in HIV molecular cluster analyses lack contextual information that is available from partner services (PS) data. Integrating these data sources in retrospective analyses can enrich understanding of the risk profile of people in clusters. In this study, HIV molecular clusters were identified and matched to information on partners and other information gleaned at the time of diagnosis, including coinfection with syphilis. We aimed to produce a more complete understanding of molecular cluster membership in Houston, Texas, a city ranking ninth nationally in rate of new HIV diagnoses that may benefit from retrospective matched analyses between molecular and PS data to inform future intervention. Data from PS were matched to molecular HIV records of people newly diagnosed from 2012 to 2018. By conducting analyses in HIV-TRACE (TRAnsmission Cluster Engine) using viral genetic sequences, molecular clusters were detected. Multivariable logistic regression models were used to estimate the association between molecular cluster membership and completion of a PS interview, number of named partners, and syphilis coinfection. Using data from 4,035 people who had a viral genetic sequence and matched PS records, molecular cluster membership was not significantly associated with completion of a PS interview. Among those with sequences who completed a PS interview (n = 3,869), 45.3% (n = 1,753) clustered. Molecular cluster membership was significantly associated with naming 1 or 3+ partners compared with not naming any partners [adjusted odds ratio, aOR: 1.27 (95% confidence interval, CI: 1.08-1.50), p = .003 and aOR: 1.38 (95% CI: 1.06-1.81), p = .02]. Alone, coinfection with syphilis was not significantly associated with molecular cluster membership. Syphilis coinfection was associated with molecular cluster membership when coupled with incarceration [aOR: 1.91 (95% CI: 1.08-3.38), p = .03], a risk for treatment interruption. Enhanced intervention among those with similar profiles, such as people coinfected with other risks, may be warranted.

An Automated Bioinformatics Pipeline Informing Near-Real-Time Public Health Responses to New HIV Diagnoses in a Statewide HIV Epidemic

Molecular HIV cluster data can guide public health responses towards ending the HIV epidemic. Currently, real-time data integration, analysis, and interpretation are challenging, leading to a delayed public health response. We present a comprehensive methodology for addressing these challenges through data integration, analysis, and reporting. We integrated heterogeneous data sources across systems and developed an open-source, automatic bioinformatics pipeline that provides molecular HIV cluster data to inform public health responses to new statewide HIV-1 diagnoses, overcoming data management, computational, and analytical challenges. We demonstrate implementation of this pipeline in a statewide HIV epidemic and use it to compare the impact of specific phylogenetic and distance-only methods and datasets on molecular HIV cluster analyses. The pipeline was applied to 18 monthly datasets generated between January 2020 and June 2022 in Rhode Island, USA, that provide statewide molecular HIV data to support routine public health case management by a multi-disciplinary team. The resulting cluster analyses and near-real-time reporting guided public health actions in 37 phylogenetically clustered cases out of 57 new HIV-1 diagnoses. Of the 37, only 21 (57%) clustered by distance-only methods. Through a unique academic-public health partnership, an automated open-source pipeline was developed and applied to prospective, routine analysis of statewide molecular HIV data in near-real-time. This collaboration informed public health actions to optimize disruption of HIV transmission.

Public Health Response to Clusters of Rapid HIV Transmission Among Hispanic or Latino Gay, Bisexual, and Other Men Who Have Sex with Men - Metropolitan Atlanta, Georgia, 2021-2022

During February 2021-June 2022, the Georgia Department of Public Health (GDPH) detected five clusters of rapid HIV transmission concentrated among Hispanic or Latino (Hispanic) gay, bisexual, and other men who have sex with men (MSM) in metropolitan Atlanta. The clusters were detected through routine analysis of HIV-1 nucleotide sequence data obtained through public health surveillance (1,2). Beginning in spring 2021, GDPH partnered with health districts with jurisdiction in four metropolitan Atlanta counties (Cobb, DeKalb, Fulton, and Gwinnett) and CDC to investigate factors contributing to HIV spread, epidemiologic characteristics, and transmission patterns. Activities included review of surveillance and partner services interview data,† medical chart reviews, and qualitative interviews with service providers and Hispanic MSM community members. By June 2022, these clusters included 75 persons, including 56% who identified as Hispanic, 96% who reported male sex at birth, 81% who reported male-to-male sexual contact, and 84% of whom resided in the four metropolitan Atlanta counties. Qualitative interviews identified barriers to accessing HIV prevention and care services, including language barriers, immigration- and deportation-related concerns, and cultural norms regarding sexuality-related stigma. GDPH and the health districts expanded coordination, initiated culturally concordant HIV prevention marketing and educational activities, developed partnerships with organizations serving Hispanic communities to enhance outreach and services, and obtained funding for a bilingual patient navigation program with academic partners to provide staff members to help persons overcome barriers and understand the health care system. HIV molecular cluster detection can identify rapid HIV transmission among sexual networks involving ethnic and sexual minority groups, draw attention to the needs of affected populations, and advance health equity through tailored responses that address those needs.

Quantifying and Predicting Ongoing Human Immunodeficiency Virus Type 1 Transmission Dynamics in Switzerland Using a Distance-Based Clustering Approach

BACKGROUND

Despite effective prevention approaches, ongoing human immunodeficiency virus 1 (HIV-1) transmission remains a public health concern indicating a need for identifying its drivers.

METHODS

We combined a network-based clustering method using evolutionary distances between viral sequences with statistical learning approaches to investigate the dynamics of HIV transmission in the Swiss HIV Cohort Study and to predict the drivers of ongoing transmission.

RESULTS

We found that only a minority of clusters and patients acquired links to new infections between 2007 and 2020. While the growth of clusters and the probability of individual patients acquiring new links in the transmission network was associated with epidemiological, behavioral, and virological predictors, the strength of these associations decreased substantially when adjusting for network characteristics. Thus, these network characteristics can capture major heterogeneities beyond classical epidemiological parameters. When modeling the probability of a newly diagnosed patient being linked with future infections, we found that the best predictive performance (median area under the curve receiver operating characteristic AUCROC = 0.77) was achieved by models including characteristics of the network as predictors and that models excluding them performed substantially worse (median AUCROC = 0.54).

CONCLUSIONS

These results highlight the utility of molecular epidemiology-based network approaches for analyzing and predicting ongoing HIV transmission dynamics. This approach may serve for real-time prospective assessment of HIV transmission.

HIV Drug Resistance in Adults Initiating or Reinitiating Antiretroviral Therapy in Uruguay-Results of a Nationally Representative Survey, 2018-2019

The first nationally representative cross-sectional HIV drug resistance (HIVDR) survey was conducted in Uruguay in 2018-2019 among adults diagnosed with HIV and initiating or reinitiating antiretroviral therapy (ART). Protease, reverse transcriptase, and integrase genes of HIV-1 were sequenced. A total of 206 participants were enrolled in the survey; 63.2% were men, 85.7% were >25 years of age, and 35.6% reported previous exposure to antiretroviral (ARV) drugs. The prevalence of HIVDR to efavirenz or nevirapine was significantly higher (OR: 1.82, p < 0.001) in adults with previous ARV drug exposure (20.3%, 95% CI: 18.7-22.0%) compared to adults without previous ARV drug exposure (12.3%, 11.0-13.8%). HIVDR to any nucleoside reverse transcriptase inhibitors was 10.3% (9.4-11.2%). HIVDR to ritonavir-boosted protease inhibitors was 1.5% (1.1-2.1%); resistance to ritonavir-boosted darunavir was 0.9% (0.4-2.1%) among adults without previous ARV drug exposure and it was not observed among adults with previous ARV drug exposure. Resistance to integrase inhibitors was 12.7% (11.7-13.8%), yet HIVDR to dolutegravir, bictegravir, and cabotegravir was not observed. The high level (>10%) of HIVDR to efavirenz highlights the need to accelerate the transition to the WHO-recommended dolutegravir-based ART. Access to dolutegravir-based ART should be prioritised for people reporting previous ARV drug exposure.

Molecular Network Analysis Discloses the Limited Contribution to HIV Transmission for Patients with Late HIV Diagnosis in Northeast China

In the "treat all" era, the high rate of late HIV diagnosis (LHD) worldwide remains an impediment to ending the HIV epidemic. In this study, we analyzed LHD in newly diagnosed people living with HIV (PLWH) and its impact on HIV transmission in Northeast China. Sociodemographic information, baseline clinical data, and plasma samples obtained from all newly diagnosed PLWH in Shenyang, the largest city in Northeast China, between 2016 and 2019 were evaluated. Multivariate logistic regression analysis was performed to identify risk factors associated with LHD. A molecular network based on the HIV pol gene was constructed to assess the risk of HIV transmission with LHD. A total of 2882 PLWH, including 882 (30.6%) patients with LHD and 1390 (48.2%) patients with non-LHD, were enrolled. The risk factors for LHD were older age (≥ 30 years: p < .01) and diagnosis in the general population through physical examination (p < .0001). Moreover, the molecular network analysis revealed that the clustering rate (p < .0001), the fraction of individuals with ≥ 4 links (p = .0847), and the fraction of individuals linked to recent HIV infection (p < .0001) for LHD were significantly or marginally significantly lower than those recorded for non-LHD. Our study indicates the major risk factors associated with LHD in Shenyang and their limited contribution to HIV transmission, revealing that the peak of HIV transmission of LHD at diagnosis may have been missed. Early detection, diagnosis, and timely intervention for LHD may prevent HIV transmission.

From components to communities: bringing network science to clustering for molecular epidemiology

Defining clusters of epidemiologically related infections is a common problem in the surveillance of infectious disease. A popular method for generating clusters is pairwise distance clustering, which assigns pairs of sequences to the same cluster if their genetic distance falls below some threshold. The result is often represented as a network or graph of nodes. A connected component is a set of interconnected nodes in a graph that are not connected to any other node. The prevailing approach to pairwise clustering is to map clusters to the connected components of the graph on a one-to-one basis. We propose that this definition of clusters is unnecessarily rigid. For instance, the connected components can collapse into one cluster by the addition of a single sequence that bridges nodes in the respective components. Moreover, the distance thresholds typically used for viruses like HIV-1 tend to exclude a large proportion of new sequences, making it difficult to train models for predicting cluster growth. These issues may be resolved by revisiting how we define clusters from genetic distances. Community detection is a promising class of clustering methods from the field of network science. A community is a set of nodes that are more densely inter-connected relative to the number of their connections to external nodes. Thus, a connected component may be partitioned into two or more communities. Here we describe community detection methods in the context of genetic clustering for epidemiology, demonstrate how a popular method (Markov clustering) enables us to resolve variation in transmission rates within a giant connected component of HIV-1 sequences, and identify current challenges and directions for further work.

Insights into HIV-1 Transmission Dynamics Using Routinely Collected Data in the Mid-Atlantic United States

Background: Molecular epidemiological approaches provide opportunities to characterize HIV transmission dynamics. We analyzed HIV sequences and virus load (VL) results obtained during 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 ambiguity ≤0.5% was considered indicative of early infection. Descriptive statistics were applied to characterize 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 using 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 management provide insights into regional transmission dynamics. Our findings demonstrate the additional 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.

Optimized phylogenetic clustering of HIV-1 sequence data for public health applications

Clusters of genetically similar infections suggest rapid transmission and may indicate priorities for public health action or reveal underlying epidemiological processes. However, clusters often require user-defined thresholds and are sensitive to non-epidemiological factors, such as non-random sampling. Consequently the ideal threshold for public health applications varies substantially across settings. Here, we show a method which selects optimal thresholds for phylogenetic (subset tree) clustering based on population. We evaluated this method on HIV-1 pol datasets (n = 14, 221 sequences) from four sites in USA (Tennessee, Washington), Canada (Northern Alberta) and China (Beijing). Clusters were defined by tips descending from an ancestral node (with a minimum bootstrap support of 95%) through a series of branches, each with a length below a given threshold. Next, we used pplacer to graft new cases to the fixed tree by maximum likelihood. We evaluated the effect of varying branch-length thresholds on cluster growth as a count outcome by fitting two Poisson regression models: a null model that predicts growth from cluster size, and an alternative model that includes mean collection date as an additional covariate. The alternative model was favoured by AIC across most thresholds, with optimal (greatest difference in AIC) thresholds ranging 0.007-0.013 across sites. The range of optimal thresholds was more variable when re-sampling 80% of the data by location (IQR 0.008 - 0.016, n = 100 replicates). Our results use prospective phylogenetic cluster growth and suggest that there is more variation in effective thresholds for public health than those typically used in clustering studies.

Impact of molecular sequence data completeness on HIV cluster detection and a network science approach to enhance detection

Detection of viral transmission clusters using molecular epidemiology is critical to the response pillar of the Ending the HIV Epidemic initiative. Here, we studied whether inference with an incomplete dataset would influence the accuracy of the reconstructed molecular transmission network. We analyzed viral sequence data available from ~ 13,000 individuals with diagnosed HIV (2012-2019) from Houston Health Department surveillance data with 53% completeness (n = 6852 individuals with sequences). We extracted random subsamples and compared the resulting reconstructed networks versus the full-size network. Increasing simulated completeness was associated with an increase in the number of detected clusters. We also subsampled based on the network node influence in the transmission of the virus where we measured Expected Force (ExF) for each node in the network. We simulated the removal of nodes with the highest and then lowest ExF from the full dataset and discovered that 4.7% and 60% of priority clusters were detected respectively. These results highlight the non-uniform impact of capturing high influence nodes in identifying transmission clusters. Although increasing sequence reporting completeness is the way to fully detect HIV transmission patterns, reaching high completeness has remained challenging in the real world. Hence, we suggest taking a network science approach to enhance performance of molecular cluster detection, augmented by node influence information.

SOPHIE: Viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework

Genomic epidemiology is now widely used for viral outbreak investigations. Still, this methodology faces many challenges. First, few methods account for intra-host viral diversity. Second, maximum parsimony principle continues to be employed for phylogenetic inference of transmission histories, even though maximum likelihood or Bayesian models are usually more consistent. Third, many methods utilize case-specific data, such as sampling times or infection exposure intervals. This impedes study of persistent infections in vulnerable groups, where such information has a limited use. Finally, most methods implicitly assume that transmission events are independent, although common source outbreaks violate this assumption. We propose a maximum likelihood framework, SOPHIE, based on the integration of phylogenetic and random graph models. It infers transmission networks from viral phylogenies and expected properties of inter-host social networks modeled as random graphs with given expected degree distributions. SOPHIE is scalable, accounts for intra-host diversity, and accurately infers transmissions without case-specific epidemiological data.

A deep learning approach to real-time HIV outbreak detection using genetic data

Pathogen genomic sequence data are increasingly made available for epidemiological monitoring. A main interest is to identify and assess the potential of infectious disease outbreaks. While popular methods to analyze sequence data often involve phylogenetic tree inference, they are vulnerable to errors from recombination and impose a high computational cost, making it difficult to obtain real-time results when the number of sequences is in or above the thousands. Here, we propose an alternative strategy to outbreak detection using genomic data based on deep learning methods developed for image classification. The key idea is to use a pairwise genetic distance matrix calculated from viral sequences as an image, and develop convolutional neutral network (CNN) models to classify areas of the images that show signatures of active outbreak, leading to identification of subsets of sequences taken from an active outbreak. We showed that our method is efficient in finding HIV-1 outbreaks with R0 ≥ 2.5, and overall a specificity exceeding 98% and sensitivity better than 92%. We validated our approach using data from HIV-1 CRF01 in Europe, containing both endemic sequences and a well-known dual outbreak in intravenous drug users. Our model accurately identified known outbreak sequences in the background of slower spreading HIV. Importantly, we detected both outbreaks early on, before they were over, implying that had this method been applied in real-time as data became available, one would have been able to intervene and possibly prevent the extent of these outbreaks. This approach is scalable to processing hundreds of thousands of sequences, making it useful for current and future real-time epidemiological investigations, including public health monitoring using large databases and especially for rapid outbreak identification.

Antiretroviral therapy initiation within 7 and 8-30 days post-HIV diagnosis demonstrates similar benefits in resource-limited settings

We estimated the optimum time to initiate antiretroviral therapy (ART) in a retrospective observational cohort. We observed that ART initiation 7 days or less ( n  = 817) and 8-30 days ( n  = 1009) were the most important factors with viral suppression, and had similar viral suppression rate, CD4 + T-cell count increase and fractions of individuals with links at least 4 and individuals linked to recent HIV infection in HIV molecular networks. This study provides real-world evidence on the benefits of rapid ART initiation in resource-limited setting.

HIV-1 pretreatment drug resistance and genetic transmission network in the southwest border region of China

BACKGROUND

HIV drug resistance increased with the widespread use of antiretroviral drugs, and posed great threat to antiretroviral therapy (ART). Pu'er Prefecture, lying in the southwest of Yunnan Province, China, borders Myanmar, Laos and Vietnam, is also the area where AIDS was discovered earlier, however, in which there has been no information on HIV drug resistance.

METHODS

A cross-sectional survey of pretreatment drug resistance (PDR) was conducted in Pu'er Prefecture in 2021. Partial pol gene sequences were obtained to analyze drug resistance and construct genetic transmission network. HIV drug resistance was analyzed using the Stanford University HIVdb algorithm.

RESULTS

A total of 295 sequences were obtained, among which 11 HIV-1 strain types were detected and CRF08_BC (62.0%, 183/295) was the predominant one. Drug resistance mutations (DRMs) were detected in 42.4% (125/295) of the sequences. The prevalence of PDR to any antiretroviral drugs, nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs) and protease inhibitors (PIs) were 10.8% (32/295), 9.5% (28/295), 1.0% (3/295) and 0.3% (1/295), respectively. The risk of PDR occurrence was higher among individuals with CRF01_AE strain types. HIV-1 molecular network was constructed, in which 56.0% (42/75) of links were transregional, and 54.7% (41/75) of links were associated with Lancang County. Among the sequences in the network, 36.8% (35/95) harbored DRMs, and 9.5% (9/95) were drug resistance strains. Furthermore, 8 clusters had shared DRM.

CONCLUSION

The overall prevalence of PDR in this study was in a moderate level, but NNRTIs resistance was very approaching to the threshold of public response initiation. PDR was identified in the transmission network, and DRMs transmission was observed. These findings suggested that the consecutive PDR surveillance should be conducted in this region.

Molecular transmission network of pretreatment drug resistance among human immunodeficiency virus-positive individuals and the impact of virological failure on those who received antiretroviral therapy in China

Objectives

We investigated the prevalence of pretreatment drug resistance (PDR), the molecular transmission network among HIV-positive individuals, and the impact of virological failure on those who received antiretroviral therapy (ART) in China.

Methods

Based on the World Health Organization (WHO) surveillance guidelines for PDR, a baseline survey and follow-up were conducted in 2018 and 2021, respectively. Demographic information and plasma samples were obtained from all participants. HIV pol gene region sequences were used to analyze the PDR and molecular transmission networks using the Stanford HIV database algorithm and HIV-TRACE, respectively. This study assessed the odds ratios (OR) of PDR to virological failure (viral load ≥ 50 copies/mL) after 3 years of ART using multivariable logistic regression.

Results

Of the 4,084 individuals, 370 (9.1%) had PDR. The prevalence of PDR to non-nucleoside reverse transcriptase inhibitors (5.2%) was notably higher than that to nucleoside reverse transcriptase inhibitors (0.7%, p < 0.001), protease inhibitors (3.0%, p < 0.001), and multidrug resistance (0.3%, p < 0.001). A total of 1,339 (32.8%) individuals from 361 clusters were enrolled in the molecular transmission network. Of the 361 clusters, 22 included two or more individuals with PDR. The prevalence of virological failure among HIV-positive individuals after 3 years of ART without PDR, those with PDR to Chinese listed drugs, and those with PDR to other drugs was 7.9, 14.3, and 12.6%, respectively. Compared with that in HIV-positive individuals without PDR, virological failure after 3 years of ART was significantly higher (OR: 2.02, 95% confidence interval (CI): 1.25–3.27) and not significantly different (OR: 1.72, 95% CI: 0.87–3.43) in individuals with PDR to Chinese listed drugs and those with PDR to other drugs, respectively. Missed doses in the past month were significantly associated with virological failure (OR, 2.82; 95% CI: 4.08–5.89).

Conclusion

The overall prevalence of PDR was close to a high level and had an impact on virological failure after 3 years of ART. Moreover, HIV drug-resistant strains were transmitted in the molecular transmission network. These results illustrate the importance of monitoring PDR and ensuring virological suppression through drug adherence.

Undiagnosed HIV Infections May Drive HIV Transmission in the Era of "Treat All": A Deep-Sampling Molecular Network Study in Northeast China during 2016 to 2019

Universal antiretroviral therapy (ART, “treat all”) was recommended by the World Health Organization in 2015; however, HIV-1 transmission is still ongoing. This study characterizes the drivers of HIV transmission in the “treat all” era. Demographic and clinical information and HIV pol gene were collected from all newly diagnosed cases in Shenyang, the largest city in Northeast China, during 2016 to 2019. Molecular networks were constructed based on genetic distance and logistic regression analysis was used to assess potential transmission source characteristics. The cumulative ART coverage in Shenyang increased significantly from 77.0% (485/630) in 2016 to 93.0% (2598/2794) in 2019 (p < 0.001). Molecular networks showed that recent HIV infections linked to untreated individuals decreased from 61.6% in 2017 to 28.9% in 2019, while linking to individuals with viral suppression (VS) increased from 9.0% to 49.0% during the same time frame (p < 0.001). Undiagnosed people living with HIV (PLWH) hidden behind the links between index cases and individuals with VS were likely to be male, younger than 25 years of age, with Manchu nationality (p < 0.05). HIV transmission has declined significantly in the era of “treat all”. Undiagnosed PLWH may drive HIV transmission and should be the target for early detection and intervention.

Epidemic Characteristics of HIV Drug Resistance in Hefei, Anhui Province

To study the characteristics of HIV pretreatment drug resistance (PDR) and acquired drug resistance (ADR) in Hefei, a cross-sectional survey was used to collect 816 samples from newly reported HIV infections from 2017 to 2020 and 127 samples from HIV infections with virological failure from 2018 to 2019 in Hefei. HIV drug resistance levels and drug resistance mutations were interpreted using the Stanford Drug Resistance Database. Molecular networks were constructed by HIV-TRACE. Among the newly reported infections in Hefei, the prevalence of PDR was 6.4% (52/816). The drug resistance mutations were mainly V179E/D/T (12.4%), K103N (1.3%), and V106I/M (1.3%). In addition, it was found that the CRF55_01B subtype had a higher drug resistance rate than other subtypes (p < 0.05). Molecular network analysis found that K103N and V179E may be transmitted in the cluster of the CRF55_01B subtype. The prevalence of ADR among HIV infections with virological failure was 38.6% (49/127), and the drug resistance mutations were mainly M184V (24.4%), K103N/S (15.7%), Y181C (11.0%), G190S/A/E (10.2%), and V106M/I (10.2%). The molecular network was constructed by combining HIV infections with virological failure and newly reported infections; M184V and Y181C may be transmitted between them. The chi-square trend test results indicated that the higher the viral load level, the greater the number of newly reported infections linked to the infections with virological failure in the molecular network. In conclusion, interventions should focus on infections of the CRF55_01B subtype to reduce the transmission of drug-resistant strains. However, improving the treatment effect of HIV infections is beneficial for reducing the second-generation transmission of HIV.

Detection of HIV-1 Transmission Clusters from Dried Blood Spots within a Universal Test-and-Treat Trial in East Africa

The Sustainable East Africa Research in Community Health (SEARCH) trial was a universal test-and-treat (UTT) trial in rural Uganda and Kenya, aiming to lower regional HIV-1 incidence. Here, we quantify breakthrough HIV-1 transmissions occurring during the trial from population-based, dried blood spot samples. Between 2013 and 2017, we obtained 549 gag and 488 pol HIV-1 consensus sequences from 745 participants: 469 participants infected prior to trial commencement and 276 SEARCH-incident infections. Putative transmission clusters, with a 1.5% pairwise genetic distance threshold, were inferred from maximum likelihood phylogenies; clusters arising after the start of SEARCH were identified with Bayesian time-calibrated phylogenies. Our phylodynamic approach identified nine clusters arising after the SEARCH start date: eight pairs and one triplet, representing mostly opposite-gender linked (6/9), within-community transmissions (7/9). Two clusters contained individuals with non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance, both linked to intervention communities. The identification of SEARCH-incident, within-community transmissions reveals the role of unsuppressed individuals in sustaining the epidemic in both arms of a UTT trial setting. The presence of transmitted NNRTI resistance, implying treatment failure to the efavirenz-based antiretroviral therapy (ART) used during SEARCH, highlights the need to improve delivery and adherence to up-to-date ART recommendations, to halt HIV-1 transmission.

Enhanced Transmissibility and Decreased Virulence of HIV-1 CRF07_BC May Explain Its Rapid Expansion in China

HIV-1 CRF07_BC is one of the most common circulating recombinant forms (CRFs) in China and is becoming increasingly prevalent especially in HIV-infected men who have sex with men (MSM). The reason why this strain expanded so quickly in China remains to be defined. We previously observed that individuals infected with HIV-1 CRF07_BC showed slower disease progression than those infected with HIV-1 subtype B or CRF01_AE. CRF07_BC viruses carry two unique mutations in the p6Gag protein: insertion of PTAPPE sequences downstream of the original Tsg101 binding domain, and deletion of a seven-amino-acid sequence (30PIDKELY36) that partially overlaps with the Alix binding domain. In this study, we confirmed the enhanced transmission capability of CRF07_BC over HIV-1 subtype B or CRF01_AE by constructing HIV-1 transmission networks to quantitatively evaluate the growth rate of transmission clusters of different HIV-1 genotypes. We further determined lower virus infectivity and slower replication of CRF07_BC with aforementioned PTAPPE insertion (insPTAP) and/or PIDKELY deletion (Δ7) in the p6Gag protein, which in turn may increase the pool of people infected with CRF07_BC and the risk of HIV-1 transmission. These new features of CRF07_BC may explain its quick spread and will help adjust prevention strategy of HIV-1 epidemic. IMPORTANCE HIV-1 CRF07_BC is one of the most common circulating recombinant forms (CRFs) in China. The question is why and how CRF07_BC expanded so rapidly remains unknown. To address the question, we explored the transmission capability of CRF07_BC by constructing HIV-1 transmission networks to quantitatively evaluate the growth rate of transmission clusters of different HIV-1 genotypes. We further characterized the role of two unique mutations in CRF07_BC, PTAPPE insertion (insPTAP) and/or PIDKELY deletion (Δ7) in the p6Gag in virus replication. Our results help define the molecular mechanism regarding the association between the unique mutations and the slower disease progression of CRF07_BC as well as the quick spread of CRF07_BC in China.

Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012-2016

We aimed to elucidate the characteristics of HIV molecular epidemiology and identify transmission hubs in eastern China using genetic transmission network and lineage analyses. HIV-TRACE was used to infer putative relationships. Across the range of epidemiologically-plausible genetic distance (GD) thresholds (0.1-2.0%), a sensitivity analysis was performed to determine the optimal threshold, generating the maximum number of transmission clusters and providing reliable resolution without merging different small clusters into a single large cluster. Characteristics of genetically linked individuals were analyzed using logistic regression. Assortativity (shared characteristics) analysis was performed to infer shared attributes between putative partners. 1,993 persons living with HIV-1 were enrolled. The determined GD thresholds within subtypes CRF07_BC, CRF01_AE, and B were 0.5%, 1.2%, and 1.7%, respectively, and 826 of 1,993 (41.4%) sequences were linked with at least one other sequence, forming 188 transmission clusters of 2-80 sequences. Clustering rates for the main subtypes CRF01_AE, CRF07_BC, and B were 50.9% (523/1027), 34.2% (256/749), and 32.1% (25/78), respectively. Median cluster sizes of these subtypes were 2 (2-52, n = 523), 2 (2-80, n = 256), and 3 (2-6, n = 25), respectively. Subtypes in individuals diagnosed and residing in Hangzhou city (OR = 1.423, 95% CI: 1.168-1.734) and men who have sex with men (MSM) were more likely to cluster. Assortativity analysis revealed individuals were more likely to be genetically linked to individuals from the same age group (AIage = 0.090, P<0.001) and the same area of residency in Zhejiang (AIcity = 0.078, P<0.001). Additionally, students living with HIV were more likely to be linked with students than show a random distribution (AI student = 0.740, P<0.01). These results highlight the importance of Hangzhou City in the regional epidemic and show that MSM comprise the population rapidly transmitting HIV in Zhejiang Province. We also provide a molecular epidemiology framework for improving our understanding of HIV transmission dynamics in eastern China.

Community and Provider Perspectives on Molecular HIV Surveillance and Cluster Detection and Response for HIV Prevention: Qualitative Findings From King County, Washington

ABSTRACT

Responding quickly to HIV outbreaks is one of four pillars of the U.S. Ending the HIV Epidemic (EHE) initiative. Inclusion of cluster detection and response in the fourth pillar of EHE has led to public discussion concerning bioethical implications of cluster detection and response and molecular HIV surveillance (MHS) among public health authorities, researchers, and community members. This study reports on findings from a qualitative analysis of interviews with community members and providers regarding their knowledge and perspectives of MHS. We identified five key themes: (a) context matters, (b) making sense of MHS, (c) messaging, equity, and resource prioritization, (d) operationalizing confidentiality, and (e) stigma, vulnerability, and power. Inclusion of community perspectives in generating innovative approaches that address bioethical concerns related to the use of MHS data is integral to ensure that widely accessible information about the use of these data is available to a diversity of community members and providers.

Using molecular epidemiology to trace the history of the injection-related HIV epidemic in New York City, 1985-2019

OBJECTIVE

Unintentional drug poisoning and overdose deaths in New York City (NYC) increased 175% between 2010 and 2017, partly due to the transition from noninjectable opioids to heroin injection. This transition has led to concern of a resurgent HIV epidemic among persons who inject drugs (PWID) in NYC. Thus, we sought to characterize HIV transmission dynamics in PWID.

DESIGN

Genetic network analysis of HIV-1 public health surveillance data.

METHODS

We analyzed HIV diagnoses reported to public health surveillance to determine the trajectory of the HIV epidemic among PWID in NYC, from 1985 through 2019. Genetic distance-based clustering was performed using HIV-TRACE to reconstruct transmission patterns among PWID.

RESULTS

The majority of the genetic links to PWID diagnosed in the 1980s and 1990s are to other PWID. However, since 2011, there has been a continued decline in new diagnoses among PWID, and genetic links between PWID have become increasingly rare, although links to noninjecting MSM and other people reporting sexual transmission risk have become increasingly common. However, we also find evidence suggestive of a resurgence of genetic links among PWID in 2018-2019. PWID who reported male-male sexual contact were not preferentially genetically linked to PWID over the surveillance period, emphasizing their distinct risk profile from other PWID.

CONCLUSION

These trends suggest a transition from parenteral to sexual transmission among PWID in NYC, suggesting that harm reduction, syringe exchange programs, and legalization of over-the-counter syringe sales in pharmacies have mitigated HIV risk by facilitating well tolerated injection among new PWID.

Do partner services linked to molecular clusters yield people with viremia or new HIV?

OBJECTIVES

We examined whether molecular cluster membership was associated with public health identification of HIV transmission potential among named partners in Chicago.

DESIGN

Historical cohort study.

METHODS

We matched and analyzed HIV surveillance and partner services data from HIV diagnoses (2012-2016) prior to implementation of cluster detection and response interventions. We constructed molecular clusters using HIV-TRACE at a pairwise genetic distance threshold of 0.5% and identified clusters exhibiting recent and rapid growth according to the Centers for Disease Control and Prevention definition (three new cases diagnosed in past year). Factors associated with identification of partners with HIV transmission potential were examined using multivariable Poisson regression.

RESULTS

There were 5208 newly diagnosed index clients over this time period. Average age of index clients in clusters was 28; 47% were Black, 29% Latinx/Hispanic, 6% female and 89% MSM. Of the 537 named partners, 191 (35.6%) were linked to index cases in a cluster and of those 16% were either new diagnoses or viremic. There was no statistically significant difference in the probability of identifying partners with HIV transmission potential among index clients in a rapidly growing cluster versus those not in a cluster [adjusted relative risk 1.82, (0.81-4.06)].

CONCLUSION

Partner services that were initiated from index clients in a molecular cluster yielded similar new HIV case finding or identification of those with viremia as did interviews with index clients not in clusters. It remains unclear whether these findings are due to temporal disconnects between diagnoses and cluster identification, unobserved cluster members, or challenges with partner services implementation.

Beyond HIV outbreaks: protocol, rationale and implementation of a prospective study quantifying the benefit of incorporating viral sequence clustering analysis into routine public health interventions

INTRODUCTION

HIV continues to have great impact on millions of lives. Novel methods are needed to disrupt HIV transmission networks. In the USA, public health departments routinely conduct contact tracing and partner services and interview newly HIV-diagnosed index cases to obtain information on social networks and guide prevention interventions. Sequence clustering methods able to infer HIV networks have been used to investigate and halt outbreaks. Incorporation of such methods into routine, not only outbreak-driven, contact tracing and partner services holds promise for further disruption of HIV transmissions.

METHODS AND ANALYSIS

Building on a strong academic-public health collaboration in Rhode Island, we designed and have implemented a state-wide prospective study to evaluate an intervention that incorporates real-time HIV molecular clustering information with routine contact tracing and partner services. We present the rationale and study design of our approach to integrate sequence clustering methods into routine public health interventions as well as related important ethical considerations. This prospective study addresses key questions about the benefit of incorporating a clustering analysis triggered intervention into the routine workflow of public health departments, going beyond outbreak-only circumstances. By developing an intervention triggered by, and incorporating information from, viral sequence clustering analysis, and evaluating it with a novel design that avoids randomisation while allowing for methods comparison, we are confident that this study will inform how viral sequence clustering analysis can be routinely integrated into public health to support the ending of the HIV pandemic in the USA and beyond.

ETHICS AND DISSEMINATION

The study was approved by both the Lifespan and Rhode Island Department of Health Human Subjects Research Institutional Review Boards and study results will be published in peer-reviewed journals.

An Evaluation of Phylogenetic Workflows in Viral Molecular Epidemiology

The use of viral sequence data to inform public health intervention has become increasingly common in the realm of epidemiology. Such methods typically utilize multiple sequence alignments and phylogenies estimated from the sequence data. Like all estimation techniques, they are error prone, yet the impacts of such imperfections on downstream epidemiological inferences are poorly understood. To address this, we executed multiple commonly used viral phylogenetic analysis workflows on simulated viral sequence data, modeling Human Immunodeficiency Virus (HIV), Hepatitis C Virus (HCV), and Ebolavirus, and we computed multiple methods of accuracy, motivated by transmission-clustering techniques. For multiple sequence alignment, MAFFT consistently outperformed MUSCLE and Clustal Omega, in both accuracy and runtime. For phylogenetic inference, FastTree 2, IQ-TREE, RAxML-NG, and PhyML had similar topological accuracies, but branch lengths and pairwise distances were consistently most accurate in phylogenies inferred by RAxML-NG. However, FastTree 2 was the fastest, by orders of magnitude, and when the other tools were used to optimize branch lengths along a fixed FastTree 2 topology, the resulting phylogenies had accuracies that were indistinguishable from their original counterparts, but with a fraction of the runtime.

Unlocking capacities of genomics for the COVID-19 response and future pandemics

During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated development of testing methods, and allowed timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific, and organizational challenges. Here, we discuss the application of genomic and computational methods for the efficient data driven COVID-19 response, advantages of democratization of viral sequencing around the world, and challenges associated with viral genome data collection and processing.

Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial - BCPP/ Ya Tsie trial

Background: Mathematical models predict that community-wide access to HIV testing-and-treatment can rapidly and substantially reduce new HIV infections. Yet several large universal test-and-treat HIV prevention trials in high-prevalence epidemics demonstrated variable reduction in population-level incidence.

Methods: To elucidate patterns of HIV spread in universal test-and-treat trials we quantified the contribution of geographic-location, gender, age and randomized-HIV-intervention to HIV transmissions in the 30-community Ya Tsie trial in Botswana. We sequenced HIV viral whole genomes from 5,114 trial participants among the 30 trial communities.

Results: Deep-sequence phylogenetic analysis revealed that most inferred HIV transmissions within the trial occurred within the same or between neighboring communities, and between similarly-aged partners. Transmissions into intervention communities from control communities were more common than the reverse post-baseline (30% [12.2 - 56.7] versus 3% [0.1 - 27.3]) than at baseline (7% [1.5 - 25.3] versus 5% [0.9 - 22.9]) compatible with a benefit from treatment-as-prevention.

Conclusion: Our findings suggest that population mobility patterns are fundamental to HIV transmission dynamics and to the impact of HIV control strategies.

Funding: This study was supported by the National Institute of General Medical Sciences (U54GM088558); the Fogarty International Center (FIC) of the U.S. National Institutes of Health (D43 TW009610); and the President's Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention (CDC) (Cooperative agreements U01 GH000447 and U2G GH001911).

Spatiotemporal Patterns of CRF07_BC in China: A Population-Based Study of the HIV Strain With the Highest Infection Rates

The prevalence of CRF07_BC is 39.7% and has become the most infectious HIV strain in China. To study the transmission and diffusion trajectory of CRF07_BC in China and to prevent further expansion of its transmission. A total of 16,635 sequences of the CRF07_BC pol gene were collected from 1997-2020. We characterized the gene subtypes according to a phylogenetic tree analysis. A 0.50% molecular network was constructed to analyze the transmission relationship among different provinces for CRF07_BC and its two epidemic clusters. Spatial and temporal propagation characteristics were analyzed according to phylogeographic analysis. Finally, we evaluated the differences in transmission of CRF07_BC-O, and CRF07_BC-N. Our dataset included 8,816 sequences of CRF07_BC-N and 7,819 sequences of CRF07_BC-O. There were 7,132 CRF07_BC sequences in the molecular network, and the rate of clustered was 42.9%. Compared to CRF07_BC-O, CRF07_BC-N showed significantly (P&lt;0.001) higher transmission-specific rates. CRF07_BC originated among injecting drug users (IDUs), and spread to men who have sex with men (MSMs) and heterosexual individuals (HETs), while MSMs also transmitted directly to HETs. CRF07_BC-O and CRF07_BC-N were prevalent in Xinjiang and Sichuan, respectively, before spreading interprovincially. In modern China, CRF07_BC-N occurs in five of the major economic zones. The CRF07_BC strain, which has contributed to the highest number of HIV infections in China, is divided into two epidemic clusters. Compared with CRF07_BC-O, risk of transmission is much greater in CRF07_BC-N, which is predominantly prevalent in economically developed provinces, and both MSMs and IDUs have transmitted this epidemic cluster to HETs. High-resolution, large-scale monitoring is a useful tool in assessing the trend and spread of the HIV epidemic. The rapidly developing economy of China requires an equally rapid response to the prevention and control of infectious diseases.

Molecular Network Analysis Reveals Transmission of HIV-1 Drug-Resistant Strains Among Newly Diagnosed HIV-1 Infections in a Moderately HIV Endemic City in China

Since the implementation of the "treat all" policy in China in 2016, there have been few data on the prevalence of transmitted drug resistance (TDR) in China. In this study, we describe TDR in patients newly diagnosed with human immunodeficiency virus (HIV) infection between 2016 and 2019 in Shenyang city, China. Demographic information and plasma samples from all newly reported HIV-infected individuals in Shenyang from 2016 to 2019 were collected. The HIV pol gene was amplified and sequenced for subtyping and TDR. The spread of TDR was analyzed by inferring an HIV molecular network based on pairwise genetic distance. In total, 2,882 sequences including CRF01_AE (2019/2,882, 70.0%), CRF07_BC (526/2,882, 18.3%), subtype B (132/2,882, 4.6%), and other subtypes (205/2,882, 7.1%) were obtained. The overall prevalence of TDR was 9.1% [95% confidence interval (CI): 8.1-10.2%]; the prevalence of TDR in each subtype in descending order was CRF07_BC [14.6% (95% CI: 11.7-18.0%)], subtype B [9.1% (95% CI: 4.8-15.3%)], CRF01_AE [7.9% (95% CI: 6.7-9.1%)], and other sequences [7.3% (95% CI: 4.2-11.8%)]. TDR mutations detected in more than 10 cases were Q58E (n = 51), M46ILV (n = 46), K103N (n = 26), E138AGKQ (n = 25), K103R/V179D (n = 20), and A98G (n = 12). Molecular network analysis revealed three CRF07_BC clusters with TDR [two with Q58E (29/29) and one with K103N (10/19)]; and five CRF01_AE clusters with TDR [two with M46L (6/6), one with A98G (4/4), one with E138A (3/3), and one with K103R/V179D (3/3)]. In the TDR clusters, 96.4% (53/55) of individuals were men who have sex with men (MSM). These results indicate that TDR is moderately prevalent in Shenyang (5-15%) and that TDR strains are mainly transmitted among MSM, providing precise targets for interventions in China.

Forecasting HIV-1 Genetic Cluster Growth in Illinois,United States

BACKGROUND

HIV intervention activities directed toward both those most likely to transmit and their HIV-negative partners have the potential to substantially disrupt HIV transmission. Using HIV sequence data to construct molecular transmission clusters can reveal individuals whose viruses are connected. The utility of various cluster prioritization schemes measuring cluster growth have been demonstrated using surveillance data in New York City and across the United States, by the Centers for Disease Control and Prevention (CDC).

METHODS

We examined clustering and cluster growth prioritization schemes using Illinois HIV sequence data that include cases from Chicago, a large urban center with high HIV prevalence, to compare their ability to predict future cluster growth.

RESULTS

We found that past cluster growth was a far better predictor of future cluster growth than cluster membership alone but found no substantive difference between the schemes used by CDC and the relative cluster growth scheme previously used in New York City (NYC). Focusing on individuals selected simultaneously by both the CDC and the NYC schemes did not provide additional improvements.

CONCLUSION

Growth-based prioritization schemes can easily be automated in HIV surveillance tools and can be used by health departments to identify and respond to clusters where HIV transmission may be actively occurring.