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

Identifying the unknown: Application of molecular epidemiology tools to identify clustering and HIV transmission routes in Poland

BACKGROUND

Understanding the dynamics of HIV-1 transmission is essential for developing effective screening and intervention strategies. Viral genetic sequences provide valuable information that can be used to infer the history and patterns of viral transmission.

PURPOSE

Our study explores the structure and dynamics of HIV transmissions in Poland from 1999 to 2022 to elucidate key patterns related with national epidemics.

METHODS

To understand the temporal dynamics of transmission routes we examined HIV pol sequence data from 5705 Polish PWH. The HIV-TRAnsmission Cluster Engine (HIV-TRACE) was utilized to identify potential links between different risk groups and putative links to individuals with unreported transmission risk.

RESULTS

Our analyses generated 503 clusters, containing 3942 individuals, and identified 13,917 putative links. Approximately 69.1 % of the sequences formed clusters. In the dataset 32.2 % of individuals were reported MSM transmission route, 7.9 % by heterosexual, and 5.6 % by PWID transmissions. The transmission route was unknown for 54.2 % of patients. Putative transmissions from MSM to all other groups revealed that 45.1 % of links lead to people with unregistered transmission mode. For heterosexual patients, 40.2 % of connections were directed to patients lacking information on infection routes and 30.5 % to MSM individuals. Our analysis unveiled that 45.1 % of cases with unreported transmission routes may be identified as MSM, while 3.5 % might be potential non-disclosed MSM.

CONCLUSIONS

Genetic linkages can provide valuable insights into the transmission dynamics among individuals, even in cases where transmission risk information is missing or unreported. The observed association between MSM and unreported cases highlights the potential of molecular epidemiology to complete missing patient data.

Threshold sensitivity analysis for HIV-1 transmission cluster detection using different genomic regions and subtypes

HIV-1 cluster analysis has been widely used in characterizing HIV-1 transmission and some countries have implemented such molecular epidemiology as part of their prevention strategy. However, HIV-1 sequences derive from varying genome regions, which affects phylogenetic clustering outputs. Here, we apply different tools to run a sensitivity analysis for assessing which threshold give the most cohesive clustering outputs for different data sources. We used a dataset of 174 full-length sequences of subtype B from the Swiss HIV Cohort Study and publicly available subtype C from South Africa. Each dataset was divided into sub-genomic sub-datasets covering gag, pol, and env. pol was further subdivided into regions commonly used in HIV-1 genotyping laboratories (pr-rt, rt-int, and pr-rt-int). Cluster analyses for each sub-genomic region was performed specifying varying distance thresholds of 0.5 %-4.5 % and tree branch support of 70 %, 90 % and 99 % in ClusterPicker. Tree topologies and clustering outputs were compared against each other to assess cluster similarity. Pylogenies using pol, pr-rt-int, or rt-int had more robust tree topologies compared to gag and env. Cluster composition changed with increasing genetic distance threshold but was not affected by branch support. Cluster identity was most similar around genetic distances of 2.5 (±0.5)% for all sub-genomic regions and for both subtype B and C. Our study demonstrated the value of performing a sensitivity analysis before setting a genetic distance threshold for clustering output and that the pol region is appropriate for clustering outputs and can be used for near real-time HIV-1 cluster detection.

Phylogeographic and genetic network assessment of COVID-19 mitigation protocols on SARS-CoV-2 transmission in university campus residences

BACKGROUND

Congregate living provides an ideal setting for SARS-CoV-2 transmission in which many outbreaks and superspreading events occurred. To avoid large outbreaks, universities turned to remote operations during the initial COVID-19 pandemic waves in 2020 and 2021. In late-2021, the University of California San Diego (UC San Diego) facilitated the return of students to campus with comprehensive testing, vaccination, masking, wastewater surveillance, and isolation policies.

METHODS

We performed molecular epidemiological and phylogeographic analysis of 4418 SARS-CoV-2 genomes sampled from UC San Diego students during the Omicron waves between December 2021 and September 2022, representing 58% of students with confirmed SARS-CoV-2 infection. We overlaid these analyses across on-campus residential information to assess the spread and persistence of SARS-CoV-2 within university residences.

FINDINGS

Within campus residences, SARS-CoV-2 transmission was frequent among students residing in the same room or suite. However, a quarter of pairs of suitemates with concurrent infections had distantly related viruses, suggesting separate sources of infection during periods of high incidence in the surrounding community. Students with concurrent infections residing in the same building were not at substantial increased probability of being members of the same transmission cluster. Genetic network and phylogeographic inference indicated that only between 3.1 and 12.4% of infections among students could be associated with transmission within buildings outside of individual suites. The only super-spreading event we detected was related to a large event outside campus residences.

INTERPRETATION

We found little evidence for sustained SARS-CoV-2 transmission within individual buildings, aside from students who resided in the same suite. Even in the face of heightened community transmission during the 2021-2022 Omicron waves, congregate living did not result in a heightened risk for SARS-CoV-2 transmission in the context of the multi-pronged mitigation strategy.

FUNDING

SEARCH Alliance: Centers for Disease Control and Prevention (CDC) BAA (75D301-22-R-72097) and the Google Cloud Platform Research Credits Program. J.O.W.: NIH-NIAID (R01 AI135992). T.I.V.: Branco Weiss Fellowship and Newkirk Fellowship. L.L.: University of California San Diego.

Divergent transmission dynamics and drug resistance evolution of HIV-1 CRF01_AE and CRF07_BC in Tianjin, China (2013-2022)

BACKGROUND

Tianjin, a major hub in northern China, faces rising HIV-1 infections dominated by CRF01_AE and CRF07_BC. This study elucidated their divergent transmission patterns and drug resistance dynamics to guide targeted interventions.

METHODS

This study included samples identified as CRF01_AE and CRF07_BC subtypes through various methods between 2013 and 2022. BEAST software was used to examine the spatiotemporal transmission patterns of these subtypes in Tianjin. By integrating HIV-TRACE, we constructed high-risk transmission clusters and identified drug resistance mutations (DRMs) based on the Stanford HIV Drug Resistance Database. Finally, the birth-death skyline serial (BDSKY) model was employed to dynamically assess the effective reproductive number (Re) of both subtypes to predict future transmission dynamics.

RESULTS

CRF01_AE might be introduced in 1988 from Henan and Zhejiang, forming multiple small clusters (< 10 nodes) and spreading through both heterosexual and men who have sex with men (MSM) in Tianjin, while CRF07_BC from Chongqing and Guizhou, et al. in 2004, experiencing explosive local transmission and forming a large cluster of 170 nodes primarily among MSM under 30 years old (P < 0.05). Phylogenetic analysis indicated that CRF01_AE has a significantly higher evolutionary rate (2.08 × 10⁻3 vs. 1.48 × 10⁻3 substitutions/site/year, P < 0.05), while CRF07_BC demonstrates a greater cluster formation capacity (56.6% vs. 37.1%, P < 0.05). CRF01_AE showed a higher mutation occurrence rate (5.18% vs. 2.49%, P < 0.05), particularly with non-nucleoside reverse transcriptase inhibitor (NNRTI) associated mutations (e.g., K101E). Although CRF07_BC had a lower resistance burden, the emergence of K103E mutations suggests a need for vigilance regarding potential decreases in sensitivity to newer NNRTIs. BDSKY modeling revealed that the Re for CRF01_AE dropped below 1 after 2016, whereas CRF07_BC's Re remains above 1, indicating that the risk of transmission still exists.

CONCLUSION

Subtype-specific strategies are critical: intensified resistance monitoring for CRF01_AE and cluster-focused interventions for CRF07_BC, particularly among young MSM.

HIV molecular network in Mexico City (2021-2022): Understanding transmission dynamics through the role of newly diagnosed cases

OBJECTIVE

We aimed to infer and describe Mexico City's HIV genetic transmission network from 2021 through 2022 by characterizing its members based on time since HIV acquisition, as well as sociodemographic, clinical, and behavioural characteristics. Additionally, we assessed clustering potential according to time since HIV acquisition.

METHODS

Individuals with a recent HIV diagnosis at the largest HIV clinic in Mexico City were invited to participate, completing self-administered questionnaires on sociodemographic, clinical, and behavioural characteristics. Blood samples were collected for analysis of the HIV pol gene using next-generation sequencing. The stage of infection at diagnosis was determined using an algorithm that includes antibody avidity tests. Genetic transmission network analysis used the Seguro HIV-TRACE tool.

RESULTS

Of 6703 participants, 561 (8.4%) were identified as people newly living with HIV (PNLH). Transmission network analysis identified 896 clusters; 30.2% had at least one PNLH. Among all individuals, 43.5% formed clusters, with 11.8% being PNLH. PNLH added to a cluster showed higher odds for higher education, engaging in commercial sex, use of dating apps, annual HIV screening, and engaging in high-risk sexual practices (p < 0.05). Clusters with PNLH exhibited greater growth rates than those without PNLH (p < 0.05).

CONCLUSIONS

The presence of PNLH in clusters was associated with a higher growth rate. Tailored prevention strategies are crucial, including using dating apps for risk communication, promoting PrEP use, and safe sexual practices in sex venues, and enhancing harm reduction related to drug use. PNLH could be key candidates for interventions aimed at breaking transmission chains, including contact tracing.

Transmission dynamics of the 2022 mpox epidemic in New York City

The 2022 global mpox epidemic was caused by transmission of MPXV clade IIb, lineage B.1 through sexual contact networks, with New York City (NYC) experiencing the first and largest outbreak in the United States. By performing phylogeographic analysis of MPXV genomes sampled from 757 individuals in NYC between April 2022 and April 2023, and 3,287 MPXV genomes sampled around the world, we identify over 200 introductions of MPXV into NYC with at least 84 leading to onward transmission. These infections primarily occurred among men who have sex with men, transgender women and nonbinary individuals. Through a comparative analysis with HIV in NYC, we find that both MPXV and HIV genomic cluster sizes are best fit by scale-free distributions, and that people in MPXV clusters are more likely to have previously received an HIV diagnosis and be a member of a recently growing HIV transmission cluster. We model MPXV transmission through sexual contact networks and show that highly connected individuals would be disproportionately infected at the start of an epidemic, which would likely result in the exhaustion of the most densely connected parts of the network, and, therefore, explain the rapid expansion and decline of the NYC outbreak. By coupling the genomic epidemiology of MPXV and HIV with epidemic modeling, we demonstrate that the transmission dynamics of MPXV in NYC can be understood by general principles of sexually transmitted pathogens.

Nationwide Implementation of HIV Molecular Cluster Detection by Centers for Disease Control and Prevention and State and Local Health Departments, United States

Detecting and responding to clusters of rapid HIV transmission is a core HIV prevention strategy in the United States, guiding public health interventions and identifying gaps in prevention and care services. In 2016, the Centers for Disease Control and Prevention (CDC) initiated molecular cluster detection using data from 27 jurisdictions. During 2016-2023, CDC expanded sequence reporting nationwide and deployed Secure HIV-TRACE, an application supporting health department (HD) molecular cluster detection. CDC conducts molecular cluster detection quarterly; state and local HDs analyze local data monthly. HDs began routinely reporting clusters to CDC by using cluster report forms in 2020. During 2018-2023, CDC identified 404 molecular clusters of rapid HIV transmission; 325 (80%) involved multiple jurisdictions. During 2020-2023, HDs reported 298 molecular clusters to CDC; 249 were first detected by HDs. Expanding molecular cluster detection has provided a foundation for improving service delivery to networks experiencing rapid HIV transmission.

Epidemiological and spatial analysis of newly diagnosed HIV-1/AIDS patients before antiretroviral therapy in Ningxia from 2020 to 2021

The high mutability of human immunodeficiency virus type 1 (HIV-1) and the widespread use of antiretroviral drugs have rendered genetic diversity and pre-treatment drug resistance (PDR) significant obstacles to the success of antiretroviral therapy (ART). However, the research on the epidemiological and spatial distribution characteristics of PDR in Ningxia is still insufficient. A cross-sectional study utilized pre-treatment blood samples collected between 2020 and 2021 from the biorepository in May 2024. Partial pol gene sequences were obtained through plasma collection and RNA extraction. Drug resistance analysis was performed using the Stanford University HIVdb algorithm. Molecular network were constructed using Cytoscape 3.10.0. Spatial analysis and visualization were further conducted using ArcGIS10.8.1. 95 sequences were obtained, among which 7 HIV-1 genotypes were detected and CRF07_BC (67.37%, 64/95) was the predominant one. Drug resistance mutations (DRMs) were detected in 13.68%(13/95) of the sequences. The risk of PDR occurrence was higher among individuals with CRF07_BC strain types. The 24 sequences of CRF07_BC, CRF01_AE, and URF subtypes grouped into nine transmission clusters in the molecular network, with CRF07_BC showing the highest integration and clustering rates. HIV-1 infections resistant to PDR were observed in all five cities in NHAR, accompanied by cross-city transmission. Additionally, seven imported sequences were detected, comprising CRF07_BC, CRF01_AE, and C subtypes, along with three sequences of CRF55_01B with high similarity to nonlocal sequences. From 2020 to 2021, the HIV-1 diversity increased significantly in NHAR, with the prevalence of PDR reaching moderate levels and evidence of resistance transmission. The districts and counties under the jurisdiction of Yinchuan City emerged as hotspots for both pre-treatment HIV/AIDS patients and the distribution of resistant strains. It is imperative to enhance PDR testing and implement targeted interventions in key areas to minimize the emergence and dissemination of resistant virus variants.

Geographic origins, transmission hotspots, and drug resistance mutations of HIV-1 CRF08_BC in Zhejiang Province, China

PURPOSE

To understand the geographic origins, transmission hotspots, and drug resistance mutations (DRMs) of HIV-1 CRF08_BC in Zhejiang Province, China.

METHODS

This study analyzed HIV-1 CRF08_BC pol sequences collected between 2020 and 2023. Bayesian inference was employed to investigate temporal epidemic trends, while HIV-TRACE and MCODE were used to identify transmission clusters (TCs), key hotspots and super-spreaders. DRMs associated with CRF08_BC were also characterized. Additionally, demographic data were integrated with these findings, allowing for a description of the transmission dynamics.

RESULTS

This study revealed that CRF08_BC strains in Zhejiang likely originated from Guangxi, with significant transmission among individuals aged 50 and older, particularly those with low educational levels. Molecular transmission analysis showed that 58.9% of CRF08_BC sequences were in TCs, with geographic concentrations in Taizhou (TZ) and Lishui (LS). 14 large clusters maintained effective reproductive numbers (Re) above 1, representing considerable epidemic growth. Hangzhou (HZ) emerged as a key transmission hub, with 10 TCs showing active transmission. LS established strong epidemiological links with HZ, Ningbo (NB), Taizhou (TZ), and Wenzhou (WZ), creating a pattern of viral spread radiating from LS to surrounding areas. DRMs were identified in 76 cases (6.0%), with NNRTI and NRTI mutations exhibiting distinct geographic clustering.

CONCLUSIONS

The CRF08_BC strains in Zhejiang likely originated from Guangxi and are mainly found in individuals aged 50 and older with low education. The current epidemic hotspots are in TZ and LS, where NNRTI and NRTI mutations are clustered, significantly impacting treatment efficacy.

Molecular Network Characteristics and Drug Resistance Analysis Among Newly Diagnosed Persons Living with HIV-1 in Hefei, China (2017-2022)

Molecular transmission networks are being used with increasing frequency to study HIV-1 transmission patterns and to develop precise intervention strategies for high-risk populations. Here, we analyzed the molecular transmission networks of newly diagnosed patients with HIV-1 in Hefei City, Anhui Province, from 2017 to 2022. Of the 1,413 newly diagnosed HIV-1 Pol sequences, the major genotypes in Hefei were CRF07_BC (600, 42.5%) and CRF01_AE (530, 37.5%). Molecular transmission network analysis identified 146 clusters and 9 large propagation clusters, including four CRF01_AE clusters, four CRF07_BC clusters, and one CRF55_01B cluster. This study highlights the pattern of local HIV-1 transmission in Hefei City, with notable rapid transmission of CRF55_01B. It suggests that the implementation of focused strategies for the identified key transmission clusters is essential for effective control of the HIV-1 epidemic.

Phylodynamics for Human Immunodeficiency Virus Prevention: A Miami-Dade County Case Study

BACKGROUND

To date, human immunodeficiency virus (HIV) molecular epidemiology has been primarily used to identify clusters of related infections (cluster detection and response) and then address interventions to these clusters. Community groups have raised concern regarding cluster detection and response related to privacy and ethical concerns. Here we demonstrate how an alternative approach to HIV molecular epidemiology can provide public health benefit.

METHODS

A limited data set for Miami-Dade County provided by the Florida Department of Health was curated and annotated by neighborhood health district (NBHD) and genetic linkage (using a genetic distance threshold of ≤0.5%) and phylodynamic analyses were performed. Phylodynamic analyses were used to infer viral transmissions into Miami-Dade County and between NBHDs within the county.

RESULTS

A total of 7274 HIV sequences from unique persons collected between 1 January 2015 and 31 December 2021 were analyzed, including 50% of the 7894 new diagnoses during this period. The proportion of sequences in local clusters increased over time. Higher ratios of local introductions, compared to viral egress (ie, source of local clusters in other NBHDs) were observed in 3 NBHDs in North Miami (range, 1.9-2.5), suggesting earlier diagnosis, but high numbers of susceptible persons not receiving preexposure prophylaxis. South Dade/Homestead had a low ratio (0.3) of local introductions compared with egress, suggesting later diagnosis and less durable suppression.

CONCLUSIONS

Phylodynamic and genetic linkage analyses can highlight populations and geographic regions that might benefit more from particular types of HIV prevention interventions. These findings will need to be explored by evaluating the impact of scaling up interventions informed by these analyses.

Bayesian mixture models for phylogenetic source attribution from consensus sequences and time since infection estimates

In stopping the spread of infectious diseases, pathogen genomic data can be used to reconstruct transmission events and characterize population-level sources of infection. Most approaches for identifying transmission pairs do not account for the time passing since the divergence of pathogen variants in individuals, which is problematic in viruses with high within-host evolutionary rates. This prompted us to consider possible transmission pairs in terms of phylogenetic data and additional estimates of time since infection derived from clinical biomarkers. We develop Bayesian mixture models with an evolutionary clock as a signal component and additional mixed effects or covariate random functions describing the mixing weights to classify potential pairs into likely and unlikely transmission pairs. We demonstrate that although sources cannot be identified at the individual level with certainty, even with the additional data on time elapsed, inferences into the population-level sources of transmission are possible, and more accurate than using only phylogenetic data without time since infection estimates. We apply the proposed approach to estimate age-specific sources of HIV infection in Amsterdam tranamission networks among men who have sex with men between 2010 and 2021. This study demonstrates that infection time estimates provide informative data to characterize transmission sources, and shows how phylogenetic source attribution can then be done with multi-dimensional mixture models.

Sexual Networks and Behavioral Characteristics of HIV-Positive Male Military Members, Female Sex Workers, and Male Civilians

Military members and female sex workers (FSWs) may be more likely to acquire or transmit HIV. Mapping HIV transmission across these high-risk populations and identifying behaviors associated with sexual network clustering are needed for effective HIV prevention approaches. A cross-sectional study recruited participants newly diagnosed with HIV among militaries, civilians, and FSWs in Zambia, Senegal, and Democratic Republic of the Congo (DRC). Participants were interviewed on behaviors and provided blood samples for HIV-1 partial pol sequencing. Genetic-distance based network analyses inferred putative relationships between HIV-1 partial pol sequences. Bivariate logistic regression models identified variables associated with clustering in a sexual network. 908 participants were included (n = 313 FSWs, n = 297 military, n = 298 civilians). 311 blood samples were sequenced and had survey data, of which 93 (29.9%) were genetically linked, forming 36 transmission clusters. All but one cluster were comprised of participants from the same country, including one large cluster (n = 12; 9 FSWs and 3 civilians) from DRC. A large mixed-country cluster (n = 9) including 7 men (4 civilians, 3 military) and 2 FSWs was observed. The odds of clustering in a sexual network were elevated for DRC participants, FSWs, and those cohabitating with a sexual partner. Findings underscore the importance of identifying linkages in high-risk populations to develop tailored HIV prevention strategies. Linkages across risk groups and countries illustrate the potential role of mobile populations in HIV transmission and acquisition. Larger studies including HIV recency testing may better elucidate biological and behavioral interactions between military, civilians, and FSWs.

Characterization of People Living with HIV Who Inject Drugs in Mexico City: Importance for Transmission and Detection

People who inject drugs (PWID) face a heightened risk of acquiring/transmitting HIV, enhanced by stigma and limited health care access. In Mexico, studies on PWID have focused on the north of the country. This study aimed to delineate characteristics of PWID living with HIV in Mexico City, identify profiles based on the substance injected, and evaluate variables associated with forming transmission clusters. A cross-sectional study was conducted with data from 2019 to 2023. Participants completed a questionnaire on sociodemographic, clinical, and behavioral variables. Bivariate and multi-variate logistic regression analyses were made. Among PWID, 96.3% were male (n = 437), of which 90.1% were men who have sex with men, 1.5% were cisgender females (n = 7), and 2.2% were transgender females (n = 10). PWID were more likely to use drugs during sex (adjusted odds ratio [aOR] = 3.3, 95% confidence interval [CI]: 1.7-6.4, p < 0.001), have more sexually transmitted diseases (aOR = 1.7, 95% CI: 1.1-2.9, p = 0.035), and have less condom use (aOR = 0.5, 95% CI: 0.3-0.8, p = 0.002). The most frequently injected substance was crystal meth, and those who injected it were more likely to have syphilis (aOR = 2.9, 95% CI: 1.2-7.1, p = 0.021), use Grindr (aOR = 3.6, 95% CI: 1.5-8.9, p < 0.001), and engage in high-risk practices (aOR = 6.9, 95% CI: 2.1-22.7, p < 0.001) in the last 3 months. Those under 25 years (p = 0.002), recently infected (p < 0.001), and who practiced insertive anal sex (p < 0.001) were more likely to be part of a cluster. These findings, and the increasing use of crystal meth, underscore the critical need to implement targeted risk-reduction strategies for PWID living with HIV and to design interventions responsive to specific profiles associated with different substances, taking into account not only their risk practices but also protective behaviors such as HIV testing.

HIV-1 Molecular Networks and Pretreatment Drug Resistance at the Frontier of Yunnan Province, China

The border areas of Yunnan Province in China are severely affected by human immunodeficiency virus (HIV). To investigate the risk of HIV transmission and assess the prevalence of pretreatment drug resistance (PDR) in the border area, blood samples were collected from individuals with newly reported HIV in 2021 in three border counties (Cangyuan, Gengma, and Zhenkang) in Yunnan Province. Among the 174 samples successfully genotyped, eight circulating recombinant forms (CRFs), two subtypes, and several unique recombinant forms (URFs) were identified. CRF08_BC (56.9%, 99/174), URFs (14.4%, 25/174), CRF01_AE (10.9%, 19/174), and CRF07_BC (8.0%, 14/174) were the main genotypes. CRF08_BC and URFs were detected more frequently in Chinese and Burmese individuals, respectively. CRF07_BC was found more frequently in men who have sex with men. The proportion of individuals detected in HIV-1 networks was only associated with case-reporting counties. When stratified by county, individuals aged ≤40 years in Cangyuan and ≥41 years in Gengma were more likely to be found in these networks. Furthermore, 93.8% (15/16) of the links in Cangyuan and 79.4% (50/63) of those in Gengma were located within their own counties. The prevalence of PDR to any antiretroviral drug, nucleoside reverse transcriptase inhibitors (NRTIs), and non-nucleoside reverse transcriptase inhibitors (NNRTIs) were 10% (17/170), 0.6% (1/170), and 9.4% (16/170), respectively. The most frequent resistance-associated mutations (RAMs) were V179D/VD/E/T (22.9%, 39/170) and E138A/G/K/R (13.5%, 23/170). In the molecular networks, six clusters shared common RAMs. HIV-1 genetics has become more diverse in border areas. HIV-1 molecular network analysis revealed the different characteristics of the HIV-1 epidemic in the border counties. The prevalence of PDR showed an upward trend, and the PDR to NNRTIs was close to the public response threshold. These findings provide information for the development of AIDS prevention and treatment strategies.

Prevalence and transmission of pretreatment drug resistance in people living with HIV-1 in Shanghai China, 2017-2021

The implementation of pretreatment drug-resistance (PDR) surveillance among people living with HIV-1 (PLWH) is a top priority in countries using efavirenz (EFV)/nevirapine (NVP) for first-line ART. In this study, we assessed the prevalence of PDR among PLWH in Shanghai, China during 2017-2021, and to reveal PDR transmission between Shanghai and other regions of China. A total of 5050 PLWH not on ART during 2017-2021 were included. Partial HIV-1 pol sequences were amplified, sequenced, and analysed for drug-resistance mutations (DRMs). Besides, transmission network of PDR variants was inferred using HIV-TRACE. The overall prevalence of PDR was 4.8% (242/5050; 95% CI, 4.2-5.4). Prevalence of NNRTI-associated PDR was 3.9% (95% CI, 3.4-4.5), higher than those of NRTI-associated (0.8%; 95% CI, 0.5-1.1) and PI-associated PDR (0.9%; 95% CI, 0.6-1.2). High prevalence of PDR (especially high-level resistance) to EFV (132/5050, 2.6%) and NVP (137/5050, 2.7%) were found. CRF01_AE (46.0%) was the predominant HIV-1 genotype with any DRMs, followed by CRF55_01B (21.0%), and CRF07_BC (15.1%). Two NRTI-associated (S68G/N/R and T215A/N/S/Y), five NNRTI-associated (V179D/E/T/L, K103N/R/S/T, E138A/G/K, V106M/I/A and Y181C/I) and two PI-associated mutations (M46I/L/V and Q58E) were the most common observed DRMs in PDR patients in Shanghai. The vast majority of S68G occurred in CRF01_AE (45%). M46I/L/V and Q58E showed a relatively high prevalence in CRF01_AE (4.1%) and CRF07_BC (12.6%). Transmission network analyses demonstrated cross-regional transmission links of PDR variants between Shanghai and other regions of China, which was mainly driven by the potential low-level DRM V179D/E. These results provide crucial information for clinical decision making of first-line ART in PLWH with PDR.

Characterizing HIV-1 transmission by genetic cluster analysis among newly diagnosed patients in the China-Myanmar border region from 2020 to 2023

Cluster analysis of HIV sequence can provide insights into viral transmission patterns in border regions. This study aims to illuminate the HIV-1 subtype distribution and transmission dynamics among newly diagnosed individuals in Dehong prefecture, a region along the China-Myanmar border. Among 948 participants with pol gene sequences, 36 HIV-1 subtypes were identified, with URFs (18.8%, 178/948) being the dominant strain, followed by CRF01_AE (18.5%, 175/948) and CRF07_BC (10.9%, 103/948). Additionally, 287 sequences (30.3%, 287/948) were grouped into 91 clusters, 31 of which contained both Chinese and Burmese individuals. Multivariable logistic regression indicated that men who have sex with men (MSM), CD4 + cell count of 200∼499, and 500 cells/μl and above, and CRF01_AE were risk factors for entering the network. Through the Chord diagram, we found frequent transmission relationships among heterosexual China male group, especially those over 35 years of age. Additionally, the correlation between heterosexual Myanmar female group and heterosexual China male group among cross-risk groups deserved to be emphasized. Furthermore, the network exhibited a growing trend over time, with the largest active transmission cluster identified in Ruili county. In conclusion, the HIV-1 subtype landscape in Dehong has become increasingly complex, and the region has faced risks of transmission from both domestic and international sources. Targeted intervention strategies should be implemented for MSM, heterosexual Chinese middle-aged and elderly men, and heterosexual Burmese young adults to mitigate these risks. These findings provided evidence-based insights for local government to formulate coordinated transnational intervention approaches.

Investigating and forecasting infectious disease dynamics using epidemiological and molecular surveillance data

The integration of viral genomic data into public health surveillance has revolutionized our ability to track and forecast infectious disease dynamics. This review addresses two critical aspects of infectious disease forecasting and monitoring: the methodological workflow for epidemic forecasting and the transformative role of molecular surveillance. We first present a detailed approach for validating epidemic models, emphasizing an iterative workflow that utilizes ordinary differential equation (ODE)-based models to investigate and forecast disease dynamics. We recommend a more structured approach to model validation, systematically addressing key stages such as model calibration, assessment of structural and practical parameter identifiability, and effective uncertainty propagation in forecasts. Furthermore, we underscore the importance of incorporating multiple data streams by applying both simulated and real epidemiological data from the COVID-19 pandemic to produce more reliable forecasts with quantified uncertainty. Additionally, we emphasize the pivotal role of viral genomic data in tracking transmission dynamics and pathogen evolution. By leveraging advanced computational tools such as Bayesian phylogenetics and phylodynamics, researchers can more accurately estimate transmission clusters and reconstruct outbreak histories, thereby improving data-driven modeling and forecasting and informing targeted public health interventions. Finally, we discuss the transformative potential of integrating molecular epidemiology with mathematical modeling to complement and enhance epidemic forecasting and optimize public health strategies.

Improvement in the 95-95-95 Targets Is Accompanied by a Reduction in Both the Human Immunodeficiency Virus Transmission Rate and Incidence in China

BACKGROUND

In 2016, China has implemented the World Health Organization's "treat all" policy. We aimed to assess the impact of significant improvements in the 95-95-95 targets on population-level human immunodeficiency virus (HIV) transmission dynamics and incidence.

METHODS

We focused on 3 steps of the HIV care continuum: diagnosed, on antiretroviral therapy, and achieving viral suppression. The molecular transmission clusters were inferred using HIV-TRACE. New HIV infections were estimated using the incidence method in the European Centre for Disease Prevention and Control HIV Modelling Tool.

RESULTS

Between 2004 and 2023, the national HIV epidemiology database recorded 2.99 billion person-times of HIV tests and identified 1 976 878 new diagnoses. We noted a roughly "inverted-V" curve in the clustering frequency, with the peak recorded in 2014 (67.1% [95% confidence interval, 63.7%-70.5%]), concurrent with a significant improvement in the 95-95-95 targets from 10-13-<71 in 2005 to 84-93-97 in 2022. Furthermore, we observed a parabolic curve for a new infection with the vertex occurring in 2010.

CONCLUSIONS

In general, it was suggested that the improvements in the 95-95-95 targets were accompanied by a reduction in both the population-level HIV transmission rate and incidence. Thus, China should allocate more effort to the first "95" target to achieve a balanced 95-95-95 target.

Evolving molecular HIV clusters revealed genotype-specific dynamics in Guangzhou, China (2008-2020)

OBJECTIVES

This study investigated the genotype-specific dynamics of molecular HIV clusters (MHCs) in Guangzhou, China, aiming to enhance HIV control.

METHODS

HIV pol sequences from people with HIV (PWH) in Guangzhou (2008-2020) were obtained for genotyping and molecular network creation. MHCs were identified and categorized into three types: emerging, growing, or stable. Clustering rates, proportions of cluster types, and members within each type were calculated and their trends were assessed using joinpoint regression.

RESULTS

Among 8395 PWH, the most prevalent HIV-1 genotypes were CRF07_BC (39.7%) and CRF01_AE (32.6%). The genotype composition has been stable since 2012 (Ps > 0.05). The overall clustering rate was 43.3%, with significant variations across genotypes (P < 0.001), indicating genotype-specific transmission fitness. Significant declines in overall and genotype-specific clustering rates toward the end of 2020 (Ps < 0.05), potentially offer support for HIV control efforts in reducing local infections. The continuously increasing proportions of stable clusters and the gradually decreasing proportions of emerging and growing clusters (either Ps < 0.05 or Ps > 0.05) suggest a trend toward stable molecular network structure. However, growing clusters exhibited CRF55_01B, CRF07_BC, and CRF59_01B dominance that indicate their priority for interventions.

CONCLUSION

The evolving MHCs highlight the genotype-specific cluster dynamics, providing fresh insights for enhanced prevention and control strategies.

User experience with HIV molecular epidemiology in research, surveillance, and cluster detection and response: a needs assessment

OBJECTIVE

HIV molecular epidemiology (HIV ME) is a tool that aims to improve HIV research, surveillance, and cluster detection and response. HIV ME is a core pillar of the U.S. initiative to End the HIV Epidemic but faces some challenges and criticisms from stakeholders. We sought to assess user experience to identify the current needs for HIV ME.

METHODS

Users of HIV ME, including researchers and public health practitioners, were engaged via a structured survey. Needs were assessed via open-ended questions about HIV ME. Data were analyzed using reflexive thematic analysis; the concordance of results was assessed semi-quantitatively.

RESULTS

Of 90 possible HIV-ME end-users, 57 completed the survey (response rate = 63%), which included users engaged in research (n = 29) and public health (n = 28). Respondents identified current imperatives, challenges, and strategies to improve HIV ME. Imperatives included characterization of the virus, identification of HIV hotspots, and tailoring of HIV interventions. Challenges encompassed technological issues, ethical concerns, and implementation difficulties. Strategies to improve HIV ME involved improving data access and analysis, enhancing implementation guidance and resources, and fostering community engagement and support. Researchers and public health practitioners prioritized different imperatives, but similarly emphasized the ethical concerns with HIV ME.

CONCLUSION

The imperatives identified by users underscore the necessity of HIV ME, while the challenges highlight the hurdles to be overcome, including ethical concerns which emerged as a shared emphasis across user groups. The strategies outlined offer a roadmap for overcoming these challenges. These insights, drawn from user experience, present a valuable opportunity to inform the development of guidelines for the ethical application of HIV ME in research, surveillance, and cluster detection and response.

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.

Transmission Network and Phylogenetic Analysis Highlight the Role of Suburban Population in HIV-1 Transmission Among Older Adults in Nanjing, Jiangsu Province, China

Describing the transmission characteristics among older adults is essential for designing tailored interventions. An epidemiological investigation combined with phylogenetic analysis was conducted to reveal potential transmission linkages among older adults in Nanjing. Between 2018 and 2022, 188 pol sequences were successfully amplified. Multiple genotypes were identified, including CRF07_BC (55.3%), CRF01_AE (30.3%), CRF08_BC (8.0%), B (3.2%), CRF55_01B (1.1%), CRF67_01B (0.5%), CRF68_01B (0.5%), and unique recombinant forms (URF) (1.1%). Transmission network analysis identified 120 genetically linked patients forming 23 clusters, ranging from 2 to 26 individuals. Multivariable logistic regression analysis showed that compared with farmers and heterosexuals, patients with other occupations (OR = 0.404, 95% CI: 0.173-0.945) and MSM (OR = 0.193, 95% CI: 0.050-0.738) were less likely to have high linkage. Subjects who lived in suburban areas were more likely to have high linkage (OR = 10.932, 95% CI: 3.335-35.830). The Sankey diagram suggested that patients living in suburban areas primarily transmitted the disease within the local district (χ2 = 24.192, p < 0.001). Among the 188 pol sequences, the prevalence of pretreatment drug resistance was 8%. In suburban areas with a rising HIV-1 epidemic, improving early detection and timely treatment is critical. More tailored interventions for this subgroup are urgently needed.

Epidemiological dynamics and molecular characterization of HIV drug resistance in eastern China from 2020 to 2023

Objective

HIV drug resistance (HIVDR) has become a threat to the elimination of the AIDS epidemic due to the global scale-up of antiretroviral therapy (ART) for HIV-infected individuals. This study aims to investigate the epidemiological dynamics and molecular characterization of HIV pretreatment drug resistance (PDR) and acquired drug resistance (ADR) in Hangzhou, a developed region in China.

Methods

An epidemiological survey combined with a molecular transmission network and Bayesian analysis was conducted. A total of 3,596 individuals with newly confirmed HIV infections (from 2020 to 2023) and 164 individuals with ART failure (from 2021 to 2023) were included. The molecular transmission network was used to identify key drug-resistant transmission clusters, while the Bayesian analysis was utilized to trace the origins and spread of these clusters.

Results

The overall prevalence of PDR was found to be 8.4% (303/3596). Among these cases, PDR to non-nucleoside reverse transcriptase inhibitors (NNRTIs) accounted for 4.7% (170/3596), significantly higher than the resistance observed for protease inhibitors (PIs; 2.8%, p < 0.001) and nucleoside reverse transcriptase inhibitors (NRTIs; 1.4%, p < 0.001). Multivariate logistic regression analysis revealed a significantly higher PDR value among individuals infected with the CRF07_BC subtype compared to those with the CRF08_BC subtype (aOR = 0.56, 95% CI = 0.359-0.859, p = 0.008). The molecular transmission network analysis identified the transmission of the drug resistance mutation (DRM) Q58E within the clusters of the CRF07_BC subtype. The Bayesian analysis suggested that these clusters were introduced into Hangzhou from Shenzhen between 2005 and 2012. Furthermore, the study highlighted 50.6% (83/164) prevalence of ADR among individuals experiencing ART failure. The combined molecular network analysis of virological failure and newly confirmed HIV infections indicated the transmission of the K103N mutation between these groups.

Conclusion

In conclusion, targeted interventions may be necessary for specific subtypes and transmission clusters to control the spread of drug-resistant HIV. Continuous monitoring of resistance patterns is critical to inform treatment strategies and optimize ART regimens.

Novel insights on unraveling dynamics of transmission clusters in outbreaks using phylogeny-based methods

Molecular data analysis is invaluable in understanding the overall behavior of a rapidly spreading virus population when epidemiological surveillance is problematic. It is also particularly beneficial in describing subgroups within the population, often identified as clades within a phylogenetic tree that represent individuals connected via direct transmission or transmission via differing risk factors in viral spread. However, transmission patterns or viral dynamics within these smaller groups should not be expected to exhibit homogeneous behavior over time. As such, standard phylogenetic approaches that identify clusters based on summary statistics would not be expected to capture dynamic clusters of transmission. We, therefore, sought to evaluate the performance of existing and adapted phylogeny-based cluster identification tools on simulated transmission clusters exhibiting dynamic transmission behavior over time. Despite the complementarity of the tools, we provide strong evidence that novel cluster identification methods are needed for reliable detection of epidemiologically linked individuals, particularly those exhibiting changing transmission dynamics during dynamic outbreak scenarios.

Insights into the molecular network characteristics of major HIV-1 subtypes in developed Eastern China: a study based on comprehensive molecular surveillance data

PURPOSE

This study aimed to conduct a comprehensive molecular epidemiology study of major HIV-1 subtypes in developed Eastern China (Zhejiang Province).

METHODS

Plasma samples and epidemiological information were collected from 4180 newly diagnosed HIV-1 positive patients in Zhejiang Province in 2021. Pol sequences were obtained to determine the subtypes via multiple analytical tools. HIV-1 molecular networks were constructed on the basis of genetic distances to analyze transmission patterns among major subtypes. Furthermore, the birth-death skyline (BDSKY) model was utilized to estimate the transmission risks associated with large clusters (LCs).

RESULTS

In 4180 patients, 3699 (88.49%) pol sequences were successfully obtained and classified into four subtype groups. In the networks under an optimal genetic distance of 0.01 substitutions/site, the majority of links (74.52%, 1383/1856) involved individuals within the same city, highlighting the predominant role of local transmission in driving the HIV-1 epidemic. In the CRF07_BC, CRF01_AE, and others/URFs networks, men who have sex with men (MSM) were the primary sexual transmission population, with the younger MSM group (< 30 years old) exhibiting higher linkage frequencies. Within the CRF08_BC network, 93.98% of individuals were infected primarily through heterosexual contact and had a significantly greater risk of localized clustering than other subtypes did. Moreover, fifteen identified LCs were predominantly transmitted through commercial heterosexual contact (CHC), exhibiting localized clustering and high potential for sustained diffusion.

CONCLUSIONS

Overall, our findings reveal a diverse and heterogeneous distribution of HIV-1 subtypes in Zhejiang Province, with noticeable variations in hotspots across different geographic areas and populations.

Combining molecular transmission network analysis and spatial epidemiology to reveal HIV-1 transmission pattern among the older people in Nanjing, China

BACKGROUND

In China, the problem of HIV infection among the older people has become increasingly prominent. This study aimed to analyze the pattern and influencing factors of HIV transmission based on a genomic and spatial epidemiological analysis among this population.

METHODS

A total of 432 older people who were aged ≥ 50 years, newly diagnosed with HIV-1 between January 2018 and December 2021 and without a history of ART were enrolled. HIV-1 pol gene sequence was obtained by viral RNA extraction and nested PCR. The molecular transmission network was constructed using HIV-TRACE and the spatial distribution analyses were performed in ArcGIS. The multivariate logistic regression analysis was performed to analyze the factors associated with clustering.

RESULTS

A total of 382 sequences were successfully sequenced, of which CRF07_BC (52.3%), CRF01_AE (32.5%), and CRF08_BC (6.8%) were the main HIV-1 strains. A total of 176 sequences entered the molecular network, with a clustering rate of 46.1%. Impressively, the clustering rate among older people infected through commercial heterosexual contact was as high as 61.7% and three female sex workers (FSWs) were observed in the network. The individuals who were aged ≥ 60 years and transmitted the virus by commercial heterosexual contact had a higher clustering rate, while those who were retirees or engaged other occupations and with higher education degree were less likely to cluster. There was a positive spatial correlation of clustering rate (Global Moran I = 0.206, P < 0.001) at the town level and the highly aggregated regions were mainly distributed in rural area. We determined three large clusters which mainly spread in the intra-region of certain towns in rural areas. Notably, 54.5% of cases in large clusters were transmitted through commercial heterosexual contact.

CONCLUSIONS

Our joint analysis of molecular and spatial epidemiology effectively revealed the spatial aggregation of HIV transmission and highlighted that towns of high aggregation were mainly located in rural area. Also, we found vital role of commercial heterosexual contact in HIV transmission among older people. Therefore, health resources should be directed towards highly aggregated rural areas and prevention strategy should take critical persons as entry points.

Identifying Impacts of Contact Tracing on Epidemiological Inference from Phylogenetic Data

Robust sampling methods are foundational to inferences using phylogenies. Yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications such as infectious disease outbreak investigations, has not been investigated in the molecular epidemiology field. To understand how contact tracing influences a recovered phylogeny, 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 examined real data from 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 data collection of 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. Overall, our results highlight the importance of including possible non-uniform sampling schemes when examining phylogenetic trees. For that, SEEPS serves as a useful tool to evaluate such impacts, thereby facilitating better phylogenetic inferences of the characteristics of a disease outbreak. SEEPS is available at github.com/MolEvolEpid/SEEPS.

Oral HIV pre-exposure prophylaxis use and resistance-associated mutations among men who have sex with men and transgender persons newly diagnosed with HIV in the Netherlands: results from the ATHENA cohort, 2018 to 2022

BackgroundIn the Netherlands, HIV pre-exposure prophylaxis (PrEP) has been available since 2019. However, the extent of PrEP use prior to HIV diagnosis and development of PrEP-resistance-associated mutations (RAMs) is not known.AimWe assessed prior PrEP use and potential transmission of PrEP RAMs among men who have sex with men (MSM) and transgender persons (TGP) with a new HIV diagnosis in the Netherlands.MethodsData on prior PrEP use between 1 January 2018 and 31 December 2022 were available from the Dutch national ATHENA cohort. We assessed proportion of prior PrEP use, detected PrEP associated RAMs and assessed potential onward transmission of RAMs between 2010 and 2022 using a maximum likelihood tree.ResultsData on prior PrEP use were available for 583/1,552 (36.3%) individuals, with 16% (94/583) reporting prior PrEP use. In 489 individuals reporting no prior PrEP use, 51.5% did not use PrEP due to: low HIV-risk perception (29%), no access (19.1%), personal preference (13.1%), and being unaware of PrEP (19.1%). For PrEP users, 13/94 (13.8%) harboured a M184V/I mutation, of whom two also harboured a K65R mutation. In people with a recent HIV infection, detection of PrEP RAMs increased from 0.23% (2/862) before 2019 to 4.11% (9/219) from 2019. We found no evidence of onward transmission of PrEP RAMs.ConclusionThe prevalence of PrEP-associated RAMs has increased since PrEP became available in the Netherlands. More widespread access to PrEP and retaining people in PrEP programmes when still at substantial risk is crucial to preventing new HIV infections.

Men with a history of commercial heterosexual contact play essential roles in the transmission of HIV-1 CRF55_01B from men who have sex with men to the general population in Guangxi, China

Background

There is increasing focus on HIV-1 CRF55_01B in China. However, there is limited information regarding the dissemination of CRF55_01B across different regions and populations in Guangxi. This study was performed to elucidate the evolutionary history of the introduction and dissemination of CRF55_01B in Guangxi.

Methods

Molecular network and phylogenetic analyses were used to investigate the transmission characteristics of CRF55_01B in China. The analyses particularly focused on the cross-provincial spatial and temporal transmission patterns between Guangdong Province and Guangxi, as well as the transmission dynamics among different regions and populations within Guangxi.

Results

In total, 2226 partial pol sequences of CRF55_01B strains sampled from 2007 to 2022 were collected, including 1895 (85.09%) sequences from Guangdong, 199 (8.94%) sequences from Guangxi, and 172 (7.59%) sequences from other provinces of China. Most people living with HIV in Guangxi were infected with HIV-1 through heterosexuals (52.76%). Among these, 19.10% had a history of commercial heterosexual contact (CHC) and 15.58% had a history of non-marital non-commercial heterosexual contact (NMNCHC). Overall, 1418 sequences were identified in the molecular network. Notably, the sequences from Guangdong Province were most closely linked to those from Guangxi. Phylogenetic analysis showed that CRF55_01B was first introduced from Shenzhen City to Nanning City around 2007. Subsequently, CRF55_01B established local transmission within Guangxi, with Nanning City serving as the transmission center from 2008 to 2017. After 2017, the CRF55_01B strain spread to other regions of Guangxi. Men who have sex with men (MSM) and men with a history of CHC have played a significant role in the transmission of CRF55_01B among different populations in Guangxi.

Conclusions

This study provides evidence on the transmission trajectory of CRF55_01B among different regions and populations in Guangxi. Given the bridging role of men with a history of CHC in the dissemination of CRF55_01B from MSM to the general population, it is imperative to enhance surveillance among key populations to mitigate the secondary transmission of HIV-1.

Application of molecular epidemiology in revealing HIV-1 transmission network and recombination patterns in Tianjin, China

Using a comprehensive molecular epidemiological approach, we characterized the transmission dynamics of HIV-1 among the MSM population in Tianjin, China. Our findings revealed that 38.56% (386/1001) of individuals clustered across 109 molecular transmission clusters (TCs), with MSM aged 50 and below being the group most commonly transmitting HIV-1. Among the identified TCs, CRF01_AE predominated, followed by CRF07_BC. Notably, CRF07_BC demonstrated a higher propensity for forming large clusters compared to CRF01_AE. Birth-death skyline analyses of the two largest clusters indicated that the HIV/AIDS transmission may be at a critical point, nearly all had Re approximately 1 by now. A retrospective analysis revealed that the rapid expansion of these large clusters was primarily driven by the introduction of viruses in 2021, highlighting the crucial importance of continuous molecular surveillance in identifying newly emerging high-risk transmission chains and adapting measures to address evolving epidemic dynamics. Furthermore, we detected the transmission of drug-resistant mutations (DRMs) within the TCs, particularly in the CRF07_BC clusters (K103N, Y181C, and K101E) and CRF01_AE clusters (P225H and K219R), emphasizing the importance of monitoring to support the continued efficacy of first-line therapies and pre-exposure prophylaxis (PrEP). Recombination analyses indicated that complex recombinant patterns, associated with increased amino acid variability, could confer adaptive traits to the viruses, potentially providing a competitive advantage in certain host populations or regions. Our study highlights the potential of integrating molecular epidemiological and phylodynamic approaches to inform targeted interventions.

Phylogenetic signatures reveal multilevel selection and fitness costs in SARS-CoV-2

Background

Large-scale sequencing of SARS-CoV-2 has enabled the study of viral evolution during the COVID-19 pandemic. Some viral mutations may be advantageous to viral replication within hosts but detrimental to transmission, thus carrying a transient fitness advantage. By affecting the number of descendants, persistence times and growth rates of associated clades, these mutations generate localised imbalance in phylogenies. Quantifying these features in closely-related clades with and without recurring mutations can elucidate the tradeoffs between within-host replication and between-host transmission.

Methods

We implemented a novel phylogenetic clustering algorithm ( mlscluster, https://github.com/mrc-ide/mlscluster) to systematically explore time-scaled phylogenies for mutations under transient/multilevel selection. We applied this method to a SARS-CoV-2 time-calibrated phylogeny with >1.2 million sequences from England, and characterised these recurrent mutations that may influence transmission fitness across PANGO-lineages and genomic regions using Poisson regressions and summary statistics.

Results

We found no major differences across two epidemic stages (before and after Omicron), PANGO-lineages, and genomic regions. However, spike, nucleocapsid, and ORF3a were proportionally more enriched for transmission fitness polymorphisms (TFP)-homoplasies than other proteins. We provide a catalog of SARS-CoV-2 sites under multilevel selection, which can guide experimental investigations within and beyond the spike protein.

Conclusions

This study provides empirical evidence for the existence of important tradeoffs between within-host replication and between-host transmission shaping the fitness landscape of SARS-CoV-2. This method may be used as a fast and scalable means to shortlist large sequence databases for sites under putative multilevel selection which may warrant subsequent confirmatory analyses and experimental confirmation.

Characteristics of Subtype and Molecular Transmission Networks among Newly Diagnosed HIV-1 Infections in Patients Residing in Taiyuan City, Shanxi Province, China, from 2021 to 2023

The HIV-1 pandemic, spanning four decades, presents a significant challenge to global public health. This study aimed to understand the molecular transmission characteristics of newly reported HIV infections in Taiyuan, Shanxi Province, China, to analyze the characteristics of subtypes and the risk factors of the transmission network, providing a scientific basis for precise prevention and intervention measures. A total of 720 samples were collected from newly diagnosed HIV-1 patients residing in Taiyuan between 2021 and 2023. Sequencing of partial genes of the HIV-1 pol gene resulted in multiple sequence acquisitions and was conducted to analyze their subtypes and molecular transmission networks. Out of the samples, 584 pol sequences were obtained, revealing 17 HIV-1 subtypes, with CRF07_BC (48.29%), CRF01_AE (31.34%), and CRF79_0107 (7.19%) being the dominant subtypes. Using a genetic distance threshold of 1.5%, 49 molecular transmission clusters were generated from the 313 pol gene sequences. Univariate analysis showed significant differences in the HIV transmission molecular network in terms of HIV subtype and household registration (p < 0.05). Multivariate logistic regression analysis showed that CRF79_0107 subtype and its migrants were associated with higher proportions of sequences in the HIV transmission network. These findings provide a scientific foundation for the development of localized HIV-specific intervention strategies.

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 heterosexual 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.

The origin and spread of HIV-1 CRF59_01B epidemic in China: A molecular network and phylogeographic analysis

Human immunodeficiency virus type 1 CRF59_01B, identified in China in 2013, has been detected nationwide, exhibiting notably high prevalence in Guangzhou and its vicinity. This study aimed to unravel its origin and migration. A data set was established, incorporating all available CRF59_01B pol gene sequences and their metadata from Guangzhou and the public database. Bayesian phylogeographic analysis demonstrated that CRF59_01B originated in Shenzhen, the neighboring city of Guangzhou, around 1998 with posterior probability of 0.937. Molecular network analysis detected 1131 transmission links and showed a remarkably high clustering rate (78.9%). Substantial inter-city transmissions (26.5%, 300/1131) were observed between Shenzhen and Guangzhou while inter-region transmissions linked Guangzhou with South (46) and Southwest (64) China. The centre of Guangzhou was the hub of CRF59_01B transmission, including the inflow from Shenzhen (3.57 events/year) and outflow to the outskirts of Guangzhou (>2 events/year). The large-scale analysis revealed significant migration from Shenzhen to Guangzhou (5.08 events/year) and North China (0.59 events/year), and spread from Guangzhou to Central (0.47 events/year), East (0.42 events/year), South (0.76 events/year), Southwest China (0.76 events/year) and Shenzhen (1.89 events/year). Shenzhen and Guangzhou served as the origin and the hub of CRF59_01B circulation, emphasizing inter-city cooperation and data sharing to confine its nationwide diffusion.

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.

Characterising HIV-1 transmission in Victoria, Australia: a molecular epidemiological study

Background

In Australia the incidence of HIV has declined steadily, yet sustained reduction of HIV transmission in this setting requires improved public health responses. As enhanced public health responses and prioritisation of resources may be guided by molecular epidemiological data, here we aimed to assess the applicability of these approaches in Victoria, Australia.

Methods

A comprehensive collection of HIV-1 pol sequences from individuals diagnosed with HIV in Victoria, Australia, between January 1st 2000 and December 31st 2020 were deidentified and used as the basis of our assessment. These sequences were subtyped and surveillance drug resistance mutations (SDRMs) identified, before definition of transmission groups was performed using HIV-TRACE (0.4.4). Phylodynamic methods were applied using BEAST (2.6.6), assessing effective reproductive numbers for large groups, and additional demographic data were integrated to provide a high resolution view of HIV transmission in Victoria on a decadal time scale.

Findings

Based on standard settings for HIV-TRACE, 70% (2438/3507) of analysed HIV-1 pol sequences were readily assigned to a transmission group. Individuals in transmission groups were more commonly males (aOR 1.50), those born in Australia (aOR 2.13), those with probable place of acquisition as Victoria (aOR 6.73), and/or those reporting injectable drug use (aOR 2.13). SDRMs were identified in 375 patients (10.7%), with sustained transmission of these limited to a subset of smaller groups. Informative patterns of epidemic growth, stabilisation, and decline were observed; many transmission groups showed effective reproductive numbers (R e ) values reaching greater than 4.0, representing considerable epidemic growth, while others maintained low R e values.

Interpretation

This study provides a high resolution view of HIV transmission in Victoria, Australia, and highlights the potential of molecular epidemiology to guide and enhance public health responses in this setting. This informs ongoing discussions with community groups on the acceptability and place of molecular epidemiological approaches in Australia.

Funding

National Health and Medical Research Council, Australian Research Council.

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.

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.

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.

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.

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.