Molecular Epidemiology and the Transformation of HIV Prevention

Molecular network analysis of 308 newly diagnosed HIV infection and 210 ART failure patients from rural counties in Sichuan

BACKGROUND

Few studies on molecular epidemiology have studied people with newly diagnosed HIV infection and ART Failure Patients at the same time in rural China. With more serious HIV epidemic than in other provinces in China, Sichuan is an area suitable for this study.

OBJECTIVE

To analyze the characteristics of HIV-1 molecular networks and factors related to network entry among newly diagnosed HIV infection and ART Failure Patients in three county-level cities (A, B, C) in Sichuan Province, to provide scientific basis for accurate prevention and control.

METHODS

Nested PCR amplification method was used to amplify HIV-1 pol gene region of 530 blood samples, Sequencer 4.9 was used to edit, clean and splice the gene sequence, Bioedit correction, Fastree 2.1.8 and Figtree 1.4.2 to construct evolutionary tree and determine genotype. HyPhy2.2.4 and Cytoscape 3.6.1 software were used to construct molecular network. Logistic regression analysis was applied.

RESULTS

523(98.68%) pol sequences were obtained, and a total of 518 valid sequences with basic information came into the final analyses. A total of 6 genotypes were detected, namely CRF01_AE (320,61.78%), CRF07_BC (149,28.76%), B (30,5.79%), CRF08_BC (11, 2.12%), CRF55_01B (6, 1.16%) and C (2, 0.39%). 186 of 518(35.91%) sequences entered the network at a genetic distance of 0.8%, forming 42 propagation clusters. "High-risk transmitters"(connected with two and more) accounted for 21.62%. Logistic regression showed that≥50 years old (OR = 2.474) were more risky than 18-49 years old, CRF07_BC sub-type (OR = 0.174) were less risky than CRF01_AE sub-type, B sub-type (OR = 6.698) is higher risky than CRF01_AE sub-type, and District B (OR = 0.077) less risky than that of A city.

CONCLUSION

The sources of HIV infection in rural Sichuan are diversified and complicated. The prevention and control of HIV infection in Sichuan Province should focus on strengthening the long-term dynamic detection of elderly population, B strain sub-type, and in City A.

Toward Consent in Molecular HIV Surveillance?: Perspectives of Critical Stakeholders

BACKGROUND

The emergence of molecular HIV surveillance (MHS) and cluster detection and response (CDR) programs as key features of the United States (US) HIV strategy since 2018 has caused major controversies. HIV surveillance programs that re-use individuals' routinely collected clinical HIV data do not require consent on the basis that the public benefit of these programs outweighs individuals' rights to opt out. However, criticisms of MHS/CDR have questioned whether expanded uses of HIV genetic sequence data for prevention reach beyond traditional public health ethics frameworks. This study aimed to explore views on consent within MHS/CDR among critical stakeholders.

METHODS

In 2021 we interviewed 26 US HIV stakeholders who identified as being critical or concerned about the rollout of MHS/CDR. Stakeholders included participants belonging to networks of people living with HIV, other advocates, academics, and public health professionals. This analysis focused on identifying the range of positions among critical and concerned stakeholders on consent affordances, opt-outs, how to best inform people living with HIV about how data about them are used in public health programs, and related ethical issues.

RESULTS

Participants were broadly supportive of introducing some forms of consent into MHS/CDR. However, they differed on the specifics of implementing consent. While some participants did not support introducing consent affordances, all supported the idea that people living with HIV should be informed about how HIV surveillance and prevention is conducted and how individuals' data are used.

CONCLUSIONS

MHS/CDR has caused sustained controversy. Among critical stakeholders, consent is generally desirable but contested, although the right for people living with HIV to be informed was centrally supported. In an era of big data-driven public health interventions and routine uses of HIV genetic sequence data in surveillance and prevention, CDC and other agencies should revisit public health ethics frameworks and consider the possibility of consent processes.

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

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

Advancing Dialogue About Consent and Molecular HIV Surveillance in the United States: Four Proposals Following a Federal Advisory Panel's Call for Major Reforms

Policy Points Molecular HIV surveillance and cluster detection and response (MHS/CDR) programs have been a core public health activity in the United States since 2018 and are the "fourth pillar" of the Ending the HIV Epidemic initiative launched in 2019. MHS/CDR has caused controversy, including calls for a moratorium from networks of people living with HIV. In October 2022, the Presidential Advisory Council on HIV/AIDS (PACHA) adopted a resolution calling for major reforms. We analyze the policy landscape and present four proposals to federal stakeholders pertaining to PACHA's recommendations about incorporating opt-outs and plain-language notifications into MHS/CDR programs.

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

Objective

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

Methods

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

Results

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

Conclusion

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Spatial distribution and temporal trends of AIDS in Brazil and regions between 2005 and 2020

OBJECTIVE

To analyze the spatial distribution and the temporal trend of the AIDS incidence rate in Brazil from 2005 to 2020.

METHODS

This is an ecological, temporal, and spatial study on AIDS cases in Brazil. Data from the Notifiable Diseases Information System were stratified by year of diagnosis, region of the country/municipalities of residence, and age group (over 13 years). Incidence rates were calculated for temporal estimation using the Joinpoint model, as well as Spatial Empirical Bayes (SEB) for spatial distribution, using the Kernel density estimator.

RESULTS

The incidence rate in Brazil, in 2020, was 17.69 cases per 100 thousand inhabitants. The general trend (2005-2020) was decrease in Brazil (Annual Percent Change - APC=-2.0%), in the Southeast (APC=-4.4%) and South (APC=-3.0%) regions. The North (APC=2.3%) showed an increase trend, whereas the Southeast and Midwest regions were stationary (p>0.05). Brazil, Southeast, South, and Midwest regions showed a decrease trend in most age groups. The Northeast and North regions showed an increase in the age groups of 13-29 years and 13-24 years, respectively. The Kernel estimator showed clusters with SEB above 30/10 thousand inhabitants in the states of Paraíba, Sergipe, Alagoas, Pernambuco, São Paulo, Minas Gerais, Pará, Rio Grande do Sul, and Santa Catarina.

CONCLUSION

Brazil, the Southeast, and South regions showed a decrease in the incidence rate, whereas the North region increased and the Northeast and Midwest regions were stationary. The Southeast, South, and Northeast regions presented the largest clusters of SEB.

Distribuição espacial e tendência temporal da AIDS no Brasil e regiões entre 2005 e 2020

RESUMO: Objetivo: Analisar a distribuição espacial e a tendência temporal da taxa de incidência de AIDS no Brasil no período de 2005 a 2020. Métodos: Estudo ecológico, temporal e espacial sobre os casos de AIDS no Brasil. Dados provenientes do Sistema de Informação de Agravos de Notificação do Departamento de Informática do Sistema Único de Saúde foram estratificados por ano do diagnóstico, região do país/municípios de residência e faixa etária (acima de 13 anos). Foram calculadas as taxas de incidência (TI) para a estimativa temporal por meio do modelo de joinpoint, bem como as taxas bayesianas empíricas espaciais (TBEE) para a distribuição espacial pelo estimador de densidade de Kernel. Resultados: A TI no Brasil no ano de 2020 foi de 17,69 casos para cada 100 mil habitantes. A tendência geral (2005–2020) foi de diminuição no Brasil (variação percentual anual — VPA=-2,0%), Sudeste (VPA=-4,4%) e Sul (VPA=-3,0%). O Norte (VPA=2,3%) demonstrou aumento, enquanto o Sudeste e Centro-oeste foram estacionários (p>0,05). O Brasil, Sudeste, Sul e Centro-oeste apresentaram tendência de diminuição na maioria das faixas etárias. O Nordeste e Norte apresentaram aumento nas faixas etárias de 13 a 29 anos e 13 a 24 anos, respectivamente. O estimador de Kernel demonstrou conglomerados com TBEE acima de 30/10 mil habitantes nos estados de Paraíba, Sergipe, Alagoas, Pernambuco, São Paulo, Minas Gerais, Pará, Rio Grande do Sul e Santa Catarina. Conclusão: O Brasil e as Regiões Sudeste e Sul apresentaram diminuição da TI, enquanto o Norte aumentou e o Nordeste e Centro-oeste foram estacionários. As Regiões Sudeste, Sul e Nordeste apresentaram os maiores conglomerados das TBEE.

Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam

Background:

More than 300 cities including the city of Amsterdam in the Netherlands have joined the UNAIDS Fast-Track Cities initiative, committing to accelerate their HIV response and end the AIDS epidemic in cities by 2030. To support this commitment, we aimed to estimate the number and proportion of Amsterdam HIV infections that originated within the city, from Amsterdam residents. We also aimed to estimate the proportion of recent HIV infections during the 5-year period 2014–2018 in Amsterdam that remained undiagnosed.

Methods:

We located diagnosed HIV infections in Amsterdam using postcode data (PC4) at time of registration in the ATHENA observational HIV cohort, and used HIV sequence data to reconstruct phylogeographically distinct, partially observed Amsterdam transmission chains. Individual-level infection times were estimated from biomarker data, and used to date the phylogenetically observed transmission chains as well as to estimate undiagnosed proportions among recent infections. A Bayesian Negative Binomial branching process model was used to estimate the number, size, and growth of the unobserved Amsterdam transmission chains from the partially observed phylogenetic data.

Results:

Between 1 January 2014 and 1 May 2019, there were 846 HIV diagnoses in Amsterdam residents, of whom 516 (61%) were estimated to have been infected in 2014–2018. The rate of new Amsterdam diagnoses since 2014 (104 per 100,000) remained higher than the national rates excluding Amsterdam (24 per 100,000), and in this sense Amsterdam remained a HIV hotspot in the Netherlands. An estimated 14% [12–16%] of infections in Amsterdan MSM in 2014–2018 remained undiagnosed by 1 May 2019, and 41% [35–48%] in Amsterdam heterosexuals, with variation by region of birth. An estimated 67% [60–74%] of Amsterdam MSM infections in 2014–2018 had an Amsterdam resident as source, and 56% [41–70%] in Amsterdam heterosexuals, with heterogeneity by region of birth. Of the locally acquired infections, an estimated 43% [37–49%] were in foreign-born MSM, 41% [35–47%] in Dutch-born MSM, 10% [6–18%] in foreign-born heterosexuals, and 5% [2–9%] in Dutch-born heterosexuals. We estimate the majority of Amsterdam MSM infections in 2014–2018 originated in transmission chains that pre-existed by 2014.

Conclusions:

This combined phylogenetic, epidemiologic, and modelling analysis in the UNAIDS Fast-Track City Amsterdam indicates that there remains considerable potential to prevent HIV infections among Amsterdam residents through city-level interventions. The burden of locally acquired infection remains concentrated in MSM, and both Dutch-born and foreign-born MSM would likely benefit most from intensified city-level interventions.

Funding:

This study received funding as part of the H-TEAM initiative from Aidsfonds (project number P29701). The H-TEAM initiative is being supported by Aidsfonds (grant number: 2013169, P29701, P60803), Stichting Amsterdam Dinner Foundation, Bristol-Myers Squibb International Corp. (study number: AI424-541), Gilead Sciences Europe Ltd (grant number: PA-HIV-PREP-16-0024), Gilead Sciences (protocol numbers: CO-NL-276-4222, CO-US-276-1712, CO-NL-985-6195), and M.A.C AIDS Fund.

The Origin, Epidemiology, and Phylodynamics of Human Immunodeficiency Virus Type 1 CRF47_BF

CRF47_BF is a circulating recombinant form (CRF) of the human immunodeficiency virus type 1 (HIV-1), the etiological agent of AIDS. CRF47_BF represents one of 19 CRFx_BFs and has a geographic focus in Spain, where it was first identified in 2010. Since its discovery, CRF47_BF has expanded considerably in Spain, predominantly through heterosexual contact (∼56% of the infections). Little is known, however, about the origin and diversity of this CRF or its epidemiological correlates, as very few samples have been available so far. This study conducts a phylogenetic analysis with representatives of all CRFx_BF sequence types along with HIV-1 M Group subtypes to validate that the CRF47_BF sequences share a unique evolutionary history. The CRFx_BF sequences cluster into a single, not well supported, clade that includes their dominant parent subtypes (B and F). This clade also includes subtype D and excludes sub-subtype F2. However, the CRF47_BF sequences all share a most recent common ancestor. Further analysis of this clade couples CRF47_BF protease-reverse transcriptase sequences and epidemiological data from an additional 87 samples collected throughout Spain, as well as additional CRF47_BF database sequences from Brazil and Spain to investigate the origin and phylodynamics of CRF47_BF. The Spanish region with the highest proportion of CRF47_BF samples in the data set was the Basque Country (43.7%) with Navarre next highest at 19.5%. We include in our analysis epidemiological data on host sex, mode of transmission, time of collection, and geographic region. The phylodynamic analysis indicates that CRF47_BF originated in Brazil around 1999–2000 and spread to Spain from Brazil in 2002–2003. The virus spread rapidly throughout Spain with an increase in population size from 2011 to 2015 and leveling off more recently. Three strongly supported clusters associated with Spanish regions (Basque Country, Navarre, and Aragon), together comprising 60.8% of the Spanish samples, were identified, one of which was also associated with transmission among men who have sex with men. The expansion in Spain of CRF47_BF, together with that of other CRFs and subtype variants of South American origin, previously reported, reflects the increasing relationship between the South American and European HIV-1 epidemics.

Use of Injection Drugs and Any Form of Methamphetamine in the Portland, OR Metro Area as a Driver of an HIV Time-Space Cluster: Clackamas, Multnomah, and Washington Counties, 2018-2020

We describe the response to detection of a time-space cluster of new HIV infection in the Portland, OR metro area among people who inject drugs (PWID) and/or people who use any form of methamphetamine. This time-space cluster took place in a region with a syndemic of homelessness and drug use. The investigation included new HIV diagnoses in 2018, 2019, and 2020 in Clackamas, Multnomah, and Washington Counties. Public health response included activating incident command, development and implementation of an enhanced interview tool, outreach testing, and stakeholder engagement. We identified 396 new cases of HIV infection, 116 (29%) of which met the cluster definition. Most cluster cases had no molecular relationships to previous cases. Persons responding to the enhanced interview tool reported behaviors associated with HIV acquisition. Field outreach testing did not identify any new HIV cases but did identify hepatitis C and syphilis infections. We show the importance of a robust public health response to a time-space cluster of new HIV infections in an urban area.

When viruses become more virulent

[Figure: see text].

Dating the Origin and Estimating the Transmission Rates of the Major HIV-1 Clusters in Greece: Evidence about the Earliest Subtype A1 Epidemic in Europe

Our aim was to estimate the date of the origin and the transmission rates of the major local clusters of subtypes A1 and B in Greece. Phylodynamic analyses were conducted in 14 subtype A1 and 31 subtype B clusters. The earliest dates of origin for subtypes A1 and B were in 1982.6 and in 1985.5, respectively. The transmission rate for the subtype A1 clusters ranged between 7.54 and 39.61 infections/100 person years (IQR: 9.39, 15.88), and for subtype B clusters between 4.42 and 36.44 infections/100 person years (IQR: 7.38, 15.04). Statistical analysis revealed that the average difference in the transmission rate between the PWID and the MSM clusters was 6.73 (95% CI: 0.86 to 12.60; p = 0.026). Our study provides evidence that the date of introduction of subtype A1 in Greece was the earliest in Europe. Transmission rates were significantly higher for PWID than MSM clusters due to the conditions that gave rise to an extensive PWID HIV-1 outbreak ten years ago in Athens, Greece. Transmission rate can be considered as a valuable measure for public health since it provides a proxy of the rate of epidemic growth within a cluster and, therefore, it can be useful for targeted HIV prevention programs.

HIV Cluster and Outbreak Detection and Response: The Science and Experience

The Respond pillar of the Ending the HIV Epidemic in the U.S. initiative, which consists of activities also known as cluster and outbreak detection and response, offers a framework to guide tailored implementation of proven HIV prevention strategies where transmission is occurring most rapidly. Cluster and outbreak response involves understanding the networks in which rapid transmission is occurring; linking people in the network to essential services; and identifying and addressing gaps in programs and services such as testing, HIV and other medical care, pre-exposure prophylaxis, and syringe services programs. This article reviews the experience gained through 30 HIV cluster and outbreak responses in North America during 2000-2020 to describe approaches for implementing these core response strategies. Numerous jurisdictions that have implemented these response strategies have demonstrated success in improving outcomes related to HIV care and viral suppression, testing, use of prevention services, and reductions in transmission or new diagnoses. Efforts to address important gaps in service delivery revealed by cluster and outbreak detection and response can strengthen prevention efforts broadly through multidisciplinary, multisector collaboration. In this way, the Respond pillar embodies the collaborative, data-guided approach that is critical to the overall success of the Ending the HIV Epidemic in the U.S. initiative.

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

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

Phylogenetic Cluster Analysis Identifies Virological and Behavioral Drivers of Human Immunodeficiency Virus Transmission in Men Who Have Sex With Men

BACKGROUND

Identifying local outbreaks and their drivers is a key step toward curbing human immunodeficiency virus (HIV) transmission and potentially achieving HIV elimination. Such outbreaks can be identified as transmission clusters extracted from phylogenetic trees constructed of densely sampled viral sequences. In this study, we combined phylogenetic transmission clusters with extensive data on virological suppression and behavioral risk of cluster members to quantify the drivers of ongoing transmission over 10 years.

METHODS

Using the comprehensive Swiss HIV Cohort Study and its drug-resistance database, we reconstructed phylogenetic trees for each year between 2007 and 2017. We identified HIV transmission clusters dominated by men who have sex with men (MSM) and determined their annual growth. We used Poisson regression to assess if cluster growth was associated with a per-cluster infectivity and behavioral risk score.

RESULTS

Both infectivity and behavioral risk scores were significantly higher in growing MSM transmission clusters compared to nongrowing clusters (P ≤ .01). The fraction of transmission clusters without infectious members acquiring new infections increased significantly over the study period. The infectivity score was significantly associated with per-capita incidence of MSM transmission clusters in 8 years, while the behavioral risk score was significantly associated with per-capita incidence of MSM transmission clusters in 3 years.

CONCLUSIONS

We present a phylogenetic method to identify hotspots of ongoing transmission among MSM. Our results demonstrate the effectiveness of treatment as prevention at the population level. However, the significantly increasing number of new infections among transmission clusters without infectious members highlights a relative shift from diagnosed to undiagnosed individuals as drivers of HIV transmission in Swiss MSM.

The CDC HIV Outbreak Coordination Unit: Developing a Standardized, Collaborative Approach to HIV Outbreak Assessment and Response

The Centers for Disease Control and Prevention (CDC) and state, territorial, and local health departments have expanded efforts to detect and respond to HIV clusters and outbreaks in the United States. In July 2017, CDC created the HIV Outbreak Coordination Unit (OCU) to ensure consistent and collaborative assessment of requests from health departments for consultation or support on possible HIV clusters and outbreaks of elevated concern. The HIV OCU is a multidisciplinary, cross-organization functional unit within CDC's Division of HIV/AIDS Prevention. HIV OCU members have expertise in areas such as outbreak detection and investigation, prevention, laboratory services, surveillance and epidemiology, policy, communication, and operations. HIV OCU discussions facilitate problem solving, coordination, and situational awareness. Between HIV OCU meetings, designated CDC staff members communicate regularly with health departments to provide support and assessment. During July 2017-December 2019, the HIV OCU reviewed 31 possible HIV clusters and outbreaks (ie, events) in 22 states that were detected by CDC, health departments, or local partners; 17 events involved HIV transmission associated with injection drug use, and other events typically involved sexual transmission or overall increases in HIV diagnoses. CDC supported health departments remotely or on site with planning and prioritization; data collection, management, and analysis; communications; laboratory support; multistate coordination; and expansion of HIV prevention services. The HIV OCU has augmented CDC's support of HIV cluster and outbreak assessment and response at health departments and had important internal organizational benefits. Health departments may benefit from developing or strengthening similar units to coordinate detection and response efforts within and across public health agencies and advance the national Ending the HIV Epidemic initiative.

Increasing Capacity to Detect Clusters of Rapid HIV Transmission in Varied Populations-United States

Molecular cluster detection analyzes HIV sequences to identify rapid HIV transmission and inform public health responses. We describe changes in the capability to detect molecular clusters and in geographic variation in transmission dynamics. We examined the reporting completeness of HIV-1 polymerase sequences in quarterly National HIV Surveillance System datasets from December 2015 to December 2019. Priority clusters were identified quarterly. To understand populations recently affected by rapid transmission, we described the transmission risk and race/ethnicity of people in clusters first detected in 2018–2019. During December 2015 to December 2019, national sequence completeness increased from 26% to 45%. Of the 1212 people in the 136 clusters first detected in 2018–2019, 69% were men who have sex with men (MSM) and 11% were people who inject drugs (PWID). State-by-state analysis showed substantial variation in transmission risk and racial/ethnic groups in clusters of rapid transmission. HIV sequence reporting has increased nationwide. Molecular cluster analysis identifies rapid transmission in varied populations and identifies emerging patterns of rapid transmission in specific population groups, such as PWID, who, in 2015–2016, comprised only 1% of people in such molecular clusters. These data can guide efforts to focus, tailor, and scale up prevention and care services for these populations.

Epidemiology of HIV in the USA: epidemic burden, inequities, contexts, and responses

The HIV epidemic in the USA began as a bicoastal epidemic focused in large cities but, over nearly four decades, the epidemiology of HIV has changed. Public health surveillance data can inform an understanding of the evolution of the HIV epidemic in terms of the populations and geographical areas most affected. We analysed publicly available HIV surveillance data and census data to describe: current HIV prevalence and new HIV diagnoses by region, race or ethnicity, and age; trends in HIV diagnoses over time by HIV acquisition risk and age; and the distribution of HIV prevalence by geographical area. We reviewed published literature to explore the reasons for the current distribution of HIV cases and important disparities in HIV prevalence. We identified opportunities to improve public health surveillance systems and uses of data for planning and monitoring public health responses. The current US HIV epidemic is marked by geographical concentration in the US South and profound disparities between regions and by race or ethnicity. Rural areas vary in HIV prevalence; rural areas in the South are more likely to have a high HIV prevalence than rural areas in other US Census regions. Ongoing disparities in HIV in the South are probably driven by the restricted expansion of Medicaid, health-care provider shortages, low health literacy, and HIV stigma. HIV diagnoses overall declined in 2009-18, but HIV diagnoses among individuals aged 25-34 years increased during the same period. HIV diagnoses decreased for all risk groups in 2009-18; among men who have sex with men (MSM), new diagnoses decreased overall and for White MSM, remained stable for Black MSM, and increased for Hispanic or Latino MSM. Surveillance data indicate profound and ongoing disparities in HIV cases, with disproportionate impact among people in the South, racial or ethnic minorities, and MSM.

Progression and transmission of HIV (PATH 4.0)-A new agent-based evolving network simulation for modeling HIV transmission clusters

We present the Progression and Transmission of HIV (PATH 4.0), a simulation tool for analyses of cluster detection and intervention strategies. Molecular clusters are groups of HIV infections that are genetically similar, indicating rapid HIV transmission where HIV prevention resources are needed to improve health outcomes and prevent new infections. PATH 4.0 was constructed using a newly developed agent-based evolving network modeling (ABENM) technique and evolving contact network algorithm (ECNA) for generating scale-free networks. ABENM and ECNA were developed to facilitate simulation of transmission networks for low-prevalence diseases, such as HIV, which creates computational challenges for current network simulation techniques. Simulating transmission networks is essential for studying network dynamics, including clusters. We validated PATH 4.0 by comparing simulated projections of HIV diagnoses with estimates from the National HIV Surveillance System (NHSS) for 2010-2017. We also applied a cluster generation algorithm to PATH 4.0 to estimate cluster features, including the distribution of persons with diagnosed HIV infection by cluster status and size and the size distribution of clusters. Simulated features matched well with NHSS estimates, which used molecular methods to detect clusters among HIV nucleotide sequences of persons with HIV diagnosed during 2015-2017. Cluster detection and response is a component of the U.S. Ending the HIV Epidemic strategy. While surveillance is critical for detecting clusters, a model in conjunction with surveillance can allow us to refine cluster detection methods, understand factors associated with cluster growth, and assess interventions to inform effective response strategies. As surveillance data are only available for cases that are diagnosed and reported, a model is a critical tool to understand the true size of clusters and assess key questions, such as the relative contributions of clusters to onward transmissions. We believe PATH 4.0 is the first modeling tool available to assess cluster detection and response at the national-level and could help inform the national strategic plan.

Effective HIV Molecular Surveillance Requires Identification of Incident Cases of Infection

BACKGROUND

Ending the HIV epidemic requires knowledge of key drivers of spread of HIV infection.

METHODS

Between 1996 and 2018, 1119 newly and previously diagnosed, therapy-naïve persons with HIV (PWH) from San Diego were followed. A genetic distance-based network was inferred using pol sequences, and genetic clusters grew over time through linkage of sequences from newly observed infections. Cox proportional hazards models were used to identify factors associated with the rate of growth. These results were used to predict the impact of a hypothetical intervention targeting PWH with incident infection. Comparison was made to the CDC EHE molecular surveillance strategy, which prioritizes clusters recently linked to all new HIV diagnoses and does not incorporate data on incident infections.

RESULTS

Overall, 219 genetic linkages to incident infections were identified over a median follow-up of 8.8 years. Incident cluster growth was strongly associated with proportion of PWH in the cluster who themselves had incident infection. (HR 44.09; 95% CI: 17.09, 113.78). The CDC EHE molecular surveillance strategy identified 11 linkages to incident infections a genetic distance threshold of 0.5%, and 24 linkages at 1.5%.

CONCLUSIONS

Over the past two decades, incident infections drove incident HIV cluster growth in San Diego. The current CDC EHE molecular detection and response strategy would not have identified most transmission events arising from those with incident infection in San Diego. Molecular surveillance that includes detection of incident cases will provide a more effective strategy for EHE.

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

Background

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

Methods

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

Results

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

Conclusions

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

Human Immunodeficiency Virus Type 1 Phylodynamics to Detect and Characterize Active Transmission Clusters in North Carolina

BACKGROUND

Human immunodeficiency virus type 1 (HIV-1) phylodynamics can be used to monitor epidemic trends and help target prevention through identification and characterization of transmission clusters.

METHODS

We analyzed HIV-1 pol sequences sampled in North Carolina from 1997 to 2014. Putative clusters were identified using maximum-likelihood trees and dated using Bayesian Markov Chain Monte Carlo inference. Active clusters were defined as clusters including internal nodes from 2009 to 2014. Effective reproductive numbers (Re) were estimated using birth-death models for large clusters that expanded ≥2-fold from 2009 to 2014.

RESULTS

Of 14 921 persons, 7508 (50%) sequences were identified in 2264 clusters. Only 288 (13%) clusters were active from 2009 to 2014; 37 were large (10-36 members). Compared to smaller clusters, large clusters were increasingly populated by men and younger persons; however, nearly 60% included ≥1 women. Clusters with ≥3 members demonstrated assortative mixing by sex, age, and sample region. Of 15 large clusters with ≥2-fold expansion, nearly all had Re approximately 1 by 2014.

CONCLUSIONS

Phylodynamics revealed transmission cluster expansion in this densely sampled region and allowed estimates of Re to monitor active clusters, showing the propensity for steady, onward propagation. Associations with clustering and cluster characteristics vary by cluster size. Harnessing sequence-derived epidemiologic parameters within routine surveillance could allow refined monitoring of local subepidemics.

The Relationship Between the Human Immunodeficiency Virus-1 Transmission Network and the HIV Care Continuum in Los Angeles County

BACKGROUND

Public health action combating human immunodeficiency virus (HIV) includes facilitating navigation through the HIV continuum of care: timely diagnosis followed by linkage to care and initiation of antiretroviral therapy to suppress viral replication. Molecular epidemiology can identify rapidly growing HIV genetic transmission clusters. How progression through the care continuum relates to transmission clusters has not been previously characterized.

METHODS

We performed a retrospective study on HIV surveillance data from 5226 adult cases in Los Angeles County diagnosed from 2010 through 2014. Genetic transmission clusters were constructed using HIV-TRACE. Cox proportional hazard models were used to estimate the impact of transmission cluster growth on the time intervals between care continuum events. Gamma frailty models incorporated the effect of heterogeneity associated with genetic transmission clusters.

RESULTS

In contrast to our expectations, there were no differences in time to the care continuum events among individuals in clusters with different growth dynamics. However, upon achieving viral suppression, individuals in high growth clusters were slower to experience viral rebound (hazard ratio 0.83, P = .011) compared with individuals in low growth clusters. Heterogeneity associated with cluster membership in the timing to each event in the care continuum was highly significant (P < .001), with and without adjustment for transmission risk and demographics.

CONCLUSIONS

Individuals within the same transmission cluster have more similar trajectories through the HIV care continuum than those across transmission clusters. These findings suggest molecular epidemiology can assist public health officials in identifying clusters of individuals who may benefit from assistance in navigating the HIV care continuum.

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

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

Reassessing the Ethics of Molecular HIV Surveillance in the Era of Cluster Detection and Response: Toward HIV Data Justice

In the United States, clinical HIV data reported to surveillance systems operated by jurisdictional departments of public health are re-used for epidemiology and prevention. In 2018, all jurisdictions began using HIV genetic sequence data from clinical drug resistance tests to identify people living with HIV in "clusters" of others with genetically similar strains. This is called "molecular HIV surveillance" (MHS). In 2019, "cluster detection and response" (CDR) programs that re-use MHS data became the "fourth pillar" of the national HIV strategy. Public health re-uses of HIV data are done without consent and are a source of concern among stakeholders. This article presents three cases that illuminate bioethical challenges associated with re-uses of clinical HIV data for public health. We focus on evidence-base, risk-benefit ratio, determining directionality of HIV transmission, consent, and ethical re-use. The conclusion offers strategies for "HIV data justice." The essay contributes to a "bioethics of the oppressed."

Can the United States achieve 90-90-90?

PURPOSE OF REVIEW

To summarize recent trends in knowledge of HIV status, care and viral suppression, and the status of implementation of relevant contextual requirements for the United States to achieve the 90-90-90 goals. Recently, the US government announced a plan to decrease HIV incidence by over 90% by 2030. Reaching this goal may require higher targets than 90-90-90.

RECENT FINDINGS

The United States is on course to reach 90-90-90 goals in the near future, with 86% of persons with HIV aware of their infection, 74% of persons with diagnosed infection in care, and 83% of persons in care with viral suppression in 2016. Some high-burden subnational jurisdictions have already achieved these goals.

SUMMARY

The United States is likely to reach 90-90-90 targets in the near future. However, to reduce HIV incidence by at least 90% by 2030, the United States will need to rapidly meet the new 95-95-95 targets and deploy a comprehensive strategy with novel approaches to testing, retaining persons with HIV on treatment, and preventing new infections with preexposure prophylaxis and comprehensive syringe services programs.

Incident infection in high-priority HIV molecular transmission clusters in the United States

OBJECTIVE

To identify correlates of incident HIV infection in rapidly growing HIV molecular clusters.

DESIGN

Phylogenetic analysis of HIV public health surveillance data.

METHODS

High-priority HIV genetic transmission clusters with evidence of rapid growth in 2012 (i.e. clusters with a pairwise genetic distance ≤0.005 substitutions/site and at least three cases diagnosed in 2012) were identified using HIV-TRACE. Then, we investigated cluster growth, defined as HIV cases diagnosed in the following 5 years that were genetically linked to these clusters. For clusters that grew during the follow-up period, Bayesian molecular clock phylogenetic inference was performed to identify clusters with evidence of incident HIV infection (as opposed to diagnosis of previously infected cases) during this follow-up period.

RESULTS

Of the 116 rapidly growing clusters identified, 73 (63%) had phylogenetic evidence for an incident HIV case during the 5-year follow-up period. Correlates of an incident HIV case arising in clusters included a greater number of diagnosed but virally unsuppressed cases in 2012, a greater number of inferred undiagnosed cases in the cluster in 2012, and a younger time of most recent common ancestor for the cluster.

CONCLUSION

These findings suggest that incident infections in rapidly growing clusters originate equally from diagnosed but unsuppressed cases and undiagnosed infections. These results highlight the importance of promoting retention in care and viral suppression as well as partner notification and other case-finding activities when investigating and intervening on high-priority molecular transmission clusters.

Social Mixing and Clinical Features Linked With Transmission in a Network of Extensively Drug-resistant Tuberculosis Cases in KwaZulu-Natal, South Africa

BACKGROUND

Tuberculosis (TB) is the leading infectious cause of death globally, and drug-resistant TB strains pose a serious threat to controlling the global TB epidemic. The clinical features, locations, and social factors driving transmission in settings with high incidences of drug-resistant TB are poorly understood.

METHODS

We measured a network of genomic links using Mycobacterium tuberculosis whole-genome sequences.

RESULTS

Patients with 2-3 months of cough or who spent time in urban locations were more likely to be linked in the network, while patients with sputum smear-positive disease were less likely to be linked than those with smear-negative disease. Associations persisted using different thresholds to define genomic links and irrespective of assumptions about the direction of transmission.

CONCLUSIONS

Identifying factors that lead to many transmissions, including contact with urban areas, can suggest settings instrumental in transmission and indicate optimal locations and groups to target with interventions.

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

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

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

Tailoring public health responses to growing HIV transmission clusters depends on accurately mapping the risk network through which it spreads and identifying acute infections that represent the leading edge of cluster growth. HIV transmission links, especially those involving persons with acute HIV infection (AHI), can be difficult to uncover, or confirm during partner services investigations. We integrated molecular, epidemiologic, serologic and behavioral data to infer and evaluate transmission linkages between participants of a prospective study of AHI conducted in North Carolina, New York City and San Francisco from 2011-2013. Among the 547 participants with newly diagnosed HIV with polymerase sequences, 465 sex partners were reported, of whom only 35 (7.5%) had HIV sequences. Among these 35 contacts, 23 (65.7%) links were genetically supported and 12 (34.3%) were not. Only five links were reported between participants with AHI but none were genetically supported. In contrast, phylodynamic inference identified 102 unreported transmission links, including 12 between persons with AHI. Importantly, all putative transmission links between persons with AHI were found among large clusters with more than five members. Taken together, the presence of putative links between acute participants who did not name each other as contacts that are found only among large clusters underscores the potential for unobserved or undiagnosed intermediaries. Phylodynamics identified many more links than partner services alone and, if routinely and rapidly integrated, can illuminate transmission patterns not readily captured by partner services investigations.

Pathogen Genomics in Public Health

Rapid advances in DNA sequencing technology ("next-generation sequencing") have inspired optimism about the potential of human genomics for "precision medicine." Meanwhile, pathogen genomics is already delivering "precision public health" through more effective investigations of outbreaks of foodborne illnesses, better-targeted tuberculosis control, and more timely and granular influenza surveillance to inform the selection of vaccine strains. In this article, we describe how public health agencies have been adopting pathogen genomics to improve their effectiveness in almost all domains of infectious disease. This momentum is likely to continue, given the ongoing development in sequencing and sequencing-related technologies.

Natural selection favoring more transmissible HIV detected in United States molecular transmission network

HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters.

Opioid Use Fueling HIV Transmission in an Urban Setting: An Outbreak of HIV Infection Among People Who Inject Drugs-Massachusetts, 2015-2018

Objectives. To describe and control an outbreak of HIV infection among people who inject drugs (PWID).Methods. The investigation included people diagnosed with HIV infection during 2015 to 2018 linked to 2 cities in northeastern Massachusetts epidemiologically or through molecular analysis. Field activities included qualitative interviews regarding service availability and HIV risk behaviors.Results. We identified 129 people meeting the case definition; 116 (90%) reported injection drug use. Molecular surveillance added 36 cases to the outbreak not otherwise linked. The 2 largest molecular groups contained 56 and 23 cases. Most interviewed PWID were homeless. Control measures, including enhanced field epidemiology, syringe services programming, and community outreach, resulted in a significant decline in new HIV diagnoses.Conclusions. We illustrate difficulties with identification and characterization of an outbreak of HIV infection among a population of PWID and the value of an intensive response.Public Health Implications. Responding to and preventing outbreaks requires ongoing surveillance, with timely detection of increases in HIV diagnoses, community partnerships, and coordinated services, all critical to achieving the goal of the national Ending the HIV Epidemic initiative.

Prediction of HIV Transmission Cluster Growth With Statewide Surveillance Data

BACKGROUND

Prediction of HIV transmission cluster growth may help guide public health action. We developed a predictive model for cluster growth in North Carolina (NC) using routine HIV surveillance data.

METHODS

We identified putative transmission clusters with ≥2 members through pairwise genetic distances ≤1.5% from HIV-1 pol sequences sampled November 2010-December 2017 in NC. Clusters established by a baseline of January 2015 with any sequences sampled within 2 years before baseline were assessed for growth (new diagnoses) over 18 months. We developed a predictive model for cluster growth incorporating demographic, clinical, temporal, and contact tracing characteristics of baseline cluster members. We internally and temporally externally validated the final model in the periods January 2015-June 2016 and July 2016-December 2017.

RESULTS

Cluster growth was predicted by larger baseline cluster size, shorter time between diagnosis and HIV care entry, younger age, shorter time since the most recent HIV diagnosis, higher proportion with no named contacts, and higher proportion with HIV viremia. The model showed areas under the receiver-operating characteristic curves of 0.82 and 0.83 in the internal and temporal external validation samples.

CONCLUSIONS

The predictive model developed and validated here is a novel means of identifying HIV transmission clusters that may benefit from targeted HIV control resources.

Ethical issues associated with HIV molecular epidemiology: a qualitative exploratory study using inductive analytic approaches

Background

HIV molecular epidemiology is increasingly recognized as a vital source of information for understanding HIV transmission dynamics. Despite extensive use of these data-intensive techniques in both research and public health settings, the ethical issues associated with this science have received minimal attention. As the discipline evolves, there is reasonable concern that existing ethical and legal frameworks and standards might lag behind the rapid methodological developments in this field. This is a follow-up on our earlier work that applied a predetermined analytical framework to examine the perspectives of a sample of scientists from the fields of epidemiology, public health, virology and bioethics on key ethical issues associated with HIV molecular epidemiology in HIV network research.

Methods

Fourteen in-depth interviews were conducted with scientists from the fields of molecular epidemiology, public health, virology and bioethics. Inductive analytical approaches were applied to identify key themes that emerged from the data.

Results

Our interviewees acknowledged the potential positive impact of molecular epidemiology in the fight against HIV. However, they were concerned that HIV phylogenetics research messages may be incorrectly interpreted if not presented at the appropriate level. There was consensus that HIV phylogenetics research presents a potential risk to privacy, but the probability and magnitude of this risk was less obvious. Although participants acknowledged the social value that could be realized from the analysis of HIV genetic sequences, there was a perceived fear that the boundaries for use of HIV sequence data were not clearly defined.

Conclusions

Our findings highlight distinct ethical issues arising from HIV molecular epidemiology. As the discipline evolves and HIV sequence data become increasingly available, it is critical to ensure that ethical standards keep pace with biomedical advancements. We argue that the ethical issues raised in this study, whether real or perceived, require further conceptual and empirical examination.

Identifying Clusters of Recent and Rapid HIV Transmission Through Analysis of Molecular Surveillance Data

BACKGROUND

Detecting recent and rapid spread of HIV can help prioritize prevention and early treatment for those at highest risk of transmission. HIV genetic sequence data can identify transmission clusters, but previous approaches have not distinguished clusters of recent, rapid transmission. We assessed an analytic approach to identify such clusters in the United States.

METHODS

We analyzed 156,553 partial HIV-1 polymerase sequences reported to the National HIV Surveillance System and inferred transmission clusters using 2 genetic distance thresholds (0.5% and 1.5%) and 2 periods for diagnoses (all years and 2013-2015, ie, recent diagnoses). For rapidly growing clusters (with ≥5 diagnoses during 2015), molecular clock phylogenetic analysis estimated the time to most recent common ancestor for all divergence events within the cluster. Cluster transmission rates were estimated using these phylogenies.

RESULTS

A distance threshold of 1.5% identified 103 rapidly growing clusters using all diagnoses and 73 using recent diagnoses; at 0.5%, 15 clusters were identified using all diagnoses and 13 using recent diagnoses. Molecular clock analysis estimated that the 13 clusters identified at 0.5% using recent diagnoses had been diversifying for a median of 4.7 years, compared with 6.5-13.2 years using other approaches. The 13 clusters at 0.5% had a transmission rate of 33/100 person-years, compared with previous national estimates of 4/100 person-years.

CONCLUSIONS

Our approach identified clusters with transmission rates 8 times those of previous national estimates. This method can identify groups involved in rapid transmission and help programs effectively direct and prioritize limited public health resources.

New HIV-1 circulating recombinant form 94: from phylogenetic detection of a large transmission cluster to prevention in the age of geosocial-networking apps in France, 2013 to 2017

BackgroundEnding the HIV pandemic must involve new tools to rapidly identify and control local outbreaks and prevent the emergence of recombinant strains with epidemiological advantages.AimThis observational study aimed to investigate in France a cluster of HIV-1 cases related to a new circulating recombinant form (CRF). The confirmation this CRF's novelty as well as measures to control its spread are presented.MethodsPhylogenetic analyses of HIV sequences routinely generated for drug resistance genotyping before 2018 in French laboratories were employed to detect the transmission chain. The CRF involved was characterised by almost full-length viral sequencing for six cases. Cases' clinical data were reviewed. Where possible, epidemiological information was collected with a questionnaire.ResultsThe transmission cluster comprised 49 cases, mostly diagnosed in 2016-2017 (n = 37). All were infected with a new CRF, CRF94_cpx. The molecular proximity of this CRF to X4 strains and the high median viraemia, exceeding 5.0 log₁₀ copies/mL, at diagnosis, even in chronic infection, raise concerns of enhanced virulence. Overall, 41 cases were diagnosed in the Ile-de-France region and 45 were men who have sex with men. Among 24 cases with available information, 20 reported finding partners through a geosocial networking app. Prevention activities in the area and population affected were undertaken.ConclusionWe advocate the systematic use of routinely generated HIV molecular data by a dedicated reactive network, to improve and accelerate targeted prevention interventions. Geosocial networking apps can play a role in the spread of outbreaks, but could also deliver local targeted preventive alerts.

Ethical issues in HIV phylogenetics and molecular epidemiology

PURPOSE OF REVIEW

HIV phylogenetic and molecular epidemiology analyses are increasingly being performed with a goal of improving HIV prevention efforts. However, ethical, legal and social issues are associated with these analyses, and should be considered when performed.

RECENT FINDINGS

Several working groups have recently outlined the major issues surrounding the use of molecular epidemiology for HIV prevention. First, the benefits of HIV molecular epidemiology remain unclear, and further work is needed to quantitatively demonstrate the benefits that can be expected. Second, privacy loss is an important risk, with implications of disclosure varying by the regional legal and social climate. Inferential privacy risks will increase with technological improvements in sequencing and analysis. Third, data sharing, which enhances the utility of the data, may also increase the risk of inferential privacy loss. Mitigation strategies are available to address each of these issues.

SUMMARY

HIV molecular epidemiology for research and public health pose significant ethical issues that continue to evolve with improving technology, increased sampling and a changing legal and social climate. Guidance surrounding these issues needs to be developed for researchers and public health officials in an iterative and region specific manner that accounts for the potential benefits and risks of this technology.

Applied Epidemiology Training Needs for the Modern Epidemiologist

Applied epidemiology training occurs throughout an epidemiologist's career, beginning with academic instruction before workforce entry, continuing as professional development while working, and culminating with mentoring the next generation. Epidemiologists need ongoing training on advancements in the field and relevant topics (e.g., informatics, laboratory science, emerging topics) to maintain and improve their skills. Even epidemiologists with advanced skills often want training on methodologic innovations or to practice a skill. Effective applied epidemiology training includes blended learning components of instruction that incorporate hands-on experiences such as simulations and experiential learning, allowing for real-time workflows and incorporation of feedback. To prepare epidemiologists for the future, public health training courses in applied epidemiology must consider the evolution in public health toward a focus on including informatics, technologic innovation, molecular epidemiology, multidisciplinary teams, delivery of population health services, and global health security. Supporting efforts by epidemiologists to increase their skills as part of their career paths ensures a strong workforce that able to tackle public health issues. We explore how to meet current training challenges for the epidemiology workforce, especially given limited resources, based on research and our experience in workforce development across federal agencies and state/local health departments, as well as with international governments and organizations.

Estimating Effects of HIV Sequencing Data Completeness on Transmission Network Patterns and Detection of Growing HIV Transmission Clusters

HIV nucleotide sequence data can identify clusters of persons with genetically similar strains suggesting transmission. We simulated the effect of lowered data completeness, defined by the percent of persons with diagnosed HIV with a reported sequence, on transmission patterns and detection of growing HIV transmission clusters. We analyzed HIV surveillance data for persons with HIV diagnosed during 2008-2014 who resided in Michigan or Washington. We calculated genetic distances, constructed the inferred transmission network for each jurisdiction, and compared transmission network characteristics and detection of growing transmission clusters in the full dataset with artificially reduced datasets. Simulating lower levels of completeness resulted in decreased percentages of persons linked to a cluster from high completeness (full dataset) to low completeness (5%) (Michigan: 54%-18%; Washington, 46%-16%). Patterns of transmission between certain populations remained robust as data completeness level was reduced. As data completeness was artificially decreased, sensitivity of cluster detection substantially diminished in both states. In Michigan, sensitivity decreased from 100% with the full dataset, to 62% at 50% completeness and 21% at 25% completeness. In Washington, sensitivity decreased from 100% with the full dataset, to 71% at 50% completeness and 29% at 25% completeness. Lower sequence data completeness limits the ability to detect clusters that may benefit from investigation; however, inferences can be made about transmission patterns even with low data completeness, given sufficient numbers. Data completeness should be prioritized, as lack of or delays in detection of transmission clusters could result in additional infections.

Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis

To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these 'source' populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8-28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.

National and International Dimensions of Human Immunodeficiency Virus-1 Sequence Clusters in a Northern California Clinical Cohort

Background

Recent advances in high-throughput molecular epidemiology are transforming the analysis of viral infections.

Methods

Human immunodeficiency virus (HIV)-1 pol sequences from a Northern Californian cohort (NCC) of 4553 antiretroviral-naive individuals sampled between 1998 and 2016 were analyzed together with 140 000 previously published global pol sequences. The HIV-TRAnsmission Cluster Engine (HIV-TRACE) was used to infer a transmission network comprising links between NCC and previously published sequences having a genetic distance ≤1.5%.

Results

Twenty-five percent of NCC sequences were included in 264 clusters linked to a published sequence, and approximately one third of these (8.0% of the total) were linked to 1 or more non-US sequences. The largest cluster, containing 512 NCC sequences (11.2% of the total), comprised the subtype B lineage that traced its origin to the earliest North American sequences. Approximately 5 percent of NCC sequences belonged to a non-B subtype, and these were more likely to cluster with a non-US sequence. Twenty-two NCC sequences belonged to 1 of 4 large clusters containing sequences from rapidly growing regional epidemics: CRF07_BC (East Asia), subtype A6 (former Soviet Union), a Japanese subtype B lineage, and an East/Southeast Asian CRF01_AE lineage. Bayesian phylogenetics suggested that most non-B sequences resulted from separate introductions but that local spread within the largest CRF01_AE cluster occurred twice.

Conclusions

The NCC contains national and international links to previously published sequences including many to the subtype B strain that originated in North America and several to rapidly growing Asian epidemics. Despite their rapid regional growth, the Asian epidemic strains demonstrated limited NCC spread.