Addressing Ethical Challenges in US-Based HIV Phylogenetic Research

Action needed to address molecular HIV surveillance ethical concerns

There have been growing ethical concerns about the widespread use of HIV-related molecular epidemiological public health surveillance and research-or what has come to be known as molecular HIV surveillance. The varied concerns of the practice originate due to lack of informed consent, lack of demonstrated benefit for communities, potential for eroded patient care relationships leading to poor health outcomes, and potential implications for information sharing and findings which could increase stigmatization and other negative impacts in contexts where HIV, drug use, sex work, migration, and poverty are criminalized. As people living with HIV, lawyers, clinicians, and social scientists, we are part of the growing movement calling for critical and ethical attention to the practice of molecular HIV surveillance and the public health logic which underwrites the practice. We urge Canadian public health actors and researchers working with molecular surveillance data to heed global guidance and recommendations for culturally informed ethical practices, to engage community members in HIV surveillance programs, and to ensure that people living with HIV are provided appropriate consent processes for uses of secondary data analysis. Furthermore, we urge researchers and Research Ethics Boards to interrogate assumptions of impracticality in seeking subsequent consent to use persons' health information held in data repositories and explore new methods of informed consent.

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.

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.

Prioritization of ethical concerns regarding HIV molecular epidemiology by public health practitioners and researchers

BACKGROUND

HIV molecular epidemiology (HIV ME) can support the early detection of emerging clusters of new HIV infections by combining HIV sequence data routinely obtained during the clinical treatment of people living with HIV with behavioral, geographic, and sociodemographic information. While information about emerging clusters promises to facilitate HIV prevention and treatment efforts, the use of this data also raises several ethical concerns. We sought to assess how those working on the frontlines of HIV ME, specifically public health practitioners (PHPs) and researchers, prioritized these issues.

METHODS

Ethical issues were identified through literature review, qualitative in-depth interviews, and stakeholder engagement. PHPs and researchers using HIV ME prioritized the issues using best-worst scaling (BWS). A balanced incomplete block design was used to generate 11 choice tasks each consisting of a sub-set of 5 ethical concerns. In each task, respondents were asked to assess the most and least concerning issue. Data were analyzed using conditional logit, with a Swait-Louviere test of poolability. Latent class analysis was then used to explore preference heterogeneity.

RESULTS

In total, 57 respondents completed the BWS experiment May-June 2023 with the Swait-Louviere test indicating that researchers and PHPs could be pooled (p = 0.512). Latent class analysis identified two classes, those highlighting "Harms" (n = 29) (prioritizing concerns about potential risk of legal prosecution, individual harm, and group stigma) and those highlighting "Utility" (n = 28) (prioritizing concerns about limited evidence, resource allocation, non-disclosure of data use for HIV ME, and the potential to infer the directionality of HIV transmission). There were no differences in the characteristics of members across classes.

CONCLUSIONS

The ethical issues of HIV ME vary in importance among stakeholders, reflecting different perspectives on the potential impact and usefulness of the data. Knowing these differences exist can directly inform the focus of future deliberations about the policies and practices of HIV ME in the United States.

Checklist for studies of HIV drug resistance prevalence or incidence: rationale and recommended use

HIV drug resistance (HIVDR) is a major challenge to the effectiveness of antiretroviral therapy. Global efforts in addressing HIVDR require clear, transparent, and replicable reporting in HIVDR studies. We describe the rationale and recommended use of a checklist that should be included in reports of HIVDR incidence and prevalence. After preliminary consultations with experts on HIVDR and establishing the need for guidance on HIVDR reporting, we used a sequential, explanatory, mixed methods approach to create the checklist; together with the accompanying articles, the checklist was reviewed by the authors and validated externally. The checklist for studies on HIVDR prevalence or incidence (CEDRIC-HIV) includes 15 recommended items that would enhance transparency and facilitate interpretation, comparability, and replicability of HIVDR studies. CEDRIC-HIV will help authors of HIVDR studies prepare research reports and assist reviewers and editors in assessments of completeness of reporting. The checklist will also facilitate statistical pooling and interpretation of HIVDR data.

Recommendations on data sharing in HIV drug resistance research

 • Human immunodeficiency virus (HIV) drug resistance has implications for antiretroviral treatment strategies and for containing the HIV pandemic because the development of HIV drug resistance leads to the requirement for antiretroviral drugs that may be less effective, less well-tolerated, and more expensive than those used in first-line regimens.  • HIV drug resistance studies are designed to determine which HIV mutations are selected by antiretroviral drugs and, in turn, how these mutations affect antiretroviral drug susceptibility and response to future antiretroviral treatment regimens.  • Such studies collectively form a vital knowledge base essential for monitoring global HIV drug resistance trends, interpreting HIV genotypic tests, and updating HIV treatment guidelines.  • Although HIV drug resistance data are collected in many studies, such data are often not publicly shared, prompting the need to recommend best practices to encourage and standardize HIV drug resistance data sharing.  • In contrast to other viruses, sharing HIV sequences from phylogenetic studies of transmission dynamics requires additional precautions as HIV transmission is criminalized in many countries and regions.  • Our recommendations are designed to ensure that the data that contribute to HIV drug resistance knowledge will be available without undue hardship to those publishing HIV drug resistance studies and without risk to people living with HIV.

Lessons learned from community engagement regarding phylodynamic research with molecular HIV surveillance data

INTRODUCTION

The widespread implementation of molecular HIV surveillance (MHS) has resulted in an increased discussion about the ethical, human rights and public health implications of MHS. We narrate our process of pausing our research that uses data collected through MHS in response to these growing concerns and summarize the key lessons we learned through conversations with community members.

METHODS

The original study aimed to describe HIV transmission patterns by age and race/ethnicity among men who have sex with men in King County, Washington, by applying probabilistic phylodynamic modelling methods to HIV-1 pol gene sequences collected through MHS. In September 2020, we paused the publication of this research to conduct community engagement: we held two public-facing online presentations, met with a national community coalition that included representatives of networks of people living with HIV, and invited two members of this coalition to provide feedback on our manuscript. During each of these meetings, we shared a brief presentation of our methods and findings and explicitly solicited feedback on the perceived public health benefit and potential harm of our analyses and results.

RESULTS

Some community concerns about MHS in public health practice also apply to research using MHS data, namely those related to informed consent, inference of transmission directionality and criminalization. Other critiques were specific to our research study and included feedback about the use of phylogenetic analyses to study assortativity by race/ethnicity and the importance of considering the broader context of stigma and structural racism. We ultimately decided the potential harms of publishing our study-perpetuating racialized stigma about men who have sex with men and eroding the trust between phylogenetics researchers and communities of people living with HIV-outweighed the potential benefits.

CONCLUSIONS

HIV phylogenetics research using data collected through MHS data is a powerful scientific technology with the potential to benefit and harm communities of people living with HIV. Addressing criminalization and including people living with HIV in decision-making processes have the potential to meaningfully address community concerns and strengthen the ethical justification for using MHS data in both research and public health practice. We close with specific opportunities for action and advocacy by researchers.

Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities

The rapid implementation of molecular HIV surveillance (MHS) has resulted in significant challenges for local health departments to develop real-time cluster detection and response (CDR) interventions for priority populations impacted by HIV. This study is among the first to explore professionals' strategies to implement MHS and develop CDR interventions in real-world public health settings. Methods: Semi-structured qualitative interviews were completed by 21 public health stakeholders in the United States' southern and midwestern regions throughout 2020-2022 to identify themes related to the implementation and development of MHS and CDR. Results for the thematic analysis revealed (1) strengths and limitations in utilizing HIV surveillance data for real-time CDR; (2) limitations of MHS data due to medical provider and staff concerns related to CDR; (3) divergent perspectives on the effectiveness of partner services; (4) optimism, but reluctance about the social network strategy; and (5) enhanced partnerships with community stakeholders to address MHS-related concerns. Conclusions: Enhancing MHS and CDR efforts requires a centralized system for staff to access public health data from multiple databases to develop CDR interventions; designating staff dedicated to CDR interventions; and establishing equitable meaningful partnerships with local community stakeholders to address MHS concerns and develop culturally informed CDR interventions.

Community Insights in Phylogenetic HIV Research: The CIPHR Project Protocol

Inferring HIV transmission networks from HIV sequences is gaining popularity in the field of HIV molecular epidemiology. However, HIV sequences are often analyzed at distance from those affected by HIV epidemics, namely without the involvement of communities most affected by HIV. These remote analyses often mean that knowledge is generated in absence of lived experiences and socio-economic realities that could inform the ethical application of network-derived information in 'real world' programmes. Procedures to engage communities are noticeably absent from the HIV molecular epidemiology literature. Here we present our team's protocol for engaging community activists living in Nairobi, Kenya in a knowledge exchange process - The CIPHR Project (Community Insights in Phylogenetic HIV Research). Drawing upon a community-based participatory approach, our team will (1) explore the possibilities and limitations of HIV molecular epidemiology for key population programmes, (2) pilot a community-based HIV molecular study, and (3) co-develop policy guidelines on conducting ethically safe HIV molecular epidemiology. Critical dialogue with activist communities will offer insight into the potential uses and abuses of using such information to sharpen HIV prevention programmes. The outcome of this process holds importance to the development of policy frameworks that will guide the next generation of the global response.

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

Background: Molecular epidemiological approaches provide opportunities to characterize HIV transmission dynamics. We analyzed HIV sequences and virus load (VL) results obtained during routine clinical care, and individual’s zip-code location to determine utility of this approach. Methods: HIV-1 pol sequences aligned using ClustalW were subtyped using REGA. A maximum likelihood (ML) tree was generated using IQTree. Transmission clusters with ≤3% genetic distance (GD) and ≥90% bootstrap support were identified using ClusterPicker. We conducted Bayesian analysis using BEAST to confirm transmission clusters. The proportion of nucleotides with ambiguity ≤0.5% was considered indicative of early infection. Descriptive statistics were applied to characterize clusters and group comparisons were performed using chi-square or t-test. Results: Among 2775 adults with data from 2014−2015, 2589 (93%) had subtype B HIV-1, mean age was 44 years (SD 12.7), 66.4% were male, and 25% had nucleotide ambiguity ≤0.5. There were 456 individuals in 193 clusters: 149 dyads, 32 triads, and 12 groups with ≥ four individuals per cluster. More commonly in clusters were males than females, 349 (76.5%) vs. 107 (23.5%), p < 0.0001; younger individuals, 35.3 years (SD 12.1) vs. 44.7 (SD 12.3), p < 0.0001; and those with early HIV-1 infection by nucleotide ambiguity, 202/456 (44.3%) vs. 442/2133 (20.7%), p < 0.0001. Members of 43/193 (22.3%) of clusters included individuals in different jurisdictions. Clusters ≥ four individuals were similarly found using BEAST. HIV-1 viral load (VL) ≥3.0 log10 c/mL was most common among individuals in clusters ≥ four, 18/21, (85.7%) compared to 137/208 (65.8%) in clusters sized 2−3, and 927/1169 (79.3%) who were not in a cluster (p < 0.0001). Discussion: HIV sequence data obtained for HIV clinical management provide insights into regional transmission dynamics. Our findings demonstrate the additional utility of HIV-1 VL data in combination with phylogenetic inferences as an enhanced contact tracing tool to direct HIV treatment and prevention services. Trans-jurisdictional approaches are needed to optimize efforts to end the HIV epidemic.

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

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

Traversing missing links in the spread of HIV

Combining clinical and genetic data can improve the effectiveness of virus tracking with the aim of reducing the number of HIV cases by 2030.

Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification

To identify and stop active HIV transmission chains new epidemiological techniques are needed. Here, we describe the development of a multi-biomarker augmentation to phylogenetic inference of the underlying transmission history in a local population. HIV biomarkers are measurable biological quantities that have some relationship to the amount of time someone has been infected with HIV. To train our model, we used five biomarkers based on real data from serological assays, HIV sequence data, and target cell counts in longitudinally followed, untreated patients with known infection times. The biomarkers were modeled with a mixed effects framework to allow for patient specific variation and general trends, and fit to patient data using Markov Chain Monte Carlo (MCMC) methods. Subsequently, the density of the unobserved infection time conditional on observed biomarkers were obtained by integrating out the random effects from the model fit. This probabilistic information about infection times was incorporated into the likelihood function for the transmission history and phylogenetic tree reconstruction, informed by the HIV sequence data. To critically test our methodology, we developed a coalescent-based simulation framework that generates phylogenies and biomarkers given a specific or general transmission history. Testing on many epidemiological scenarios showed that biomarker augmented phylogenetics can reach 90% accuracy under idealized situations. Under realistic within-host HIV-1 evolution, involving substantial within-host diversification and frequent transmission of multiple lineages, the average accuracy was at about 50% in transmission clusters involving 5-50 hosts. Realistic biomarker data added on average 16 percentage points over using the phylogeny alone. Using more biomarkers improved the performance. Shorter temporal spacing between transmission events and increased transmission heterogeneity reduced reconstruction accuracy, but larger clusters were not harder to get right. More sequence data per infected host also improved accuracy. We show that the method is robust to incomplete sampling and that adding biomarkers improves reconstructions of real HIV-1 transmission histories. The technology presented here could allow for better prevention programs by providing data for locally informed and tailored strategies.

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

ABSTRACT

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

Past dynamics of HIV transmission among men who have sex with men in Montréal, Canada: a mathematical modeling study

BACKGROUND

Gay, bisexual, and other men who have sex with men (gbMSM) experience disproportionate risks of HIV acquisition and transmission. In 2017, Montréal became the first Canadian Fast-Track City, setting the 2030 goal of zero new HIV infections. To inform local elimination efforts, we estimate the evolving role of prevention and sexual behaviours on HIV transmission dynamics among gbMSM in Montréal between 1975 and 2019.

METHODS

Data from local bio-behavioural surveys were analyzed to develop, parameterize, and calibrate an agent-based model of sexual HIV transmission. Partnership dynamics, HIV's natural history, and treatment and prevention strategies were considered. The model simulations were analyzed to estimate the fraction of HIV acquisitions and transmissions attributable to specific groups, with a focus on age, sexual partnering level, and gaps in the HIV care-continuum.

RESULTS

The model-estimated HIV incidence peaked in 1985 (2.3 per 100 person years (PY); 90% CrI: 1.4-2.9 per 100 PY) and decreased to 0.1 per 100 PY (90% CrI: 0.04-0.3 per 100 PY) in 2019. Between 2000-2017, the majority of HIV acquisitions and transmissions occurred among men aged 25-44 years, and men aged 35-44 thereafter. The unmet prevention needs of men with > 10 annual anal sex partners contributed 90-93% of transmissions and 67-73% of acquisitions annually. The primary stage of HIV played an increasing role over time, contributing to 11-22% of annual transmissions over 2000-2019. In 2019, approximately 70% of transmission events occurred from men who had discontinued, or never initiated antiretroviral therapy.

CONCLUSIONS

The evolving HIV landscape has contributed to the declining HIV incidence among gbMSM in Montréal. The shifting dynamics identified in this study highlight the need for continued population-level surveillance to identify gaps in the HIV care continuum and core groups on which to prioritize elimination efforts.

Beyond criminalization: reconsidering HIV criminalization in an era of reform

PURPOSE OF REVIEW

This paper reviews recent studies examining the application of human immunodeficiency virus (HIV)-specific criminal laws in North America (particularly the United States and Canada). In the wake of the development of new biomedical prevention strategies, many states in the United States (US) have recently begun to reform or repeal their HIV-specific laws. These findings can help inform efforts to 'modernize' HIV laws (or, to revise in ways that reflect recent scientific advances in HIV treatment and prevention).

RECENT FINDINGS

Recent studies suggest that HIV-specific laws disproportionately impact Black men, white women, and Black women. The media sensationally covers criminal trials under these laws, especially when they involve Black defendants who they often describe in racialized terms as predators. Activists contest these laws and raise concerns about new phylogenetic HIV surveillance techniques that have the potential to be harnessed for law enforcement purposes.

SUMMARY

These findings collectively raise urgent concerns for the continued use of HIV-specific criminal laws. These policies disproportionately impact marginalized groups - particularly Black men. Media coverage of these cases often helps to spread misinformation and stigmatizing rhetoric about people living with HIV and promulgate racist stereotypes. Although well-intentioned, new phylogenetic HIV surveillance technologies have the potential to exacerbate these issues if law enforcement is able to gain access to these public health tools.

Primary case inference in viral outbreaks through analysis of intra-host variant population

Background

Investigation of outbreaks to identify the primary case is crucial for the interruption and prevention of transmission of infectious diseases. These individuals may have a higher risk of participating in near future transmission events when compared to the other patients in the outbreak, so directing more transmission prevention resources towards these individuals is a priority. Although the genetic characterization of intra-host viral populations can aid the identification of transmission clusters, it is not trivial to determine the directionality of transmissions during outbreaks, owing to complexity of viral evolution. Here, we present a new computational framework, PYCIVO: primary case inference in viral outbreaks. This framework expands upon our earlier work in development of QUENTIN, which builds a probabilistic disease transmission tree based on simulation of evolution of intra-host hepatitis C virus (HCV) variants between cases involved in direct transmission during an outbreak. PYCIVO improves upon QUENTIN by also adding a custom heterogeneity index and identifying the scenario when the primary case may have not been sampled.

Results

These approaches were validated using a set of 105 sequence samples from 11 distinct HCV transmission clusters identified during outbreak investigations, in which the primary case was epidemiologically verified. Both models can detect the correct primary case in 9 out of 11 transmission clusters (81.8%). However, while QUENTIN issues erroneous predictions on the remaining 2 transmission clusters, PYCIVO issues a null output for these clusters, giving it an effective prediction accuracy of 100%. To further evaluate accuracy of the inference, we created 10 modified transmission clusters in which the primary case had been removed. In this scenario, PYCIVO was able to correctly identify that there was no primary case in 8/10 (80%) of these modified clusters. This model was validated with HCV; however, this approach may be applicable to other microbial pathogens.

Conclusions

PYCIVO improves upon QUENTIN by also implementing a custom heterogeneity index which empowers PYCIVO to make the important ‘No primary case’ prediction. One or more samples, possibly including the primary case, may have not been sampled, and this designation is meant to account for these scenarios.

Transmission of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) from pre and asymptomatic infected individuals: a systematic review

BACKGROUND

The role of SARS-Cov-2-infected persons who develop symptoms after testing (presymptomatics) or not at all (asymptomatics) in the pandemic spread is unknown.

OBJECTIVES

To determine infectiousness and probable contribution of asymptomatic persons (at the time of testing) to pandemic SARS-CoV-2 spread.

DATA SOURCES

LitCovid, medRxiv, Google Scholar, and WHO Covid-19 databases (to 31 March 2021) and references in included studies.

STUDY ELIGIBILITY CRITERIA

Studies with a proven or hypothesized transmission chain based either on serial PCR cycle threshold readings and/or viral culture and/or gene sequencing, with adequate follow-up.

PARTICIPANTS

People exposed to SARS-CoV-2 within 2-14 days to index asymptomatic (at time of observation) infected individuals.

INTERVENTIONS

Reliability of symptom and signs was assessed within contemporary knowledge; transmission likelihood was assessed using adapted causality criteria.

METHODS

Systematic review. We contacted all included studies' corresponding authors requesting further details.

RESULTS

We included 18 studies from a diverse setting with substantial methodological variation (this field lacks standardized methodology). At initial testing, prevalence of asymptomatic cases was 12.5-100%. Of these, 6-100% were later determined to be presymptomatic, this proportion varying according to setting, methods of case ascertainment and population. Nursing/care home facilities reported high rates of presymptomatic: 50-100% (n = 3 studies). Fourteen studies were classified as high risk of, and four studies as at moderate risk of symptom ascertainment bias. High-risk studies may be less likely to distinguish between presymptomatic and asymptomatic cases. Six asymptomatic studies and four presymptomatic studies reported culturing infectious virus; data were too sparse to determine infectiousness duration. Three studies provided evidence of possible and three of probable/likely asymptomatic transmission; five studies provided possible and two probable/likely presymptomatic SARS-CoV-2 transmission.

CONCLUSION

High-quality studies provide probable evidence of SARS-CoV-2 transmission from presymptomatic and asymptomatic individuals, with highly variable estimated transmission rates.

Phylogenetic and Drug-Resistance Analysis of HIV-1 Sequences From an Extensive Paediatric HIV-1 Outbreak in Larkana, Pakistan

Introduction

In April 2019, an HIV-1 outbreak among children occurred in Larkana, Pakistan, affecting more than a thousand children. It was assumed that the outbreak originated from a single source, namely a doctor at a private health facility. In this study, we performed subtype distribution, phylogenetic and drug-resistance analysis of HIV-1 sequences from 2019 outbreak in Larkana, Pakistan.

Methods

A total of 401 blood samples were collected between April–June 2019, from children infected with HIV-1 aged 0–15 years recruited into a case-control study to investigate the risk factors for HIV-1 transmission. Partial HIV-1 pol sequences were generated from 344 blood plasma samples to determine HIV-1 subtype and drug resistance mutations (DRM). Maximum-likelihood phylogenetics based on outbreak and reference sequences was used to identify transmission clusters and assess the relationship between outbreak and key population sequences between and within the determined clusters. Bayesian analysis was employed to identify the time to the most recent common recent ancestor (tMRCA) of the main Pakistani clusters.

Results

The HIV-1 circulating recombinant form (CRF) 02_AG and subtype A1 were most common among the outbreak sequences. Of the treatment-naïve participants, the two most common mutations were RT: E138A (8%) and RT: K219Q (8%). Four supported clusters within the outbreak were identified, and the median tMRCAs of the Larkana outbreak sequences were estimated to 2016 for both the CRF02_AG and the subtype A1 clusters. Furthermore, outbreak sequences exhibited no phylogenetic mixing with sequences from other high-risk groups of Pakistan.

Conclusion

The presence of multiple clusters indicated a multi-source outbreak, rather than a single source outbreak from a single health practitioner as previously suggested. The multiple introductions were likely a consequence of ongoing transmission within the high-risk groups of Larkana, and it is possible that the so-called Larkana strain was introduced into the general population through poor infection prevention control practices in healthcare settings. The study highlights the need to scale up HIV-1 prevention programmes among key population groups and improving infection prevention control in Pakistan.

Characterization of HIV Risk Behaviors and Clusters Using HIV-Transmission Cluster Engine Among a Cohort of Persons Living with HIV in Washington, DC

Molecular epidemiology (ME) is one tool used to end the HIV epidemic in the United States. We combined clinical and behavioral data with HIV sequence data to identify any overlap in clusters generated from different sequence datasets; to characterize HIV transmission clusters; and to identify correlates of clustering among people living with HIV (PLWH) in Washington, District of Columbia (DC). First, Sanger sequences from DC Cohort participants, a longitudinal HIV study, were combined with next-generation sequences (NGS) from participants in a ME substudy to identify clusters. Next, demographic and self-reported behavioral data from ME substudy participants were used to identify risks of secondary transmission. Finally, we combined NGS from ME substudy participants with Sanger sequences in the DC Molecular HIV Surveillance database to identify clusters. Cluster analyses used HIV-Transmission Cluster Engine to identify linked pairs of sequences (defined as distance ≤1.5%). Twenty-eight clusters of ≥3 sequences (size range: 3-12) representing 108 (3%) participants were identified. None of the five largest clusters (size range: 5-12) included newly diagnosed PLWH. Thirty-four percent of ME substudy participants (n = 213) reported condomless sex during their last sexual encounter and 14% reported a Syphilis diagnosis in the past year. Seven transmission clusters (size range: 2-19) were identified in the final analysis, each containing at least one ME substudy participant. Substudy participants in clusters from the third analysis were present in clusters from the first analysis. Combining HIV sequence, clinical and behavioral data provided insights into HIV transmission that may not be identified using traditional epidemiological methods alone. Specifically, the sexual risk behaviors and STI diagnoses reported in the substudy survey may not have been disclosed during Partner Services activities and the survey data complemented clinical data to fully characterize transmission clusters. These findings can be used to enhance local efforts to interrupt transmission and avert new infections.

Considerations for an integrated population health databank in Africa: lessons from global best practices

Background: The rising digitisation and proliferation of data sources and repositories cannot be ignored. This trend expands opportunities to integrate and share population health data. Such platforms have many benefits, including the potential to efficiently translate information arising from such data to evidence needed to address complex global health challenges. There are pockets of quality data on the continent that may benefit from greater integration. Integration of data sources is however under-explored in Africa. The aim of this article is to identify the requirements and provide practical recommendations for developing a multi-consortia public and population health data-sharing framework for Africa. Methods: We conducted a narrative review of global best practices and policies on data sharing and its optimisation. We searched eight databases for publications and undertook an iterative snowballing search of articles cited in the identified publications. The Leximancer software © enabled content analysis and selection of a sample of the most relevant articles for detailed review. Themes were developed through immersion in the extracts of selected articles using inductive thematic analysis. We also performed interviews with public and population health stakeholders in Africa to gather their experiences, perceptions, and expectations of data sharing. Results: Our findings described global stakeholder experiences on research data sharing. We identified some challenges and measures to harness available resources and incentivise data sharing.  We further highlight progress made by the different groups in Africa and identified the infrastructural requirements and considerations when implementing data sharing platforms. Furthermore, the review suggests key reforms required, particularly in the areas of consenting, privacy protection, data ownership, governance, and data access. Conclusions: The findings underscore the critical role of inclusion, social justice, public good, data security, accountability, legislation, reciprocity, and mutual respect in developing a responsive, ethical, durable, and integrated research data sharing ecosystem.

HIV-1 Transmission linkages among persons with incident infection to inform public health surveillance

BACKGROUND

We evaluated features of HIV transmission networks involving persons diagnosed during incident HIV infection (IHI) to assess network-based opportunities to curtail onward transmission.

METHODS

Transmission networks were constructed using partial pol sequences reported to North Carolina surveillance among persons with recent (2014-2018) and past (<2014) HIV diagnoses. IHI were defined as documented acute infections or seroconversion. Demographic and virologic features of HIV genetic clusters (<1.5% pairwise genetic distance) involving ≥ 1 IHI were assessed. Persons with viral genetic links and who had diagnoses >90 days prior to an IHI were further characterized. We assessed named partner outcomes among IHI index persons using contact tracing data.

FINDINGS

Of 4,405 HIV diagnoses 2014-2018 with sequences, there were 323 (7%) IHI index persons; most were male (88%), Black (65%), young (68% <30 years), and reported sex with men (MSM) risk (79%). Index persons were more likely to be cluster members compared to non-index persons diagnosed during the same period (72% vs. 49%). In total, 162 clusters were identified involving 233 IHI, 577 recent diagnoses, and 163 past diagnoses. Most IHI cases (53%) had viral linkages to ≥1 previously diagnosed person without evidence of HIV viral suppression in the year prior to the diagnosis of the IHI index. In contact tracing, only 53% IHI cases named an HIV-positive contact, resulting in 0.5 previously diagnosed persons detected per IHI investigated. When combined with viral analyses, the detection rate of viremic previously diagnosed persons increased to 1.3.

INTERPRETATION

Integrating public health with molecular epidemiology, revealed that more than half of IHI have viral links to persons with previously diagnosed unsuppressed HIV infection which was largely unrecognized by traditional contact tracing. Enhanced partner services to support engagement and retention in HIV care and improved case finding supported by rapid phylogenetic analysis are tools to substantially reduce onward HIV transmission.

Molecular epidemiology in the HIV and SARS-CoV-2 pandemics

PURPOSE OF REVIEW

The aim of this review was to compare and contrast the application of molecular epidemiology approaches for the improved management and understanding of the HIV versus SARS-CoV-2 epidemics.

RECENT FINDINGS

Molecular biology approaches, including PCR and whole genome sequencing (WGS), have become powerful tools for epidemiological investigation. PCR approaches form the basis for many high-sensitivity diagnostic tests and can supplement traditional contact tracing and surveillance strategies to define risk networks and transmission patterns. WGS approaches can further define the causative agents of disease, trace the origins of the pathogen, and clarify routes of transmission. When coupled with clinical datasets, such as electronic medical record data, these approaches can investigate co-correlates of disease and pathogenesis. In the ongoing HIV epidemic, these approaches have been effectively deployed to identify treatment gaps, transmission clusters and risk factors, though significant barriers to rapid or real-time implementation remain critical to overcome. Likewise, these approaches have been successful in addressing some questions of SARS-CoV-2 transmission and pathogenesis, but the nature and rapid spread of the virus have posed additional challenges.

SUMMARY

Overall, molecular epidemiology approaches offer unique advantages and challenges that complement traditional epidemiological tools for the improved understanding and management of epidemics.

Transparency, trust, and community welfare: towards a precision public health ethics framework for the genomics era

Infectious disease control is experiencing a paradigm shift, as pathogen sequencing technologies and digital applications are increasingly implemented for control of diseases such as tuberculosis, Ebola, and COVID-19. A new ethical framework should be a critical part of this emerging paradigm to ensure that the benefit of precision public health interventions based on advances in genomics research is not outweighed by the risks they pose to individuals, families, and vulnerable segments of the population. We suggest that the ethical framework guiding practice in this domain combines standard precepts from public health ethics with emerging ethics principles from precision medicine.

What Should Health Departments Do with HIV Sequence Data?

Many countries and US states have mandatory statues that require reporting of HIV clinical data including genetic sequencing results to the public health departments. Because genetic sequencing is a part of routine care for HIV infected persons, health departments have extensive sequence collections spanning years and even decades of the HIV epidemic. How should these data be used (or not) in public health practice? This is a complex, multi-faceted question that weighs personal risks against public health benefit. The answer is neither straightforward nor universal. However, to make that judgement—of how genetic sequence data should be used in describing and combating the HIV epidemic—we need a clear image of what a phylogenetically enhanced HIV surveillance system can do and what benefit it might provide. In this paper, we present a positive case for how up-to-date analysis of HIV sequence databases managed by health departments can provide unique and actionable information of how HIV is spreading in local communities. We discuss this question broadly, with examples from the US, as it is globally relevant for all health authorities that collect HIV genetic data.