Connecting the dots: network data and models in HIV epidemiology

Interpreting the Epidemiological Characteristics of HIV-1 in Heterosexually Transmitted Population Based on Molecular Transmission Network in Kunming, Yunnan: A Retrospective Cohort Study

Heterosexuals have become the most prevalent group of HIV-1 in Kunming, Yunnan Province. Utilizing the principle of genetic similarity between their gene sequences, we built a molecular transmission network by gathering data from earlier molecular epidemiological studies. This allowed us to analyze the epidemiological features of this group and offer fresh concepts and approaches for the prevention and management of HIV-1 epidemics. Cytoscope was used to visualize and characterize the network following the processing of the sample gene sequences by BioEdit and HyPhy. The number of possible links and the size of the clusters were investigated as influencing factors using a zero-inflated Poisson model and a logistic regression model, respectively. A scikit-learn-based prediction model was developed to account for the dynamic changes in the HIV-1 molecular network. Six noteworthy modular clusters with network scores ranging from 4 to 9 were found from 150 clusters using Molecular Complex Detection analysis at a standard genetic distance threshold of 0.01. The size of the number of possible links and the network's clustering rate were significantly impacted by sampling time, marital status, and CD4+ T lymphocytes (all p < 0.05). The gradient boosting machine (GBM) model had the highest area under the curve value, 0.884 ± 0.051, according to scikit-learn. Though not all cluster subtypes grew equally, the network clusters were relatively specific and aggregated. The largest local transmission-risk group for HIV-1CRF08_BC is now the heterosexual transmission population. The most suitable model for constructing the HIV-1 molecular network dynamics prediction model was found to be the GBM model.

Using molecular transmission networks to understand the epidemic characteristics of HIV-1 CRF08_BC across China

HIV-1 CRF08_BC has become a major epidemic in heterosexuals and intravenous drug users (IDUs) in southern China. In order to evaluate the trends of its epidemic and facilitate targeted HIV prevention, we constructed the genetic transmission networks based on its pol sequences, derived from the National HIV Molecular Epidemiology Survey. Through retrospective network analysis, to study the epidemiological and demographic correlations with the transmission network. Of the 1,829 study subjects, 639 (34.9%) were clustered in 151 transmission networks. Factors associated with increased clustering include IDUs, heterosexual men, young adults and people with lower education (P < 0.05 for all). The IDUs, MSM, young adult and person with low education had more potential transmission links as well (P < 0.05 for all). The most crossover links were found between heterosexual women and IDUs, with 30.9% heterosexual women linked to IDUs. The crossover links heterosexual women were mainly those with middle age and single (P < 0.001). This study indicated that the HIV-1 CRF08_BC epidemic was still on going in China with more than one third of the infected people clustered in the transmission networks. Meanwhile, the study could help identify the active CRF08_BC spreader in the local community and greatly facilitate précising AIDS prevention with targeted intervention.

Challenges and Controversies in COVID-19: Masking the General Population may Attenuate This Pandemic's Outbreak

SARS-CoV-2, the virus that causes COVID-19, spreads i. a., by respiratory droplets. The use of masks in preventing spread is controversial; masks are considered useless by many, while being mandated in some locations. Here, the effect of masking the general population on a COVID-19-like epidemic is estimated by computer simulation using three separate types of software. The main questions are whether mask use by the general population can limit the spread of SARS-CoV-2 in a country and how to identify opportunities when mask use is cost-effective and safe. To address these questions, the protective effects of different types of masks, the side-effects of masks, and avenues for improvements of masks and masking are addressed. Main results: (i) Any type of mask, even simple home-made ones, may be of value, even if the protective effect of each mask (here dubbed "one mask-protection") is low. Strict adherence to mask use does not appear to be critical but increasing one mask-protection to >50% was found to be advantageous. (ii) Masks do seem to reduce the number of new cases even if introduced at a late stage in an epidemic, but early implementation helps reduce the cumulative and total number of cases. (iii) The simulations suggest that it might be possible to eliminate a COVID-19 outbreak by widespread mask use during a limited period. There is a brief discussion of why the reported effect size of masking varies widely, and is expected to do so, because of different filtration abilities of different masks, differences in compliance and fitting, other routes of transmission, pre-existing immunity, and because a system of interconnected, disease-prone individuals has non-linear properties. A software solution to visualize infection spread is presented. The results from these simulations are encouraging, but do not necessarily represent the real-life situation, so it is suggested that clinical trials of masks are now carried out while continuously monitoring effects and side-effects. As mask use is not without risks and costs, it is suggested that governments and scientists have an important role in advising the public about the sensible use of masks.

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.

HIV-1 molecular transmission network among sexually transmitted populations in Liaoning Province, China

INTRODUCTION

In recent years, with the development of molecular epidemiology, molecular transmission networks based on evolutionary theory and sequence analysis have been widely used in research on human immunodeficiency virus (HIV)-1 transmission dynamics and precise intervention for high-risk populations. The HIV-1 molecular transmission network is a new method to study the population's access to the network, the characteristics of clustering, and the characteristics of interconnection in the network. Here, we analyzed the characteristics of the HIV-1 molecular transmission network of sexually transmitted people in Liaoning Province.

METHODS

A study of HIV-infected persons who were sexually transmitted in Liaoning Province from 2003 to 2019. HIV-1 RNA was extracted, amplified and sequenced, and a phylogenetic tree was constructed to determine the subtype using the well matched pol gene region sequence. The gene distance between sequences was calculated, the threshold was determined, and the molecular transmission network was constructed.

RESULTS

109 samples of pol gene region were obtained. The main subtype of HIV-1 was CRF01_AE, followed by B, CRF07_BC, etc. 12.8% of them were resistant to HIV. At the threshold of 0.55 gene distance, 60.6% of them entered the HIV-1 molecular transmission network. Workers, sample source voluntary counseling and testing, other testing, subtype B and drug resistance are the factors influencing the access to HIV-1 molecular transmission network. The subtype of CRF01_AE formed 6 clusters in the molecular transmission network. In the network, the difference of connection degree between different subtypes was statistically significant.

DISCUSSION

The three subtypes CRF01_AE, CRF07_BC and B that enter the molecular transmission network do not have interconnections, and they form clusters with each other. It shows that the risk of transmission among the three subtypes is less than the risk of transmission within each subtype. The factors affecting HIV-1 entry into the molecular transmission network were occupation, sample source, genotype and drug resistance. The L33F mutation at the HIV-1 resistance mutation site constitutes the interconnection in the largest transmission cluster in the network. The epidemiological characteristics of HIV-infected persons in each molecular transmission cluster show that 97% of the study subjects come from the same area and have a certain spatial aggregation.

CONCLUSION

Constructing a molecular transmission network and conducting long-term monitoring, while taking targeted measures to block the spread of HIV can achieve precise prevention and control.

Temporal Variation in One-Time Partnership Rates Among Young Men Who Have Sex With Men and Transgender Women

BACKGROUND

Volatility in sexual contact rates has been recognized as an important factor influencing HIV transmission dynamics. One-time partnerships may be particularly important given the potential to quickly accumulate large number of contacts. Yet, empirical data documenting individual variation in contact rates remain rare. This study provides much needed data on temporal variation in one-time partners to better understand behavioral dynamics and improve the accuracy of transmission models.

METHODS

Data for this study were obtained from a longitudinal cohort study of young men who have sex with men and transgender women in Chicago. Participants provided sexual network data every 6 months for 2 years. A series of random effects models examined variation in one-time partnership rates and disaggregated within and between associations of exposure variables. Exposure variables included prior number of one-time partners, number of casual partners, and having a main partner.

RESULTS

Results indicated substantial between-person and within-person variation in one-time partners. Casual partnerships were positively associated and main partnerships negatively associated with one-time partnership rates. There remained a small positive association between prior one-time partnerships and the current number of one-time partnerships.

CONCLUSIONS

Despite the preponderance of a low number of one-time partners, substantial variation in one-time partnership rates exists among young men who have sex with men and transgender women. Accordingly, focusing on high contact rate individuals alone may be insufficient to identify periods of highest risk. Future studies should use these estimates to more accurately model how volatility impacts HIV transmission and better understand how this variation influences intervention effectiveness.

Factors Associated With Human Immunodeficiency Virus Infections Linked in Genetic Clusters But Disconnected in Partner Tracing

BACKGROUND

Successful partner notification can improve community-level outcomes by increasing the proportion of persons living with human immunodeficiency virus (HIV) who are linked to HIV care and virally suppressed, but it is resource intensive. Understanding where HIV transmission pathways may be undetected by routine partner notification may help improve case finding strategies.

METHODS

We combined partner notification interview and HIV sequence data for persons diagnosed with HIV in Wake County, NC in 2012 to 2013 to evaluate partner contact networks among persons with HIV pol gene sequences 2% or less pairwise genetic distance. We applied a set of multivariable generalized estimating equations to identify correlates of disparate membership in genetic versus partner contact networks.

RESULTS

In the multivariable model, being in a male-male pair (adjusted odds ratio [AOR], 16.7; P = 0.01), chronic HIV infection status (AOR, 4.5; P < 0.01), and increasing percent genetic distance between each dyad member's HIV pol gene sequence (AOR, 8.3 per each 1% increase, P < 0.01) were all associated with persons with HIV clustering but not being identified in the partner notification network component. Having anonymous partners or other factors typically associated with risk behavior were not associated.

CONCLUSIONS

Based on genetic networks, partnerships which may be stigmatized, may have occurred farther back in time or may have an intervening partner were more likely to be unobserved in the partner contact network. The HIV genetic cluster information contributes to public health understanding of HIV transmission networks in these settings where partner identifying information is not available.

Genetic transmission networks of HIV-1 CRF07_BC strain among HIV-1 infections with virologic failure of ART in a minority area of China: a population-based study

Background

The drug resistance and the virologic failure of antiretroviral therapy (ART) are quite severe in Liangshan. A better understanding of the virologic failure of ART and the HIV-1 transmission network dynamics is essential for the surveillance and prevention of HIV. Here, we analyzed the HIV-1 CRF07_BC strain genetic transmission networks and their associated factors among people living with HIV-1 (PLWH) who had virologic failure of ART by using close genetic links.

Methods

The drug-resistant mutations were determined using the Stanford University HIV Drug Resistance Database. HIV-1 pol genes sequences were used for phylogenetic and genotypic drug resistance analysis. The genetic transmission networks were performed by comparing sequences, constructing the phylogenetic tree, calculating the pairwise distance, and visualizing the network.

Results

A total of 1050 PLWH with CRF07_BC pol sequences were finally identified and included in the genetic transmission network analysis from 2016 to 2017. Of the 1050 CRF07_BC pol sequences, 346 (32.95%) fell into clusters at a genetic distance of 0.006, resulting in 137 clusters ranging in size from 2 to 40 individuals. Subjects who were widowed or divorced were less likely to form a genetic transmission network (adjusted OR: 0.50), while subjects who had shared a needle ≥ five times were more likely to form a network (adjusted OR: 1.88).

Conclusions

The genetic transmission networks revealed the complex transmission pattern, highlighting the urgent need for transmission monitoring of virologic failure of ART and selection of more effective therapeutic regimens to promote viral suppression.

Calibration of individual-based models to epidemiological data: A systematic review

Individual-based models (IBMs) informing public health policy should be calibrated to data and provide estimates of uncertainty. Two main components of model-calibration methods are the parameter-search strategy and the goodness-of-fit (GOF) measure; many options exist for each of these. This review provides an overview of calibration methods used in IBMs modelling infectious disease spread. We identified articles on PubMed employing simulation-based methods to calibrate IBMs informing public health policy in HIV, tuberculosis, and malaria epidemiology published between 1 January 2013 and 31 December 2018. Articles were included if models stored individual-specific information, and calibration involved comparing model output to population-level targets. We extracted information on parameter-search strategies, GOF measures, and model validation. The PubMed search identified 653 candidate articles, of which 84 met the review criteria. Of the included articles, 40 (48%) combined a quantitative GOF measure with an algorithmic parameter-search strategy–either an optimisation algorithm (14/40) or a sampling algorithm (26/40). These 40 articles varied widely in their choices of parameter-search strategies and GOF measures. For the remaining 44 (52%) articles, the parameter-search strategy could either not be identified (32/44) or was described as an informal, non-reproducible method (12/44). Of these 44 articles, the majority (25/44) were unclear about the GOF measure used; of the rest, only five quantitatively evaluated GOF. Only a minority of the included articles, 14 (17%) provided a rationale for their choice of model-calibration method. Model validation was reported in 31 (37%) articles. Reporting on calibration methods is far from optimal in epidemiological modelling studies of HIV, malaria and TB transmission dynamics. The adoption of better documented, algorithmic calibration methods could improve both reproducibility and the quality of inference in model-based epidemiology. There is a need for research comparing the performance of calibration methods to inform decisions about the parameter-search strategies and GOF measures.

Calibration—that is, “fitting” the model to data—is a crucial part of using mathematical models to better forecast and control the population-level spread of infectious diseases. Evidence that the mathematical model is well-calibrated improves confidence that the model provides a realistic picture of the consequences of health policy decisions. To make informed decisions, Policymakers need information about uncertainty: i.e., what is the range of likely outcomes (rather than just a single prediction). Thus, modellers should also strive to provide accurate measurements of uncertainty, both for their model parameters and for their predictions. This systematic review provides an overview of the methods used to calibrate individual-based models (IBMs) of the spread of HIV, malaria, and tuberculosis. We found that less than half of the reviewed articles used reproducible, non-subjective calibration methods. For the remaining articles, the method could either not be identified or was described as an informal, non-reproducible method. Only one-third of the articles obtained estimates of parameter uncertainty. We conclude that the adoption of better-documented, algorithmic calibration methods could improve both reproducibility and the quality of inference in model-based epidemiology.

Egocentric sexual networks of men who have sex with men in the United States: Results from the ARTnet study

In this paper, we present an overview and descriptive results from one of the first egocentric network studies of men who have sex with men (MSM) from across the United States: the ARTnet study. ARTnet was designed to support prevention research for human immunodeficiency virus (HIV) and other sexually transmitted infections (STIs) that are transmitted across partnership networks. ARTnet implemented a population-based egocentric network study design that sampled egos from the target population and asked them to report on the number, attributes, and timing of their sexual partnerships. Such data provide the foundation needed for parameterizing stochastic network models that are used for disease projection and intervention planning. ARTnet collected data online from 2017 to 2019, with a final sample of 4904 participants who reported on 16198 sexual partnerships. The aims of this paper were to characterize the joint distribution of three network parameters needed for modeling: degree distributions, assortative mixing, and partnership age, with heterogeneity by partnership type (main, casual and one-time), demography, and geography. Participants had an average of 1.19 currently active partnerships ("mean degree"), which was higher for casual partnerships (0.74) than main partnerships (0.45). The mean rate of one-time partnership acquisition was 0.16 per week (8.5 partners per year). Main partnerships lasted 272.5 weeks on average, while casual partnerships lasted 133.0 weeks. There was strong but heterogenous assortative mixing by race/ethnicity for all groups. The mean absolute age difference for all partnership types was 9.5 years, with main partners differing by 6.3 years compared to 10.8 years for casual partners. Our analysis suggests that MSM may be at sustained risk for HIV/STI acquisition and transmission through high network degree of sexual partnerships. The ARTnet network study provides a robust and reproducible foundation for understanding the dynamics of HIV/STI epidemiology among U.S. MSM and supporting the implementation science that seeks to address persistent challenges in HIV/STI prevention.

SimpactCyan 1.0: An Open-source Simulator for Individual-Based Models in HIV Epidemiology with R and Python Interfaces

SimpactCyan is an open-source simulator for individual-based models in HIV epidemiology. Its core algorithm is written in C++ for computational efficiency, while the R and Python interfaces aim to make the tool accessible to the fast-growing community of R and Python users. Transmission, treatment and prevention of HIV infections in dynamic sexual networks are simulated by discrete events. A generic “intervention” event allows model parameters to be changed over time, and can be used to model medical and behavioural HIV prevention programmes. First, we describe a more efficient variant of the modified Next Reaction Method that drives our continuous-time simulator. Next, we outline key built-in features and assumptions of individual-based models formulated in SimpactCyan, and provide code snippets for how to formulate, execute and analyse models in SimpactCyan through its R and Python interfaces. Lastly, we give two examples of applications in HIV epidemiology: the first demonstrates how the software can be used to estimate the impact of progressive changes to the eligibility criteria for HIV treatment on HIV incidence. The second example illustrates the use of SimpactCyan as a data-generating tool for assessing the performance of a phylodynamic inference framework.

Using Social Networks to Understand and Overcome Implementation Barriers in the Global HIV Response

BACKGROUND

Despite the development of several efficacious HIV prevention and treatment methods in the past 2 decades, HIV continues to spread globally. Uptake of interventions is nonrandomly distributed across populations. Such inequality is socially patterned and reinforced by homophily arising from both social selection (becoming friends with similar people) and influence (becoming similar to friends).

METHODS

We conducted a narrative review to describe how social network analysis methods-including egocentric, sociocentric, and respondent-driven sampling designs-provide tools to measure key populations, to understand how epidemics spread, and to evaluate intervention take-up.

RESULTS

Social network analysis-informed designs can improve intervention effectiveness by reaching otherwise inaccessible populations. They can also improve intervention efficiency by maximizing spillovers, through social ties, to at-risk but susceptible individuals. Social network analysis-informed designs thus have the potential to be both more effective and less unequal in their effects, compared with social network analysis-naïve approaches. Although social network analysis-informed designs are often resource-intensive, we believe they provide unique insights that can help reach those most in need of HIV prevention and treatment interventions.

CONCLUSION

Increased collection of social network data during both research and implementation work would provide important information to improve the roll-out of existing studies in the present and to inform the design of more data-efficient, social network analysis-informed interventions in the future. Doing so will improve the reach of interventions, especially to key populations, and to maximize intervention impact once delivered.

Individual and Network Factors Associated With Racial Disparities in HIV Among Young Men Who Have Sex With Men: Results From the RADAR Cohort Study

BACKGROUND

Individual sexual risk behaviors have failed to explain the observed racial disparity in HIV acquisition. To increase understanding of potential drivers in disparities, we assessed differences across individual, network, and social determinants.

METHODS

Data come from RADAR (N = 1015), a longitudinal cohort study of multilevel HIV-risk factors among young men who have sex with men (YMSM) aged 16-29 years in Chicago, IL. Data collection includes biological specimens; network data, including detailed information about social, sexual, and drug-use networks; and psychosocial characteristics of YMSM.

RESULTS

Compared to white YMSM (24.8%) and Hispanic YMSM (30.0%), black YMSM (33.9%) had a higher prevalence of both HIV (32%; P < 0.001) and rectal sexually transmitted infections (26.5%; P = 0.011) with no observed differences in pre-exposure prophylaxis use. Black YMSM reported lower rates of sexual risk behaviors and more lifetime HIV tests (P < 0.001) compared with all other YMSM; however, they were also significantly less likely to achieve viral suppression (P = 0.01). Black YMSM reported the highest rate of cannabis use (P = 0.03) as well as greater levels of stigma (P < 0.001), victimization (P = 0.04), trauma (P < 0.001), and childhood sexual abuse (P < 0.001). White YMSM reported higher rates of depression (P < 0.001) and alcohol use (P < 0.001). In network analyses, significant differences existed across network characteristics with black YMSM having the lowest transitivity (P = 0.002), the highest density (P < 0.001), and the highest homophily (P < 0.001).

CONCLUSIONS

Black YMSM do not report higher rates of HIV-risk behaviors, but social and network determinants are aligned toward increased HIV risk. These results suggest that network interventions and those addressing social determinants may help reduce disparities.

Leveraging Phylogenetics to Understand HIV Transmission and Partner Notification Networks

BACKGROUND

Partner notification is an important component of public health test and treat interventions. To enhance this essential function, we assessed the potential for molecular methods to supplement routine partner notification and corroborate HIV networks.

METHODS

All persons diagnosed with HIV infection in Wake County, NC, during 2012-2013 and their disclosed sexual partners were included in a sexual network. A data set containing HIV-1 pol sequences collected in NC during 1997-2014 from 15,246 persons was matched to HIV-positive persons in the network and used to identify putative transmission clusters. Both networks were compared.

RESULTS

The partner notification network comprised 280 index cases and 383 sexual partners and high-risk social contacts (n = 131 HIV-positive). Of the 411 HIV-positive persons in the partner notification network, 181 (44%) did not match to a HIV sequence, 61 (15%) had sequences but were not identified in a transmission cluster, and 169 (41%) were identified in a transmission cluster. More than half (59%) of transmission clusters bridged sexual network partnerships that were not recognized in the partner notification; most of these clusters were dominated by men who have sex with men.

CONCLUSIONS

Partner notification and HIV sequence analysis provide complementary representations of the existent partnerships underlying the HIV transmission network. The partner notification network components were bridged by transmission clusters, particularly among components dominated by men who have sex with men. Supplementing the partner notification network with phylogenetic data highlighted avenues for intervention.

Modelling microbial infection to address global health challenges

The continued growth of the world’s population and increased interconnectivity heighten the risk that infectious diseases pose for human health worldwide. Epidemiological modelling is a tool that can be used to mitigate this risk by predicting disease spread or quantifying the impact of different intervention strategies on disease transmission dynamics. We illustrate how four decades of methodological advances and improved data quality have facilitated the contribution of modelling to address global health challenges, exemplified by models for the HIV crisis, emerging pathogens and pandemic preparedness. Throughout, we discuss the importance of designing a model that is appropriate to the research question and the available data. We highlight pitfalls that can arise in model development, validation and interpretation. Close collaboration between empiricists and modellers continues to improve the accuracy of predictions and the optimization of models for public health decision-making.

Social Networks of Substance-Using Populations: Key Issues and Promising New Approaches for HIV

PURPOSE OF REVIEW

This paper presents recent literature on substance using networks and HIV, highlighting renewed and emerging themes in the field. The goal is to draw attention to research that holds considerable promise for advancing our understanding of the role of networks in shaping behaviors, while also providing critical information for the development of interventions, programs, and policies to reduce HIV and other drug-related harms.

RECENT FINDINGS

Recent research advances our understanding of networks and HIV, including among understudied populations, and provides new insight into how risk environments shape the networks and health of substance-using populations. In particular, the integration of network approaches with molecular epidemiology, research on space and place, and intervention methods provides exciting new avenues of investigation. Continued advances in network research are critical to supporting the health and rights of substance-using populations and ensuring the development of high-impact HIV programs and policies.

Molecular Analysis of Human Immunodeficiency Virus Type 1 (HIV-1)-Infected Individuals in a Network-Based Intervention (Transmission Reduction Intervention Project): Phylogenetics Identify HIV-1-Infected Individuals With Social Links

Background

The Transmission Reduction Intervention Project (TRIP) is a network-based intervention that aims at decreasing human immunodeficiency virus type 1 (HIV-1) spread. We herein explore associations between transmission links as estimated by phylogenetic analyses, and social network-based ties among persons who inject drugs (PWID) recruited in TRIP.

Methods

Phylogenetic trees were inferred from HIV-1 sequences of TRIP participants. Highly supported phylogenetic clusters (transmission clusters) were those fulfilling 3 different phylogenetic confidence criteria. Social network-based ties (injecting or sexual partners, same venue engagement) were determined based on personal interviews, recruitment links, and field observation.

Results

TRIP recruited 356 individuals (90.2% PWID) including HIV-negative controls; recently HIV-infected seeds; long-term HIV-infected seeds; and their social network members. Of the 150 HIV-infected participants, 118 (78.7%) were phylogenetically analyzed. Phylogenetic analyses suggested the existence of 13 transmission clusters with 32 sequences. Seven of these clusters included 14 individuals (14/32 [43.8%]) who also had social ties with at least 1 member of their cluster. This proportion was significantly higher than what was expected by chance.

Conclusions

Molecular methods can identify HIV-infected people socially linked with another person in about half of the phylogenetic clusters. This could help public health efforts to locate individuals in networks with high transmission rates.

Impact of early initiation versus national standard of care of antiretroviral therapy in Swaziland's public sector health system: study protocol for a stepped-wedge randomized trial

Background

There is robust clinical evidence to support offering early access to antiretroviral treatment (ART) to all HIV-positive individuals, irrespective of disease stage, to both improve patient health outcomes and reduce HIV incidence. However, as the global treatment guidelines shift to meet this evidence, it is still largely unknown if early access to ART for all (also referred to as “treatment as prevention” or “universal test and treat”) is a feasible intervention in the resource-limited countries where this approach could have the biggest impact on the course of the HIV epidemics. The MaxART Early Access to ART for All (EAAA) implementation study was designed to determine the feasibility, acceptability, clinical outcomes, affordability, and scalability of offering early antiretroviral treatment to all HIV-positive individuals in Swaziland’s public sector health system.

Methods

This is a three-year stepped-wedge randomized design with open enrollment for all adults aged 18 years and older across 14 government-managed health facilities in Swaziland’s Hhohho Region. Primary endpoints are retention and viral suppression. Secondary endpoints include ART initiation, adherence, drug resistance, tuberculosis, HIV disease progression, patient satisfaction, and cost per patient per year.

Sites are grouped to transition two at a time from the control (standard of care) to intervention (EAAA) stage at each four-month step. This design will result in approximately one half of the total observation time to accrue in the intervention arm and the other half in the control arm. Our estimated enrolment number, which is supported by conservative power calculations, is 4501 patients over the course of the 36-month study period.

A multidisciplinary, mixed-methods approach will be adopted to supplement the randomized controlled trial and meet the study aims. Additional study components include implementation science, social science, economic evaluation, and predictive HIV incidence modeling.

Discussion

A stepped-wedge randomized design is a causally strong and robust approach to determine if providing antiretroviral treatment for all HIV-positive individuals is a feasible intervention in a resource-limited, public sector health system. We expect our study results to contribute to health policy decisions related to the HIV response in Swaziland and other countries in sub-Saharan Africa.

Trial registration

ClinicalTrials.gov, NCT02909218. Registered on 10 July 2016.

Electronic supplementary material

The online version of this article (doi:10.1186/s13063-017-2128-8) contains supplementary material, which is available to authorized users.

Genetic transmission networks reveal the transmission patterns of HIV-1 CRF01_AE in China

OBJECTIVES

The epidemic of HIV-1 CRF01_AE has become a major public health issue in China. This study aimed to characterise the transmission patterns of genetic networks for CRF01_AE nationwide and elucidate possible opportunities for prevention.

METHODS

We isolated and conducted genetic transmission network analysis of all available CRF01_AE pol sequences (n=4704) from China in the Los Alamos HIV sequence database.

RESULTS

A total of 1391 (29.6%) sequences were identified as belonging to 400 separate networks. Of men who have sex with men (MSM) in the networks, 93.8% were linked to other MSM and only 2.4% were linked to heterosexual women. However, 11.8% heterosexual women in the networks were linked to MSM. Lineages composed mainly of MSM had higher transmission than those that were mostly heterosexuals. Of the 1391 individuals in networks, 513 (36.9%) were linked to cases diagnosed in different provinces. The proportion of individuals involved in inter-province links was interrelated with the number of migrant people (Spearman's r=0.738, p=0.001).

CONCLUSIONS

The outcome of this study could help improve our ability to understand HIV transmission among various regions and risk groups in China, and highlighted the importance of targeting MSM and migrants by prevention and intervention efforts.

Effects of contact structure on the transient evolution of HIV virulence

Early in an epidemic, high densities of susceptible hosts select for relatively high parasite virulence; later in the epidemic, lower susceptible densities select for lower virulence. Thus over the course of a typical epidemic the average virulence of parasite strains increases initially, peaks partway through the epidemic, then declines again. However, precise quantitative outcomes, such as the peak virulence reached and its timing, may depend sensitively on epidemiological details. Fraser et al. proposed a model for the eco-evolutionary dynamics of HIV that incorporates the tradeoffs between transmission and virulence (mediated by set-point viral load, SPVL) and their heritability between hosts. Their model used implicit equations to capture the effects of partnership dynamics that are at the core of epidemics of sexually transmitted diseases. Our models combine HIV virulence tradeoffs with a range of contact models, explicitly modeling partnership formation and dissolution and allowing for individuals to transmit disease outside of partnerships. We assess summary statistics such as the peak virulence (corresponding to the maximum value of population mean log₁₀ SPVL achieved throughout the epidemic) across models for a range of parameters applicable to the HIV epidemic in sub-Saharan Africa. Although virulence trajectories are broadly similar across models, the timing and magnitude of the virulence peak vary considerably. Previously developed implicit models predicted lower virulence and slower progression at the peak (a maximum of 3.5 log₁₀ SPVL) compared both to more realistic models and to simple random-mixing models with no partnership structure at all (both with a maximum of ≈ 4.7 log₁₀ SPVL). In this range of models, the simplest random-mixing structure best approximates the most realistic model; this surprising outcome occurs because the dominance of extra-pair contact in the realistic model swamps the effects of partnership structure.

Pathogens such as HIV can evolve rapidly when the environment changes. One important aspect of a pathogen’s environment is the probability that an infectious contact (a sneeze for a respiratory disease, or an unprotected sex act for a sexually transmitted disease) encounters an uninfected person and thus has a chance to transmit the pathogen. As an epidemic grows the number of uninfected people shrinks, changing evolutionary pressures on the pathogen. While researchers have used models to explore pathogen evolution during epidemics, their models usually neglect important processes such as people entering and leaving sexual partnerships. We compared several evolutionary models for HIV that include partnership dynamics as well as sexual contact outside of stable partnerships. Models of intermediate complexity predicted lower virulence midway through the epidemic (a minimum of 15 years to progress to AIDS) than either more realistic models or simple models with no partnership structure (both with a minimum of 7.25 years to progress to AIDS), because random sexual contacts tended to wash out the effects of stable partnerships. Researchers trying to predict the evolution of pathogens must try to understand the implications of their modeling choices; models of intermediate complexity may not produce intermediate conclusions.

Inference of Transmission Network Structure from HIV Phylogenetic Trees

Phylogenetic inference is an attractive means to reconstruct transmission histories and epidemics. However, there is not a perfect correspondence between transmission history and virus phylogeny. Both node height and topological differences may occur, depending on the interaction between within-host evolutionary dynamics and between-host transmission patterns. To investigate these interactions, we added a within-host evolutionary model in epidemiological simulations and examined if the resulting phylogeny could recover different types of contact networks. To further improve realism, we also introduced patient-specific differences in infectivity across disease stages, and on the epidemic level we considered incomplete sampling and the age of the epidemic. Second, we implemented an inference method based on approximate Bayesian computation (ABC) to discriminate among three well-studied network models and jointly estimate both network parameters and key epidemiological quantities such as the infection rate. Our ABC framework used both topological and distance-based tree statistics for comparison between simulated and observed trees. Overall, our simulations showed that a virus time-scaled phylogeny (genealogy) may be substantially different from the between-host transmission tree. This has important implications for the interpretation of what a phylogeny reveals about the underlying epidemic contact network. In particular, we found that while the within-host evolutionary process obscures the transmission tree, the diversification process and infectivity dynamics also add discriminatory power to differentiate between different types of contact networks. We also found that the possibility to differentiate contact networks depends on how far an epidemic has progressed, where distance-based tree statistics have more power early in an epidemic. Finally, we applied our ABC inference on two different outbreaks from the Swedish HIV-1 epidemic.

Evolutionary Dynamics and Complicated Genetic Transmission Network Patterns of HIV-1 CRF01_AE among MSM in Shanghai, China

To explore the evolutionary dynamics and molecular transmission patterns of HIV-1 CRF01_AE in depth among men who have sex with men (MSM) in Shanghai, we constructed phylogenetic tree and genetic transmission networks based on 1, 152 pol sequences from MSM, 282 from other risk groups and 795 references. Phylogenetic analyses identified two distinct major CRF01_AE lineages and a Shanghai-based sub-lineage. The estimated tMRCAs for lineage 1 and 2 were 1996.0 (1992.9-1999.2) and 1997.8 (1994.3-2001.4), respectively. Of the 1, 152 MSM, 681 (59.1%) were identified as belonging to 241 separate networks. Of these 681 individuals in networks, 74.2% were linked to cases diagnosed in different years, 4.3% were linked to heterosexual women, and 0.7% were linked to persons who inject drugs. A total of 71 networks including 180 individuals diagnosed in Shanghai with the same domicile were found. Recent infection (P = 0.022) and sampling year after 2011 (P < 0.001) were significantly associated with potential transmission links among the networks. Besides, a significant transmission of viruses with drug resistant mutations at V179D/E were found in the networks. Given these findings, we propose that genetic transmission analysis is a useful tool in HIV intervention strategies to curb the spread of virus and promoting public health.