Determining the likely place of HIV acquisition for migrants in Europe combining subject-specific information and biomarkers data

Sources of Human Immunodeficiency Virus Infections Among Men Who Have Sex With Men With a Migration Background: A Viral Phylogenetic Case Study in Amsterdam, The Netherlands

BACKGROUND

Men and women with a migration background comprise an increasing proportion of incident human immunodeficiency virus (HIV) cases across Western Europe.

METHODS

To characterize sources of transmission in local transmission chains, we used partial HIV consensus sequences with linked demographic and clinical data from the opt-out AIDS Therapy Evaluation in the Netherlands (ATHENA) cohort of people with HIV in the Netherlands and identified phylogenetically and epidemiologically possible HIV transmission pairs in Amsterdam. We interpreted these in the context of estimated infection dates, and quantified population-level sources of transmission to foreign-born and Dutch-born Amsterdam men who have sex with men (MSM) within Amsterdam transmission chains.

RESULTS

We estimate that Dutch-born MSM were the predominant sources of infections among all Amsterdam MSM who acquired their infection locally in 2010-2021, and among almost all foreign-born Amsterdam MSM subpopulations. Stratifying by 2-year intervals indicated time trends in transmission dynamics, with a majority of infections originating from foreign-born MSM since 2016, although uncertainty ranges remained wide.

CONCLUSIONS

Native-born MSM have predominantly driven HIV transmissions in Amsterdam in 2010-2021. However, in the context of rapidly declining incidence in Amsterdam, the contribution from foreign-born MSM living in Amsterdam is increasing, with some evidence that most local transmissions have been from foreign-born Amsterdam MSM since 2016.

Post-migration HIV acquisition: A systematic review and meta-analysis

Migrants in Europe face a disproportionate burden of HIV infection; however, it remains unclear if this can be prevented through public health interventions in host countries. We undertake a systematic review and meta-analysis to estimate post-migration HIV acquisition (PMHA) as a proportion of all HIV cases in European migrants. MEDLINE, EMBASE, Global Health, HMIC, and Cochrane Library were searched with terms capturing 'HIV', 'migration', and 'Europe'. Data relating to the proportion of HIV acquired following migration were extracted and random-effects model (REM) meta-analysis was undertaken to calculate a pooled estimate for the proportion of PMHA in European countries. Subgroup meta-analysis was undertaken for PMHA by migrant demographic characteristics and host country. Fifteen articles were included for systematic review following retrieval and screening of 2,320 articles. A total of 47,182 migrants in 11 European countries were included in REM meta-analysis, showing an overall PMHA proportion of 0.30 (95% CI: 0.23-0.38). Subgroup analysis showed no significant difference in PMHA between host country and migrant demographic characteristics. This work illustrates that migrants continue to be at high risk of HIV acquisition in Europe. This indicates the need for targeted screening and HIV prevention interventions, ensuring resources are appropriately directed to combat the spread of HIV.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

A population-level application of a method for estimating the timing of HIV acquisition among migrants to Australia

INTRODUCTION

Australia has set the goal for the virtual elimination of HIV transmission by the end of 2022, yet accurate information is lacking on the level of HIV transmission occurring among residents. We developed a method for estimating the timing of HIV acquisition among migrants, relative to their arrival in Australia. We then applied this method to surveillance data from the Australian National HIV Registry with the aim of ascertaining the level of HIV transmission among migrants to Australia occurring before and after migration, and to inform appropriate local public health interventions.

METHODS

We developed an algorithm incorporating CD4⁺ T-cell decline back-projection and enhanced variables (clinical presentation, past HIV testing history and clinician estimate of the place of HIV acquisition) and compared it to a standard algorithm which uses CD4⁺ T-cell back-projection only. We applied both algorithms to all new HIV diagnoses among migrants to estimate whether HIV infection occurred before or after arrival in Australia.

RESULTS

Between 1 January 2016 and 31 December 2020, 1909 migrants were newly diagnosed with HIV in Australia, 85% were men, and the median age was 33 years. Using the enhanced algorithm, 932 (49%) were estimated to have acquired HIV after arrival in Australia, 629 (33%) before arrival (from overseas), 250 (13%) close to arrival and 98 (5%) were unable to be classified. Using the standard algorithm, 622 (33%) were estimated to have acquired HIV in Australia, 472 (25%) before arrival, 321 (17%) close to arrival and 494 (26%) were unable to be classified.

CONCLUSIONS

Using our algorithm, close to half of migrants diagnosed with HIV were estimated to have acquired HIV after arrival in Australia, highlighting the need for tailored culturally appropriate testing and prevention programmes to limit HIV transmission and achieve elimination targets. Our method reduced the proportion of HIV cases unable to be classified and can be adopted in other countries with similar HIV surveillance protocols, to inform epidemiology and elimination efforts.

Probabilistic HIV recency classification-a logistic regression without labeled individual level training data

Accurate HIV incidence estimation based on individual recent infection status (recent vs long-term infection) is important for monitoring the epidemic, targeting interventions to those at greatest risk of new infection, and evaluating existing programs of prevention and treatment. Starting from 2015, the Population-based HIV Impact Assessment (PHIA) individual-level surveys are implemented in the most-affected countries in sub-Saharan Africa. PHIA is a nationally-representative HIV-focused survey that combines household visits with key questions and cutting-edge technologies such as biomarker tests for HIV antibody and HIV viral load which offer the unique opportunity of distinguishing between recent infection and long-term infection, and providing relevant HIV information by age, gender, and location. In this article, we propose a semi-supervised logistic regression model for estimating individual level HIV recency status. It incorporates information from multiple data sources - the PHIA survey where the true HIV recency status is unknown, and the cohort studies provided in the literature where the relationship between HIV recency status and the covariates are presented in the form of a contingency table. It also utilizes the national level HIV incidence estimates from the epidemiology model. Applying the proposed model to Malawi PHIA data, we demonstrate that our approach is more accurate for the individual level estimation and more appropriate for estimating HIV recency rates at aggregated levels than the current practice - the binary classification tree (BCT).

bayroot: Bayesian sampling of HIV-1 integration dates by root-to-tip regression

The composition of the latent human immunodeficiency virus 1 (HIV-1) reservoir is shaped by when proviruses integrated into host genomes. These integration dates can be estimated by phylogenetic methods like root-to-tip (RTT) regression. However, RTT does not accommodate variation in the number of mutations over time, uncertainty in estimating the molecular clock, or the position of the root in the tree. To address these limitations, we implemented a Bayesian extension of RTT as an R package (bayroot), which enables the user to incorporate prior information about the time of infection and start of antiretroviral therapy. Taking an unrooted maximum likelihood tree as input, we use a Metropolis-Hastings algorithm to sample from the joint posterior distribution of three parameters (the rate of sequence evolution, i.e., molecular clock; the location of the root; and the time associated with the root). Next, we apply rejection sampling to this posterior sample of model parameters to simulate integration dates for HIV proviral sequences. To validate this method, we use the R package treeswithintrees (twt) to simulate time-scaled trees relating samples of actively and latently infected T cells from a single host. We find that bayroot yields significantly more accurate estimates of integration dates than conventional RTT under a range of model settings.

Post-migration HIV acquisition among african immigrants in the U.S

BACKGROUND

African immigrants in the U.S. are more likely to have a late HIV diagnosis than U.S.-born people, potentially leading to onward transmission. We sought to determine the proportion of African-born people living with HIV (APLWH) who (1) had tested HIV negative prior to diagnosis, and (2) likely acquired HIV in the U.S.

METHODS

We interviewed APLWH from 2014 to 2017 and estimated the proportion with post-migration HIV acquisition based on clinical data, HIV testing history, immigration date, and behavioral data.

RESULTS

Of 179 participants, 113 (63%) were women. Less than half (44%) reported a negative HIV test prior to diagnosis. Among 142 (79%) participants with sufficient data to evaluate post-migration HIV acquisition, we estimate that 29% acquired HIV post-migration. Most APLWH acquire HIV prior to immigration.

DISCUSSION

Approximately one-quarter of APLWH acquire HIV post-migration and HIV testing is infrequent, highlighting the need for prevention efforts for African immigrants in the U.S.

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.

HIV continuum of care: bridging cross-sectional and longitudinal analyses

OBJECTIVE

The aim of this study was to propose a unified continuum-of-care (CoC) analysis combining cross-sectional and longitudinal elements, incorporating time spent between stages.

DESIGN

The established 90-90-90 target follows a cross-sectional four-stage CoC analysis, lacking information on timing of diagnosis, antiretroviral therapy (ART) initiation, and viral suppression durability.

METHODS

Data were derived from the Athens Multicenter AIDS Cohort Study (AMACS). In the cross-sectional CoC, we added stratification of diagnosed people with HIV (PWH) by estimated time from infection to diagnosis; of those who ever initiated ART or achieved viral suppression by corresponding current status (in 2018); and cumulative incidence function (CIF) of ART initiation and viral suppression, treating loss-to-follow-up (LTFU) as competing event. Viral suppression was defined as viral load less than 500 copies/ml. Viral suppression durability was assessed by the CIF of viral load rebound.

FINDINGS

About 89.1% of PWH in 2018 were diagnosed (range of diagnoses: 1980-2018). Median time to diagnosis was 3.5 years (IQR: 1.1-7.0). Among diagnosed, 89.1% were ever treated, of whom 86.7% remained on ART. CIF of ART initiation and LTFU before ART initiation were 80.9 and 6.0% at 5 years since diagnosis, respectively. Among treated, 89.4% achieved viral suppression, of whom 87.4% were currently virally suppressed. The CIF of viral load rebound was 24.2% at 5 years since first viral suppression but substantially reduced in more recent years.

INTERPRETATION

The proposed analysis highlights time gaps in CoC not evident by the standard cross-sectional approach. Our analysis highlights the need for early diagnosis and identifies late presenters as a key population for interventions that could decrease gaps in the CoC.

Diagnosis delays in the UK according to pre or postmigration acquisition of HIV

OBJECTIVES

The aim of this study was to evaluate whether infection occurred pre or postmigration and the associated diagnosis delay in migrants diagnosed with HIV in the UK.

DESIGN

We analyzed a cohort of individuals diagnosed with HIV in the UK in 2014-2016 born in Africa or elsewhere in Europe. Inclusion criteria were arrival within 15 years before diagnosis, availability of HIV pol sequence, and viral subtype shared by at least 10 individuals.

METHODS

We examined phylogenies for evidence of infection after entry into the UK and incorporated this information into a Bayesian analysis of timing of infection using biomarkers of CD4+ cell count, avidity assays, proportion of ambiguous nucleotides in viral sequences, and last negative test dates where available.

RESULTS

One thousand, two hundred and fifty-six individuals were included. The final model indicated that HIV was acquired postmigration for most MSM born in Europe (posterior expectation 65%, 95% credibility interval 64-67%) or Africa (65%, 62-69%), whereas a minority (20-30%) of men and women with heterosexual transmission acquired HIV postmigration. Estimated diagnosis delays were lower for MSM than for those with heterosexual transmission, and were lower for those with postmigration infection across all subgroups. For MSM acquiring HIV postmigration, the estimated mean time to diagnosis was less than one year, but for those who acquired HIV premigration, the mean time from infection to diagnosis was more than five years for all subgroups.

CONCLUSION

Acquisition of HIV postmigration is common, particularly among MSM, calling for prevention efforts aimed at migrant communities. Delays in diagnosis reinforce the need for targeted testing initiatives.

Discriminating Between Premigration and Postmigration HIV Acquisition Using Surveillance Data

BACKGROUND

Migrant populations are overrepresented among persons diagnosed with HIV in the European Union and the European Economic Area. Understanding the timing of HIV acquisition (premigration or postmigration) is crucial for developing public health interventions and for producing reliable estimates of HIV incidence and the number of people living with undiagnosed HIV infection. We summarize a recently proposed method for determining the timing of HIV acquisition and apply it to both real and simulated data.

METHODS

The considered method combines estimates from a mixed model, applied to data from a large seroconverters' cohort, with biomarker measurements and individual characteristics to derive probabilities of premigration HIV acquisition within a Bayesian framework. The method is applied to a subset of data from the European Surveillance System (TESSy) and simulated data.

FINDINGS

Simulation study results showed good performance with the probabilities of correctly classifying a premigration case or a postmigration case being 87.4% and 80.4%, respectively. Applying the method to TESSy data, we estimated the proportions of migrants who acquired HIV in the destination country were 31.9%, 37.1%, 45.3%, and 45.2% for those originating from Africa, Europe, Asia, and other regions, respectively.

CONCLUSIONS

Although the considered method was initially developed for cases with multiple biomarkers' measurements, its performance, when applied to data where only one CD4 count per individual is available, remains satisfactory. Application of the method to TESSy data, estimated that a substantial proportion of HIV acquisition among migrants occurs in destination countries, having important implications for public health policy and programs.

Phylogenetic Clustering among Asylum Seekers with New HIV-1 Diagnoses in Montreal, QC, Canada

Migrants are at an increased risk of HIV acquisition. We aimed to use phylogenetics to characterize transmission clusters among newly-diagnosed asylum seekers and to understand the role of networks in local HIV transmission. Retrospective chart reviews of asylum seekers linked to HIV care between 1 June 2017 and 31 December 2018 at the McGill University Health Centre and the Jewish General Hospital in Montreal were performed. HIV-1 partial pol sequences were analyzed among study participants and individuals in the provincial genotyping database. Trees were reconstructed using MEGA10 neighbor-joining analysis. Clustering of linked viral sequences was based on a strong bootstrap support (>97%) and a short genetic distance (<0.01). Overall, 10,645 provincial sequences and 105 asylum seekers were included. A total of 13/105 participant sequences (12%; n = 7 males) formed part of eight clusters. Four clusters (two to three people) included only study participants (n = 9) and four clusters (two to three people) included four study participants clustered with six individuals from the provincial genotyping database. Six (75%) clusters were HIV subtype B. We identified the presence of HIV-1 phylogenetic clusters among asylum seekers and at a population-level. Our findings highlight the complementary role of cohort data and population-level genotypic surveillance to better characterize transmission clusters in Quebec.

Misspecifying the covariance structure in a linear mixed model under MAR drop-out

Misspecification of the covariance structure in a linear mixed model (LMM) can lead to biased population parameters' estimates under MAR drop-out. In our motivating example of modeling CD4 cell counts during untreated HIV infection, random intercept and slope LMMs are frequently used. In this article, we evaluate the performance of LMMs with specific covariance structures, in terms of bias in the fixed effects estimates, under specific MAR drop-out mechanisms, and adopt a Bayesian model comparison criterion to discriminate between the examined approaches in real-data applications. We analytically show that using a random intercept and slope structure when the true one is more complex can lead to seriously biased estimates, with the degree of bias depending on the magnitude of the MAR drop-out. Under misspecified covariance structure, we compare in terms of induced bias the approach of adding a fractional Brownian motion (BM) process on top of random intercepts and slopes with the approach of using splines for the random effects. In general, the performance of both approaches was satisfactory, with the BM model leading to smaller bias in most cases. A simulation study is carried out to evaluate the performance of the proposed Bayesian criterion in identifying the model with the correct covariance structure. Overall, the proposed method performs better than the AIC and BIC criteria under our specific simulation setting. The models under consideration are applied to real data from the CASCADE study; the most plausible model is identified by all examined criteria.

Contribution of transgender sex workers to the complexity of the HIV-1 epidemic in the metropolitan area of Milan

OBJECTIVES

Transgender people are disproportionately affected by the HIV-1 epidemic. We evaluated the origin of HIV-1 variants carried by South American transgenders living in Milan by combining accurate phylogenetic methods and epidemiological data.

METHODS

We collected 156 HIV-1 pol sequences obtained from transgender patients engaged in sex work (TSWs) followed between 1999 and 2015 at L. Sacco Hospital, Milan, Italy. Phylogenetic analyses were conducted by HIV-TRACE, MrBayes, MacClade and Beast programs. Reference sequences were retrieved from Los Alamos and local databases. Last negative testing or proxy data from clinical records of infected individuals were used to investigate the country of infection.

RESULTS

Among South American TSWs, the most represented HIV-1 subtypes were B (70.5%), F1 (12.8%) and C (4.4%). Gene flow migrations of B subtype indicated significant fluxes from TSWs to Italians (21.3%) belonging to all risk groups (26.4% to heterosexuals (HEs), 18.9% to men who have sex with men (MSM), 15.1% to injecting drug users). The largest proportion of bidirectional fluxes were observed between Italians and TSWs (24.6%). For F1 subtype, bidirectional viral fluxes involved TSWs and Italians (7.1% and 14.3%), and a similar proportion of fluxes linked TSWs and Italian HEs or MSM (both 15.8%). Significant fluxes were detected from Italians to TSWs for subtype C involving both MSM (30%) and HEs (40%). Country of HIV-1 acquisition was identified for 72 subjects; overall, the largest proportion of patients with B subtype (73.5%) acquired HIV-1 infection in South America.

CONCLUSIONS

Our results indicated that South American transgenders largely contribute to the heterogeneity of HIV-1 variants in our country. The high number of clusters based on all subtypes indicated numerous transmission chains in which TSWs were constantly intermixed with HEs and MSM. Our results strongly advocate interventions to facilitate prevention, diagnosis and HIV-1 care continuum among transgender people.

The phylogenetic approach for viral infectious disease evolution and epidemiology: An updating review

In the last decade, the phylogenetic approach is recurrent in molecular evolutionary analysis. On 12 May, 2019, about 2 296 213 papers are found, but typing "phylogeny" or "epidemiology AND phylogeny" only 199 804 and 20 133 are retrieved, respectively. Molecular epidemiology in infectious diseases is widely used to define the source of infection as so as the ancestral relationships of individuals sampled from a population. Coalescent theory and phylogeographic analysis have had scientific application in several, recent pandemic events, and nosocomial outbreaks. Hepatitis viruses and immunodeficiency virus (human immunodeficiency virus) have been largely studied. Phylogenetic analysis has been recently applied on Polyomaviruses so as in the more recent outbreaks due to different arboviruses type as Zika and chikungunya viruses discovering the source of infection and the geographic spread. Data on sequences isolated by the microorganism are essential to apply the phylogenetic tools and research in the field of infectious disease phylodinamics is growing up. There is the need to apply molecular phylogenetic and evolutionary methods in areas out of infectious diseases, as translational genomics and personalized medicine. Lastly, the application of these tools in vaccine strategy so as in antibiotic and antiviral researchers are encouraged.

Estimation of the duration between HIV seroconversion and HIV diagnosis in different population groups in French Guiana: Strategic information to reduce the proportion of undiagnosed infections

BACKGROUND

Given the great efforts put into the strategic objective of reducing the proportion of HIV-infected patients that are undiagnosed, the aim of the present study was to review the temporal trends between 1997 and 2016 for median estimates of infection duration and median CD4 count at diagnosis for the main patient origins in French Guiana.

METHODS

CD4 cell count at HIV sero-conversion and square root of CD4 cell decline were obtained using the CD4 decline in a cohort of HIV-infected persons in the UK, fitting random effect (slope and intercept) multilevel linear regression models. Multivariate analysis used robust regression for modeling the delay between estimated HIV seroconversion and diagnosis and quantile regression for CD4 at HIV diagnosis.

RESULTS

The median interval between the estimated HIV seroconversion and HIV diagnosis was 8 years for patients fromBrazil, 4.5 years for those from Haiti, 6.6 years for those from Suriname, 3.3 years for patients from Guyana, and 3.1 years for French patients. A simple robust regression model with French patients as reference group adjusting for sex and age at the time of diagnosis showed that the interval was significantly longer for Brazilian (β = +3.7 years, P = 0.001), Surinamese (β = +4.2 years, P<0.0001), Haitian origins (β = +1.5 years, P = 0.049) but not for those originating from Guyana (β = -0.03 years, P = 0.9); Men independently had a longer interval than women (β = +3.5 years, P<0.0001).

CONCLUSIONS

Despite great efforts in French Guiana regarding HIV testing both in terms of diversification and intensification we still need to tailor the offer to better reach the communities in need. These results should help authorities scale up and optimize initiatives to reduce the proportion of patients who are unaware of their infection. They also raise the question of the role of stigma and discrimination as a barrier to HIV testing in small communities, and further emphasize the importance of reducing it.