COVID-19 therapeutics: stewardship in England and considerations for antimicrobial resistance

The COVID-19 pandemic saw unprecedented resources and funds driven into research for the development, and subsequent rapid distribution, of vaccines, diagnostics and directly acting antivirals (DAAs). DAAs have undeniably prevented progression and life-threatening conditions in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. However, there are concerns of antimicrobial resistance (AMR), antiviral resistance specifically, for DAAs. To preserve activity of DAAs for COVID-19 therapy, as well as detect possible mutations conferring resistance, antimicrobial stewardship and surveillance were rapidly implemented in England. This paper expands on the ubiquitous ongoing public health activities carried out in England, including epidemiologic, virologic and genomic surveillance, to support the stewardship of DAAs and assess the deployment, safety, effectiveness and resistance potential of these novel and repurposed therapeutics.

Generation of SARS-CoV-2 escape mutations by monoclonal antibody therapy

COVID-19 patients at risk of severe disease may be treated with neutralising monoclonal antibodies (mAbs). To minimise virus escape from neutralisation these are administered as combinations e.g. casirivimab+imdevimab or, for antibodies targeting relatively conserved regions, individually e.g. sotrovimab. Unprecedented genomic surveillance of SARS-CoV-2 in the UK has enabled a genome-first approach to detect emerging drug resistance in Delta and Omicron cases treated with casirivimab+imdevimab and sotrovimab respectively. Mutations occur within the antibody epitopes and for casirivimab+imdevimab multiple mutations are present on contiguous raw reads, simultaneously affecting both components. Using surface plasmon resonance and pseudoviral neutralisation assays we demonstrate these mutations reduce or completely abrogate antibody affinity and neutralising activity, suggesting they are driven by immune evasion. In addition, we show that some mutations also reduce the neutralising activity of vaccine-induced serum.

Prediction of Coreceptor Tropism in HIV-1 Subtype C in Botswana

It remains unknown whether the C-C motif chemokine receptor type 5 (CCR5) coreceptor is still the predominant coreceptor used by Human Immunodeficiency Virus-1 (HIV-1) in Botswana, where the HIV-1 subtype C predominates. We sought to determine HIV-1C tropism in Botswana using genotypic tools, taking into account the effect of antiretroviral treatment (ART) and virologic suppression. HIV-1 gp120 V3 loop sequences from 5602 participants were analyzed for viral tropism using three coreceptor use predicting algorithms/tools: Geno2pheno, HIV-1C Web Position-Specific Score Matrices (WebPSSM) and the 11/25 charge rule. We then compared the demographic and clinical characteristics of people living with HIV (PLWH) harboring R5- versus X4-tropic viruses using χ2 and Wilcoxon rank sum tests for categorical and continuous data analysis, respectively. The three tools congruently predicted 64% of viruses as either R5-tropic or X4-tropic. Geno2pheno and the 11/25 charge rule had the highest concordance at 89%. We observed a significant difference in ART status between participants harboring X4- versus R5-tropic viruses. X4-tropic viruses were more frequent among PLWH receiving ART (χ2 test, p = 0.03). CCR5 is the predominant coreceptor used by HIV-1C strains circulating in Botswana, underlining the strong potential for CCR5 inhibitor use, even in PLWH with drug resistance. We suggest that the tools for coreceptor prediction should be used in combination.

Epidemiological and viral characteristics of undiagnosed HIV infections in Botswana

Background

HIV-1 is endemic in Botswana. The country’s primary challenge is identifying people living with HIV who are unaware of their status. We evaluated factors associated with undiagnosed HIV infection using HIV-1 phylogenetic, behavioural, and demographic data.

Methods

As part of the Botswana Combination Prevention Project, 20% of households in 30 villages were tested for HIV and followed from 2013 to 2018. A total of 12,610 participants were enrolled, 3596 tested HIV-positive at enrolment, and 147 participants acquired HIV during the trial. Extensive socio-demographic and behavioural data were collected from participants and next-generation sequences were generated for HIV-positive cases. We compared three groups of participants: (1) those previously known to be HIV-positive at enrolment (n = 2995); (2) those newly diagnosed at enrolment (n = 601) and (3) those who tested HIV-negative at enrolment but tested HIV-positive during follow-up (n = 147). We searched for differences in demographic and behavioural factors between known and newly diagnosed group using logistic regression. We also compared the topology of each group in HIV-1 phylogenies and used a genetic diversity-based algorithm to classify infections as recent (< 1 year) or chronic (≥ 1 year).

Results

Being male (aOR = 2.23) and younger than 35 years old (aOR = 8.08) was associated with undiagnosed HIV infection (p < 0.001), as was inconsistent condom use (aOR = 1.76). Women were more likely to have undiagnosed infections if they were married, educated, and tested frequently. For men, being divorced increased their risk. The genetic diversity-based algorithm classified most incident infections as recent (75.0%), but almost none of known infections (2.0%). The estimated proportion of recent infections among new diagnoses was 37.0% (p < 0.001).

Conclusion

Our results indicate that those with undiagnosed infections are likely to be young men and women who do not use condoms consistently. Among women, several factors were predictive: being married, educated, and testing frequently increased risk. Men at risk were more difficult to delineate. A sizeable proportion of undiagnosed infections were recent based on a genetic diversity-based classifier. In the era of “test and treat all”, pre-exposure prophylaxis may be prioritized towards individuals who self-identify or who can be identified using these predictors in order to halt onward transmission in time.

Evaluating whole HIV-1 genome sequence for estimation of incidence and migration in a rural South African community

Background: South Africa has the largest number of people living with HIV (PLWHIV) in the world, with HIV prevalence and transmission patterns varying greatly between provinces. Transmission between regions is still poorly understood, but phylodynamics of HIV-1 evolution can reveal how many infections are attributable to contacts outside a given community. We analysed whole genome HIV-1 genetic sequences to estimate incidence and the proportion of transmissions between communities in Hlabisa, a rural South African community. Methods: We separately analysed HIV-1 for gag, pol, and env genes sampled from 2,503 PLWHIV. We estimated time-scaled phylogenies by maximum likelihood under a molecular clock model. Phylodynamic models were fitted to time-scaled trees to estimate transmission rates, effective number of infections, incidence through time, and the proportion of infections imported to Hlabisa. We also partitioned time-scaled phylogenies with significantly different distributions of coalescent times. Results: Phylodynamic analyses showed similar trends in epidemic growth rates between 1980 and 1990. Model-based estimates of incidence and effective number of infections were consistent across genes. Parameter estimates with gag were generally smaller than those estimated with pol and env. When estimating the proportions of new infections in Hlabisa from immigration or transmission from external sources, our posterior median estimates were 85% (95% credible interval (CI) = 78%–92%) for gag, 62% (CI = 40%–78%) for pol, and 77% (CI = 58%–90%) for env in 2015. Analysis of phylogenetic partitions by gene showed that most close global reference sequences clustered within a single partition. This suggests local evolving epidemics or potential unmeasured heterogeneity in the population. Conclusions: We estimated consistent epidemic dynamic trends for gag, pol and env genes using phylodynamic models. There was a high probability that new infections were not attributable to endogenous transmission within Hlabisa, suggesting high inter-connectedness between communities in rural South Africa.

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.

Forecasting HIV-1 Genetic Cluster Growth in Illinois,United States

BACKGROUND

HIV intervention activities directed toward both those most likely to transmit and their HIV-negative partners have the potential to substantially disrupt HIV transmission. Using HIV sequence data to construct molecular transmission clusters can reveal individuals whose viruses are connected. The utility of various cluster prioritization schemes measuring cluster growth have been demonstrated using surveillance data in New York City and across the United States, by the Centers for Disease Control and Prevention (CDC).

METHODS

We examined clustering and cluster growth prioritization schemes using Illinois HIV sequence data that include cases from Chicago, a large urban center with high HIV prevalence, to compare their ability to predict future cluster growth.

RESULTS

We found that past cluster growth was a far better predictor of future cluster growth than cluster membership alone but found no substantive difference between the schemes used by CDC and the relative cluster growth scheme previously used in New York City (NYC). Focusing on individuals selected simultaneously by both the CDC and the NYC schemes did not provide additional improvements.

CONCLUSION

Growth-based prioritization schemes can easily be automated in HIV surveillance tools and can be used by health departments to identify and respond to clusters where HIV transmission may be actively occurring.

Sorting by Race/Ethnicity Across HIV Genetic Transmission Networks in Three Major Metropolitan Areas in the United States

An important component underlying the disparity in HIV risk between race/ethnic groups is the preferential transmission between individuals in the same group. We sought to quantify transmission between different race/ethnicity groups and measure racial assortativity in HIV transmission networks in major metropolitan areas in the United States. We reconstructed HIV molecular transmission networks from viral sequences collected as part of HIV surveillance in New York City, Los Angeles County, and Cook County, Illinois. We calculated assortativity (the tendency for individuals to link to others with similar characteristics) across the network for three candidate characteristics: transmission risk, age at diagnosis, and race/ethnicity. We then compared assortativity between race/ethnicity groups. Finally, for each race/ethnicity pair, we performed network permutations to test whether the number of links observed differed from that expected if individuals were sorting at random. Transmission networks in all three jurisdictions were more assortative by race/ethnicity than by transmission risk or age at diagnosis. Despite the different race/ethnicity proportions in each metropolitan area and lower proportions of clustering among African Americans than other race/ethnicities, African Americans were the group most likely to have transmission partners of the same race/ethnicity. This high level of assortativity should be considered in the design of HIV intervention and prevention strategies.

HIV genetic diversity informs stage of HIV-1 infection among patients receiving antiretroviral therapy in Botswana

Background

Human immunodeficiency virus (HIV)-1 genetic diversity increases during infection and can help infer the time elapsed since infection. However, the effect of antiretroviral treatment (ART) on the inference remains unknown.

Methods

Participants with estimated duration of HIV-1 infection based on repeated testing were sourced from cohorts in Botswana (n = 1944). Full-length HIV genome sequencing was performed from proviral deoxyribonucleic acid. We optimized a machine learning model to classify infections as < or >1 year based on viral genetic diversity, demographic, and clinical data.

Results

The best predictive model included variables for genetic diversity of HIV-1 gag, pol, and env, viral load, age, sex, and ART status. Most participants were on ART. Balanced accuracy was 90.6% (95% confidence interval, 86.7%–94.1%). We tested the algorithm among newly diagnosed participants with or without documented negative HIV tests. Among those without records, those who self-reported a negative HIV test within <1 year were more frequently classified as recent than those who reported a test >1 year previously. There was no difference in classification between those self-reporting a negative HIV test <1 year, whether or not they had a record.

Conclusions

These results indicate that recency of HIV-1 infection can be inferred from viral sequence diversity even among patients on suppressive ART.

Interplay Between Geography and HIV Transmission Clusters in Los Angeles County

BACKGROUND

Clusters of HIV diagnoses in time and space and clusters of genetically linked cases can both serve as alerts for directing prevention and treatment activities. We assessed the interplay between geography and transmission across the Los Angeles County (LAC) HIV genetic transmission network.

METHODS

Deidentified surveillance data reported for 8186 people with HIV residing in LAC from 2010 through 2016 were used to construct a transmission network using HIV-TRACE. We explored geographic assortativity, the tendency for people to link within the same geographic region; concordant time-space pairs, the proportion of genetically linked pairs from the same geographic region and diagnosis year; and Jaccard coefficient, the overlap between geographical and genetic clusters.

RESULTS

Geography was assortative in the genetic transmission network but less so than either race/ethnicity or transmission risk. Only 18% of individuals were diagnosed in the same year and location as a genetically linked partner. Jaccard analysis revealed that cis-men and younger age at diagnosis had more overlap between genetic clusters and geography; the inverse association was observed for trans-women and Blacks/African Americans.

CONCLUSIONS

Within an urban setting with endemic HIV, genetic clustering may serve as a better indicator than time-space clustering to understand HIV transmission patterns and guide public health action.

Genetic evidence for the association between COVID-19 epidemic severity and timing of non-pharmaceutical interventions

Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non-pharmaceutical interventions is still debated. We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were examined in relation to the dates of the most stringent interventions in each location as well as to the number of cumulative COVID-19 deaths and phylodynamic estimates of epidemic size. Here we report that the time elapsed between epidemic origin and maximum intervention is associated with different measures of epidemic severity and explains 11% of the variance in reported deaths one month after the most stringent intervention. Locations where strong non-pharmaceutical interventions were implemented earlier experienced much less severe COVID-19 morbidity and mortality during the period of study.

From Hospital to the Community: Redesigning the Human Immunodeficiency Virus (HIV) Clinical Service Model to Respond to an Outbreak of HIV Among People Who Inject Drugs

An outbreak of human immunodeficiency virus (HIV) among people who inject drugs in Glasgow, Scotland started in 2014. We describe 156 cases over 5 years and evaluate the impact of clinical interventions using virological and phylogenetic analysis. We established (1) HIV services within homeless health facilities, including outreach nurses, and (2) antiretroviral therapy (ART) via community pharmacies. Implementation of the new model reduced time to ART initiation from 264 to 23 days and increased community viral load suppression rates to 86%. Phylogenetic analysis demonstrated that 2019 diagnoses were concentrated within a single network. Traditional HIV care models require adaptation for this highly complex population.

Reduction in mobility and COVID-19 transmission

In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts. Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world. Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27-77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49-91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12-48%]) post-relaxation. In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.

Database of epidemic trends and control measures during the first wave of COVID-19 in mainland China

OBJECTIVES

In this data collation study, we aimed to provide a comprehensive database describing the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19) throughout the main provinces in China.

METHODS

From mid-January to March 2020, we extracted publicly available data regarding the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted descriptive analyses of the epidemic in the six most-affected provinces.

RESULTS

School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends differed among provinces. Compared with Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as the local transmission of COVID-19 declined, switching the focus of measures to the testing and quarantine of inbound travellers may have helped to sustain the control of the epidemic.

CONCLUSIONS

Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database containing these indicators and information regarding control measures is a useful resource for further research and policy planning in response to the COVID-19 epidemic.

Genomic epidemiology of a densely sampled COVID-19 outbreak in China

Analysis of genetic sequence data from the SARS-CoV-2 pandemic can provide insights into epidemic origins, worldwide dispersal, and epidemiological history. With few exceptions, genomic epidemiological analysis has focused on geographically distributed data sets with few isolates in any given location. Here, we report an analysis of 20 whole SARS- CoV-2 genomes from a single relatively small and geographically constrained outbreak in Weifang, People's Republic of China. Using Bayesian model-based phylodynamic methods, we estimate a mean basic reproduction number (R 0) of 3.4 (95% highest posterior density interval: 2.1-5.2) in Weifang, and a mean effective reproduction number (Rt) that falls below 1 on 4 February. We further estimate the number of infections through time and compare these estimates to confirmed diagnoses by the Weifang Centers for Disease Control. We find that these estimates are consistent with reported cases and there is unlikely to be a large undiagnosed burden of infection over the period we studied.

Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City region

Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epidemiological parameters. Here, we report the analysis of 864 SARS-CoV-2 sequences from cases in the New York City metropolitan area during the COVID-19 outbreak in spring 2020. The majority of cases had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that early transmission was most linked to cases from Europe. Our data are consistent with numerous seeds from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of genomic surveillance in addition to traditional epidemiological indicators.

Sequencing identifies multiple early introductions of SARS-CoV-2 to the New York City Region

Effective public response to a pandemic relies upon accurate measurement of the extent and dynamics of an outbreak. Viral genome sequencing has emerged as a powerful approach to link seemingly unrelated cases, and large-scale sequencing surveillance can inform on critical epidemiological parameters. Here, we report the analysis of 864 SARS-CoV-2 sequences from cases in the New York City metropolitan area during the COVID-19 outbreak in Spring 2020. The majority of cases had no recent travel history or known exposure, and genetically linked cases were spread throughout the region. Comparison to global viral sequences showed that early transmission was most linked to cases from Europe. Our data are consistent with numerous seeds from multiple sources and a prolonged period of unrecognized community spreading. This work highlights the complementary role of genomic surveillance in addition to traditional epidemiological indicators.

FAVITES: simultaneous simulation of transmission networks, phylogenetic trees and sequences

MOTIVATION

The ability to simulate epidemics as a function of model parameters allows insights that are unobtainable from real datasets. Further, reconstructing transmission networks for fast-evolving viruses like Human Immunodeficiency Virus (HIV) may have the potential to greatly enhance epidemic intervention, but transmission network reconstruction methods have been inadequately studied, largely because it is difficult to obtain 'truth' sets on which to test them and properly measure their performance.

RESULTS

We introduce FrAmework for VIral Transmission and Evolution Simulation (FAVITES), a robust framework for simulating realistic datasets for epidemics that are caused by fast-evolving pathogens like HIV. FAVITES creates a generative model to produce contact networks, transmission networks, phylogenetic trees and sequence datasets, and to add error to the data. FAVITES is designed to be extensible by dividing the generative model into modules, each of which is expressed as a fixed API that can be implemented using various models. We use FAVITES to simulate HIV datasets and study the realism of the simulated datasets. We then use the simulated data to study the impact of the increased treatment efforts on epidemiological outcomes. We also study two transmission network reconstruction methods and their effectiveness in detecting fast-growing clusters.

AVAILABILITY AND IMPLEMENTATION

FAVITES is available at https://github.com/niemasd/FAVITES, and a Docker image can be found on DockerHub (https://hub.docker.com/r/niemasd/favites).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

HIV co-infection is associated with increased transmission risk in patients with chronic hepatitis C virus

Molecular epidemiological analysis of viral pathogens can identify factors associated with increased transmission risk. We investigated the frequency of genetic clustering in a large data set of NS34A, NS5A, and NS5B viral sequences from patients with chronic hepatitis C virus (HCV). Within a subset of patients with longitudinal samples, Receiver Operator Characteristic (ROC) analysis was applied which identified a threshold of 0.02 substitutions/site as most appropriate for clustering. From the 7457 patients with chronic HCV infection included in this analysis, we inferred 256 clusters comprising 541 patients (7.3%). We found that HCV/HIV co-infection, young age, and high HCV viral load were all associated with increased clustering frequency, an indicator of increased transmission risk. In light of previous work on HCV/HIV co-infection in acute HCV cohorts, our results suggest that patients with HCV/HIV co-infection may disproportionately be the source of new HCV infections and treatment efforts should be geared towards viral elimination in this vulnerable population.

Hepatitis C virus genotype 1 and 2 recombinant genomes and the phylogeographic history of the 2k/1b lineage

Recombination is an important driver of genetic diversity, though it is relatively uncommon in hepatitis C virus (HCV). Recent investigation of sequence data acquired from HCV clinical trials produced twenty-one full-genome recombinant viruses belonging to three putative inter-subtype forms 2b/1a, 2b/1b, and 2k/1b. The 2k/1b chimera is the only known HCV circulating recombinant form (CRF), provoking interest in its genetic structure and origin. Discovered in Russia in 1999, 2k/1b cases have since been detected throughout the former Soviet Union, Western Europe, and North America. Although 2k/1b prevalence is highest in the Caucasus mountain region (i.e., Armenia, Azerbaijan, and Georgia), the origin and migration patterns of CRF 2k/1b have remained obscure due to a paucity of available sequences. We assembled an alignment which spans the entire coding region of the HCV genome containing all available 2k/1b sequences (>500 nucleotides; n = 109) sampled in ninteen countries from public databases (102 individuals), additional newly sequenced genomic regions (from 48 of these 102 individuals), unpublished isolates with newly sequenced regions (5 additional individuals), and novel complete genomes (2 additional individuals) generated in this study. Analysis of this expanded dataset reconfirmed the monophyletic origin of 2k/1b with a recombination breakpoint at position 3,187 (95% confidence interval: 3,172–3,202; HCV GT1a reference strain H77). Phylogeography is a valuable tool used to reveal viral migration dynamics. Inference of the timed history of spread in a Bayesian framework identified Russia as the ancestral source of the CRF 2k/1b clade. Further, we found evidence for migration routes leading out of Russia to other former Soviet Republics or countries under the Soviet sphere of influence. These findings suggest an interplay between geopolitics and the historical spread of CRF 2k/1b.

Recent and Rapid Transmission of HIV Among People Who Inject Drugs in Scotland Revealed Through Phylogenetic Analysis

Background

Harm reduction has dramatically reduced HIV incidence among people who inject drugs (PWID). In Glasgow, Scotland, <10 infections/year have been diagnosed among PWID since the mid-1990s. However, in 2015 a sharp rise in diagnoses was noted among PWID; many were subtype C with 2 identical drug-resistant mutations and some displayed low avidity, suggesting the infections were linked and recent.

Methods

We collected Scottish pol sequences and identified closely related sequences from public databases. Genetic linkage was ascertained among 228 Scottish, 1820 UK, and 524 global sequences. The outbreak cluster was extracted to estimate epidemic parameters.

Results

All 104 outbreak sequences originated from Scotland and contained E138A and V179E. Mean genetic distance was <1% and mean time between transmissions was 6.7 months. The average number of onward transmissions consistently exceeded 1, indicating that spread was ongoing.

Conclusions

In contrast to other recent HIV outbreaks among PWID, harm reduction services were not clearly reduced in Scotland. Nonetheless, the high proportion of individuals with a history of homelessness (45%) suggests that services were inadequate for those in precarious living situations. The high prevalence of hepatitis C (>90%) is indicative of sharing of injecting equipment. Monitoring the epidemic phylogenetically in real time may accelerate public health action.

Non-disclosed men who have sex with men in UK HIV transmission networks: phylogenetic analysis of surveillance data

BACKGROUND

Patients who do not disclose their sexuality, including men who do not disclose same-sex behaviour, are difficult to characterise through traditional epidemiological approaches such as interviews. Using a recently developed method to detect large networks of viral sequences from time-resolved trees, we localised non-disclosed men who have sex with men (MSM) in UK transmission networks, gaining crucial insight into the behaviour of this group.

METHODS

For this phylogenetic analysis, we obtained HIV pol sequences from the UK HIV Drug Resistance Database (UKRDB), a central repository for resistance tests done as part of routine clinical care throughout the UK. Sequence data are linked to demographic and clinical data held by the UK Collaborative HIV Cohort study and the national HIV/AIDS reporting system database. Initially, we reconstructed maximum likelihood phylogenies from these sequences, then sequences were selected for time-resolved analysis in BEAST if they were clustered with at least one other sequence at a genetic distance of 4·5% or less with support of at least 90%. We used time-resolved phylogenies to create networks by linking together nodes if sequences shared a common ancestor within the previous 5 years. We identified potential non-disclosed MSM (pnMSM), defined as self-reported heterosexual men who clustered only with men. We measured the network position of pnMSM, including betweenness (a measure of connectedness and importance) and assortativity (the propensity for nodes sharing attributes to link).

FINDINGS

14 405 individuals were in the network, including 8452 MSM, 1743 heterosexual women and 1341 heterosexual men. 249 pnMSM were identified (18·6% of all clustered heterosexual men) in the network. pnMSM were more likely to be black African (p<0·0001), less likely to be infected with subtype B (p=0·006), and were slightly older (p=0·002) than the MSM they clustered with. Mean betweenness centrality was lower for pnMSM than for MSM (1·31, 95% CI 0·48-2·15 in pnMSM vs 2·24, 0·98-3·51 in MSM; p=0·002), indicating that pnMSM were in peripheral positions in MSM clusters. Assortativity by risk group was higher than expected (0·037 vs -0·037, p=0·01) signifying that pnMSM were linked to each other. We found that self-reported heterosexual men were more likely to link MSM and heterosexual women than heterosexual women were to link MSM and heterosexual men (Fisher's exact test p=0·0004; OR 2·24) but the number of such transmission chains was small (only 54 in total vs 32 in women).

INTERPRETATION

pnMSM are a subgroup distinct from both MSM and from heterosexual men. They are more likely to choose sexual partners who are also pnMSM and might exhibit lower-risk sexual behaviour than MSM (eg, choosing low-risk partners or consistently using condoms). Heterosexual men are the group most likely to be diagnosed with late-stage disease (ie, low CD4 counts) and non-disclosed MSM might put female partners at higher risk than heterosexual men because non-disclosed MSM have male partners. Hence, pnMSM require specific consideration to ensure they are included in public health interventions.

FUNDING

National Institutes of Health.

HIV transmission networks among transgender women in Los Angeles County, CA, USA: a phylogenetic analysis of surveillance data

BACKGROUND

Transgender women are among the groups at highest risk for HIV infection, with a prevalence of 27·7% in the USA; and despite this known high risk, undiagnosed infection is common in this population. We set out to identify transgender women and their partners in a molecular transmission network to prioritise public health activities.

METHODS

Since 2006, HIV protease and reverse transcriptase gene (pol) sequences from drug resistance testing have been reported to the Los Angeles County Department of Public Health and linked to demographic data, gender, and HIV transmission risk factor data for each case in the enhanced HIV/AIDS Reporting System. We reconstructed a molecular transmission network by use of HIV-TRAnsmission Cluster Engine (with a pairwise genetic distance threshold of 0·015 substitutions per site) from the earliest pol sequences from 22 398 unique individuals, including 412 (2%) self-identified transgender women. We examined the possible predictors of clustering with multivariate logistic regression. We characterised the genetically linked partners of transgender women and calculated assortativity (the tendency for people to link to other people with the same attributes) for each transmission risk group.

FINDINGS

8133 (36·3%) of 22 398 individuals clustered in the network across 1722 molecular transmission clusters. Transgender women who indicated a sexual risk factor clustered at the highest frequency in the network, with 147 (43%) of 345 being linked to at least one other person (adjusted odds ratio [aOR] 2·0, p=0·0002). Transgender women were assortative in the network (assortativity 0·06, p<0·001), indicating that they tended to link to other transgender women. Transgender women were more likely than expected to link to other transgender women (OR 4·65, p<0·001) and cisgender men who did not identify as men who have sex with men (MSM; OR 1·53, p<0·001). Transgender women were less likely than expected to link to MSM (OR 0·75, p<0·001), despite the high prevalence of HIV among MSM. Transgender women were distributed across 126 clusters, and cisgender individuals linked to one transgender woman were 9·2 times more likely to link to a second transgender woman than other individuals in the surveillance database. Reconstruction of the transmission network is limited by sample availability, but sequences were available for more than 40% of diagnoses.

INTERPRETATION

Clustering of transgender women and the observed tendency for linkage with cisgender men who did not identify as MSM, shows the potential to use molecular epidemiology both to identify clusters that are likely to include undiagnosed transgender women with HIV and to improve the targeting of public health prevention and treatment services to transgender women.

FUNDING

California HIV and AIDS Research Program and National Institutes of Health-National Institute of Allergy and Infectious Diseases.

Intrapatient viral diversity and treatment outcome in patients with genotype 3a hepatitis C virus infection on sofosbuvir-containing regimens

Treatment with the direct-acting antiviral agent (DAA) sofosbuvir (SOF), an NS5B inhibitor, and velpatasvir (VEL), an NS5A inhibitor, demonstrates viral cure rates of ≥95% in hepatitis C virus (HCV) genotypes (GT) 1-6. Here, we investigated intrapatient HCV diversity in NS5A and NS5B using Shannon entropy to examine the relationship between viral diversity and treatment outcome. At baseline, HCV diversity was lowest in patients infected with HCV GT3 as compared to the other GTs, and viral diversity was greater in NS5A than NS5B (P < .0001). Treatment outcome with SOF/VEL or the comparator regimen of SOF with ribavirin (RBV) was not correlated with baseline diversity. However, among persons treated with SOF/VEL, a decrease in diversity from baseline was observed at relapse in the majority virologic failures, consistent with a viral bottleneck event at relapse. In contrast, an increase in diversity was observed in 27% of SOF+RBV virologic failures. We investigated whether the increase in diversity was due to an increase in the transition rate, one mode of potential RBV-mediated mutagenesis; however, we found no evidence of this mechanism. Overall, we did not observe that viral diversity at baseline influenced treatment outcome, but the diversity changes observed at relapse can improve our understanding of RBV viral suppression in vivo.

Bayesian inference reveals ancient origin of simian foamy virus in orangutans

Simian foamy viruses (SFVs) infect most nonhuman primate species and appears to co-evolve with its hosts. This co-evolutionary signal is particularly strong among great apes, including orangutans (genus Pongo). Previous studies have identified three distinct orangutan SFV clades. The first of these three clades is composed of SFV from P. abelii from Sumatra, the second consists of SFV from P. pygmaeus from Borneo, while the third clade is mixed, comprising an SFV strain found in both species of orangutan. The existence of the mixed clade has been attributed to an expansion of P. pygmaeus into Sumatra following the Mount Toba super-volcanic eruption about 73,000years ago. Divergence dating, however, has yet to be performed to establish a temporal association with the Toba eruption. Here, we use a Bayesian framework and a relaxed molecular clock model with fossil calibrations to test the Toba hypothesis and to gain a more complete understanding of the evolutionary history of orangutan SFV. As with previous studies, our results show a similar three-clade orangutan SFV phylogeny, along with strong statistical support for SFV-host co-evolution in orangutans. Using Bayesian inference, we date the origin of orangutan SFV to >4.7 million years ago (mya), while the mixed species clade dates to approximately 1.7mya, >1.6 million years older than the Toba super-eruption. These results, combined with fossil and paleogeographic evidence, suggest that the origin of SFV in Sumatran and Bornean orangutans, including the mixed species clade, likely occurred on the mainland of Indo-China during the Late Pliocene and Calabrian stage of the Pleistocene, respectively.

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

We compared the behavior of two approaches (Cluster Picker and HIV-TRACE) at varying genetic distances to identify transmission clusters. We used three HIV gp41 sequence datasets originating from the Rakai Community Cohort Study: (1) next-generation sequence (NGS) data from nine linked couples; (2) NGS data from longitudinal sampling of 14 individuals; and (3) Sanger consensus sequences from a cross-sectional dataset (n = 1,022) containing 91 epidemiologically linked heterosexual couples. We calculated the optimal genetic distance threshold to separate linked versus unlinked NGS datasets using a receiver operating curve analysis. We evaluated the number, size, and composition of clusters detected by Cluster Picker and HIV-TRACE at six genetic distance thresholds (1%-5.3%) on all three datasets. We further tested the effect of using all NGS, versus only a single variant for each patient/time point, for datasets (1) and (2). The optimal gp41 genetic distance threshold to distinguish linked and unlinked couples and individuals was 5.3% and 4%, respectively. HIV-TRACE tended to detect larger and fewer clusters, whereas Cluster Picker detected more clusters containing only two sequences. For NGS datasets (1) and (2), HIV-TRACE and Cluster Picker detected all linked pairs at 3% and 4% genetic distances, respectively. However, at 5.3% genetic distance, 20% of couples in dataset (3) did not cluster using either program, and for >1/3 of couples cluster assignment were discordant. We suggest caution in choosing thresholds for clustering analyses in a generalized epidemic.

Detailed phylogenetic analysis of primate T-lymphotropic virus type 1 (PTLV-1) sequences from orangutans (Pongo pygmaeus) reveals new insights into the evolutionary history of PTLV-1 in Asia

While human T-lymphotropic virus type 1 (HTLV-1) originates from ancient cross-species transmission of simian T-lymphotropic virus type 1 (STLV-1) from infected nonhuman primates, much debate exists on whether the first HTLV-1 occurred in Africa, or in Asia during early human evolution and migration. This topic is complicated by a lack of representative Asian STLV-1 to infer PTLV-1 evolutionary histories. In this study we obtained new STLV-1 LTR and tax sequences from a wild-born Bornean orangutan (Pongo pygmaeus) and performed detailed phylogenetic analyses using both maximum likelihood and Bayesian inference of available Asian PTLV-1 and African STLV-1 sequences. Phylogenies, divergence dates and nucleotide substitution rates were co-inferred and compared using six different molecular clock calibrations in a Bayesian framework, including both archaeological and/or nucleotide substitution rate calibrations. We then combined our molecular results with paleobiogeographical and ecological data to infer the most likely evolutionary history of PTLV-1. Based on the preferred models our analyses robustly inferred an Asian source for PTLV-1 with cross-species transmission of STLV-1 likely from a macaque (Macaca sp.) to an orangutan about 37.9-48.9kya, and to humans between 20.3-25.5kya. An orangutan diversification of STLV-1 commenced approximately 6.4-7.3kya. Our analyses also inferred that HTLV-1 was first introduced into Australia ~3.1-3.7kya, corresponding to both genetic and archaeological changes occurring in Australia at that time. Finally, HTLV-1 appears in Melanesia at ~2.3-2.7kya corresponding to the migration of the Lapita peoples into the region. Our results also provide an important future reference for calibrating information essential for PTLV evolutionary timescale inference. Longer sequence data, or full genomes from a greater representation of Asian primates, including gibbons, leaf monkeys, and Sumatran orangutans are needed to fully elucidate these evolutionary dates and relationships using the model criteria suggested herein.

Transmission of Non-B HIV Subtypes in the United Kingdom Is Increasingly Driven by Large Non-Heterosexual Transmission Clusters

Background. The United Kingdom human immunodeficiency virus (HIV) epidemic was historically dominated by HIV subtype B transmission among men who have sex with men (MSM). Now 50% of diagnoses and prevalent infections are among heterosexual individuals and mainly involve non-B subtypes. Between 2002 and 2010, the prevalence of non-B diagnoses among MSM increased from 5.4% to 17%, and this study focused on the drivers of this change.

Methods. Growth between 2007 and 2009 in transmission clusters among 14 000 subtype A1, C, D, and G sequences from the United Kingdom HIV Drug Resistance Database was analysed by risk group.

Results. Of 1148 clusters containing at least 2 sequences in 2007, >75% were pairs and >90% were heterosexual. Most clusters (71.4%) did not grow during the study period. Growth was significantly lower for small clusters and higher for clusters of ≥7 sequences, with the highest growth observed for clusters comprising sequences from MSM and people who inject drugs (PWID). Risk group (P < .0001), cluster size (P < .0001), and subtype (P < .01) were predictive of growth in a generalized linear model.

Discussion. Despite the increase in non-B subtypes associated with heterosexual transmission, MSM and PWID are at risk for non-B infections. Crossover of subtype C from heterosexuals to MSM has led to the expansion of this subtype within the United Kingdom.

Lack of Effectiveness of Antiretroviral Therapy in Preventing HIV Infection in Serodiscordant Couples in Uganda: An Observational Study

Background

We examined the real-world effectiveness of ART as an HIV prevention tool among HIV serodiscordant couples in a programmatic setting in a low-income country.

Methods

We enrolled individuals from HIV serodiscordant couples aged ≥18 years of age in Jinja, Uganda from June 2009 – June 2011. In one group of couples the HIV positive partner was receiving ART as they met clinical eligibility criteria (a CD4 cell count ≤250 cells/ μL or WHO Stage III/IV disease). In the second group the infected partner was not yet ART-eligible. We measured HIV incidence by testing the uninfected partner every three months. We conducted genetic linkage studies to determine the source of new infections in seroconverting participants.

Results

A total of 586 couples were enrolled of which 249 (42%) of the HIV positive participants were receiving ART at enrollment, and an additional 99 (17%) initiated ART during the study. The median duration of follow-up was 1.5 years. We found 9 new infections among partners of participants who had been receiving ART for at least three months and 8 new infections in partners of participants who had not received ART or received it for less than three months, for incidence rates of 2.09 per 100 person-years (PYRs) and 2.30 per 100 PYRs, respectively. The incidence rate ratio for ART-use was 0.91 (95% confidence interval 0.31-2.70; p=0.999). The hazard ratio for HIV seroconversion associated with ART-use by the positive partner was 1.07 (95% CI 0.41-2.80). A total of 5/7 (71%) of the transmissions on ART and 6/7 (86%) of those not on ART were genetically linked.

Conclusion

Overall HIV incidence was low in comparison to previous studies of serodiscordant couples. However, ART-use was not associated with a reduced risk of HIV transmission in this study.

Analysis of the history and spread of HIV-1 in Uganda using phylodynamics

HIV prevalence has decreased in Uganda since the 1990s, but remains substantial within high-risk groups. Here, we reconstruct the history and spread of HIV subtypes A1 and D in Uganda and explore the transmission dynamics in high-risk populations. We analysed HIV pol sequences from female sex workers in Kampala (n = 42), Lake Victoria fisher-folk (n = 46) and a rural clinical cohort (n = 74), together with publicly available sequences from adjacent regions in Uganda (n = 412) and newly generated sequences from samples taken in Kampala in 1986 (n = 12). Of the sequences from the three Ugandan populations, 60 (37.1 %) were classified as subtype D, 54 (33.3 %) as subtype A1, 31 (19.1 %) as A1/D recombinants, six (3.7 %) as subtype C, one (0.6 %) as subtype G and 10 (6.2 %) as other recombinants. Among the A1/D recombinants we identified a new candidate circulating recombinant form. Phylodynamic and phylogeographic analyses using BEAST indicated that the Ugandan epidemics originated in 1960 (1950-1968) for subtype A1 and 1973 (1970-1977) for D, in rural south-western Uganda with subsequent spread to Kampala. They also showed extensive interconnection with adjacent countries. The sequence analysis shows both epidemics grew exponentially during the 1970s-1980s and decreased from 1992, which agrees with HIV prevalence reports in Uganda. Inclusion of sequences from the 1980s indicated the origin of both epidemics was more recent than expected and substantially narrowed the confidence intervals in comparison to previous estimates. We identified three transmission clusters and ten pairs, none of them including patients from different populations, suggesting active transmission within a structured transmission network.

Automated analysis of phylogenetic clusters

BACKGROUND

As sequence data sets used for the investigation of pathogen transmission patterns increase in size, automated tools and standardized methods for cluster analysis have become necessary. We have developed an automated Cluster Picker which identifies monophyletic clades meeting user-input criteria for bootstrap support and maximum genetic distance within large phylogenetic trees. A second tool, the Cluster Matcher, automates the process of linking genetic data to epidemiological or clinical data, and matches clusters between runs of the Cluster Picker.

RESULTS

We explore the effect of different bootstrap and genetic distance thresholds on clusters identified in a data set of publicly available HIV sequences, and compare these results to those of a previously published tool for cluster identification. To demonstrate their utility, we then use the Cluster Picker and Cluster Matcher together to investigate how clusters in the data set changed over time. We find that clusters containing sequences from more than one UK location at the first time point (multiple origin) were significantly more likely to grow than those representing only a single location.

CONCLUSIONS

The Cluster Picker and Cluster Matcher can rapidly process phylogenetic trees containing tens of thousands of sequences. Together these tools will facilitate comparisons of pathogen transmission dynamics between studies and countries.

Adaptive evolution of HIV at HLA epitopes is associated with ethnicity in Canada

Host immune selection pressure influences the development of mutations that allow for HIV escape. Mutation patterns induced in HIV by the human leukocyte antigen (HLA) are HLA-allele specific. As ethnic groups have distinct and characteristic HLA allele frequencies, we can expect divergent viral evolution within ethnicities. Here, we have sequenced and analyzed the HIV pol gene from 1248 subtype B infected, treatment-naïve individuals in Canada. Phylogenetic analysis showed no separation between pol sequences from five self-identified ethnic groups, yet fixation index (F_ST) values showed significant divergence between ethnicities. A total of 17 amino acid sites showed an ethnic-specific fixation pattern (0.015<F_ST <0.060, p<0.01), and 27 codons were inferred to be under positive selection (p<0.01), with each set of sites strongly associated with HLA sites (p = 1.78×10⁻⁶ and p = 1.91×10⁻⁷, respectively). Within the pol gene, eight sites under HLA selective pressure were correlated with ethnicity, indicating ‘adaptive divergence’ between the groups studied. Our findings highlight challenges in HIV vaccine design in ethnically diverse countries with subtype B epidemics.

HIV-1 modulates the tRNA pool to improve translation efficiency

Despite its poorly adapted codon usage, HIV-1 replicates and is expressed extremely well in human host cells. HIV-1 has recently been shown to package non-lysyl transfer RNAs (tRNAs) in addition to the tRNA(Lys) needed for priming reverse transcription and integration of the HIV-1 genome. By comparing the codon usage of HIV-1 genes with that of its human host, we found that tRNAs decoding codons that are highly used by HIV-1 but avoided by its host are overrepresented in HIV-1 virions. In particular, tRNAs decoding A-ending codons, required for the expression of HIV's A-rich genome, are highly enriched. Because the affinity of Gag-Pol for all tRNAs is nonspecific, HIV packaging is most likely passive and reflects the tRNA pool at the time of viral particle formation. Codon usage of HIV-1 early genes is similar to that of highly expressed host genes, but codon usage of HIV-1 late genes was better adapted to the selectively enriched tRNA pool, suggesting that alterations in the tRNA pool are induced late in viral infection. If HIV-1 genes are adapting to an altered tRNA pool, codon adaptation of HIV-1 may be better than previously thought.