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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.

BACKGROUND In the United States, young men (aged 13-24 years) who have sex with men (MSM) bear a disproportionate burden of HIV. Transmission among MSM has been found to be disassortative by age. METHODS We analyzed HIV-1 pol sequences reported to the US National HIV Surveillance System from MSM with HIV diagnosed during 2009-2016. Using an HIV genetic transmission network, we identified persons with closely related viruses (ie, genetic distance ≤1.5%) and used multivariable logistic regression to examine changes from 2009-2012 to 2013-2016 in proportions of MSM linked to young MSM who were >5 years older or of the same race/ethnicity. RESULTS Among 9510 young MSM linked to another MSM with a closely related virus, 37% linked to an older MSM and 62% linked to an MSM of the same race/ethnicity. Comparing 2013-2016 with 2009-2012, we found increases in linkage of older MSM to young MSM, with the most substantial increases seen in Hispanic/Latinos aged 13-19 [adjusted prevalence ratio (APR) = 1.31, 95% confidence interval (CI) = 1.11 to 1.56] and blacks aged 13-19 (APR = 1.23, CI = 1.06 to 1.41) and 20-24 years (APR = 1.14, CI = 1.02 to 1.28). By contrast, change in linkage patterns among racial/ethnic groups was unremarkable. CONCLUSIONS We found evidence of increased age mixing among MSM with respect to HIV transmission over time, which coincides temporally with changes in partner-seeking behavior such as increased use of mobile applications. These findings indicate the importance of social factors on HIV sexual and transmission networks and suggest that prevention efforts need to effectively reach MSM of all ages.

Objective To identify correlates of incident HIV infection in rapidly growing HIV molecular clusters. Design Phylogenetic analysis of HIV public health surveillance data. Methods High-priority HIV genetic transmission clusters with evidence of rapid growth in 2012 (i.e. clusters with a pairwise genetic distance ≤0.005 substitutions/site and at least three cases diagnosed in 2012) were identified using HIV-TRACE. Then, we investigated cluster growth, defined as HIV cases diagnosed in the following 5 years that were genetically linked to these clusters. For clusters that grew during the follow-up period, Bayesian molecular clock phylogenetic inference was performed to identify clusters with evidence of incident HIV infection (as opposed to diagnosis of previously infected cases) during this follow-up period. Results Of the 116 rapidly growing clusters identified, 73 (63%) had phylogenetic evidence for an incident HIV case during the 5-year follow-up period. Correlates of an incident HIV case arising in clusters included a greater number of diagnosed but virally unsuppressed cases in 2012, a greater number of inferred undiagnosed cases in the cluster in 2012, and a younger time of most recent common ancestor for the cluster. Conclusion These findings suggest that incident infections in rapidly growing clusters originate equally from diagnosed but unsuppressed cases and undiagnosed infections. These results highlight the importance of promoting retention in care and viral suppression as well as partner notification and other case-finding activities when investigating and intervening on high-priority molecular transmission clusters.

BACKGROUND: To develop a predictive model to prioritize persons with a transmissible HIV viral load for transmission-reduction interventions. METHODS: New York City (NYC) HIV molecular surveillance data from 2010–2013 were used to build a model to predict the probability that the partial pol gene of the virus of a person with a transmissible HIV viral load (>1,500 copies/mL) would be genetically similar to that of a person with a new HIV infection (diagnosis at stage 0 or 1 according to the revised Centers for Disease Control and Prevention classification system). Data from 2013–2016 were then used to validate the model and compare it with five other selection strategies that can be used to prioritize persons for transmission-reduction interventions. RESULTS: A total of 10,609 persons living with HIV (PLWH) were included in the development dataset, and 8,257 were included in the validation dataset. Among the six selection strategies, the predictive model had the highest area under the receiver operating characteristic curve (AUC) (0.86, 95% confidence interval [CI]: 0.84, 0.88), followed by the “Young men who have sex with men (MSM)” (0.79, 95% CI: 0.77, 0.82), “MSM with high viral loads” (0.74, 95% CI: 0.72, 0.76), “Random sample of MSM” (0.73, 95% CI: 0.71, 0.76), “Persons with high viral loads” (0.56, 95% CI: 0.54, 0.59), and “Random sample” (0.50, 95% CI: 0.48, 0.53) strategies. CONCLUSIONS: Jurisdictions should consider applying predictive modeling to prioritize persons with a transmissible viral load for transmission-reduction interventions and to evaluate its feasibility and effectiveness.

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.

Viruses closely related to human pathogens can reveal the origins of human infectious diseases. Human herpes simplexvirus type 1 (HSV-1) and type 2 (HSV-2) are hypothesized to have arisen via host-virus codivergence and cross-species transmission. We report the discovery of novel herpes simplexviruses during a large-scale screening of fecal samples from wild gorillas, bonobos, and chimpanzees. Phylogenetic analysis indicates that, contrary to expectation, simplexviruses from these African apes are all more closely related to HSV-2 than to HSV-1. Molecular clock-based hypothesis testing suggests the divergence between HSV-1 and the African great ape simplexviruses likely represents a codivergence event between humans and gorillas. The simplexviruses infecting African great apes subsequently experienced multiple cross-species transmission events over the past 3 My, the most recent of which occurred between humans and bonobos around 1 Ma. These findings revise our understanding of the origins of human herpes simplexviruses and suggest that HSV-2 is one of the earliest zoonotic pathogens.

Molecular epidemiological analysis of viral pathogens can identify factors associated with increased transmission risk. We investigated the frequency of genetic clustering in a large dataset of NS34A, NS5A, and NS5B viral sequences from patients with chronic hepatitis C virus (HCV) genotypes 1–6 infection. 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 7,457 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 elimination in this vulnerable population.

Purpose of review To discuss the recent HIV phylogenetic analyses examining HIV transmission patterns among and within risk groups. Recent findings Phylodynamic analysis has recently been applied to multiple HIV outbreaks among people who inject drugs to determine whether HIV transmission is ongoing. Large-scale analyses of datasets of HIV sequences collected for drug-resistance testing provide population-level insights into transmission patterns. One focus across world regions has been to investigate whether age-disparity is a driver of HIV transmission. In sub-Saharan Africa, researchers have examined transmission between heterosexuals and MSM and between high prevalence fishing communities and inland communities. In the US and the UK, cryptic risk groups such as nondisclosed MSM and the partners of transgender women are increasingly being uncovered based on their position in densely sampled molecular transmission networks. Summary Analysis of HIV genetic sequence can resolve viral transmission patterns between risk groups at unprecedented scales and levels of detail. Future research should focus on understanding the effect of missing data on inferences and the biases of different methods. Uncovering groups and patterns obscured from traditional epidemiolocal analyses is exciting but should not compromise the privacy of the groups in question.

Summary 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 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.

Public health interviews (i.e., partner services), during which persons with diagnosed human immunodeficiency virus (HIV) infection name their sexual or needle-sharing partners (named partners), are used to identify HIV transmission networks to guide and prioritize HIV prevention activities. HIV sequence data, generated from provider-ordered drug resistance testing, can be used to understand characteristics of molecular clusters, a group of sequences for which each sequence is highly similar (linked) to all other sequences, and assess whether named partners are plausible HIV transmission partners. Although molecular data in higher HIV-morbidity states have been analyzed (1-3), few analyses exist for lower morbidity states (4), such as Wisconsin, which reported 4.6 HIV diagnoses per 100,000 persons aged ≥13 years in 2016 (5). The Wisconsin Division of Public Health (DPH) analyzed HIV sequence data generated from provider-ordered drug resistance testing and collected through routine HIV surveillance to identify molecular clusters and describe demographic and transmission risk characteristics among pairs of persons whose sequences were highly genetically similar (i.e., molecular linkages). In addition, overlap between partner linkages identified during public health interviews and molecular linkages was assessed. Overall, characteristics of molecular clusters in Wisconsin mirrored those from states with more HIV diagnoses, particularly in that most molecular linkages were observed among persons of the same race (78.2% of non-Hispanic blacks [blacks] linked to other blacks), the same transmission risk (90.2% of men who have sex with men [MSM] linked to other MSM), and the same age group (59.2% of persons aged 20-29 years linked to other persons aged 20-29 years). Among named partner linkages identified during interviews in which both persons also had a reported sequence, overlap of named partner and molecular linkages was moderate: 33.8% of named partners were plausible transmission partners according to available molecular data. Analysis of HIV sequence data is a useful tool for characterizing transmission patterns not immediately apparent using traditional public health interview data, even in a state with lower HIV morbidity. Prevention recommendations generated from national data (e.g., targeting preexposure prophylaxis for HIV-negative persons at high risk and implementing measures to maintain viral suppression among persons with HIV infection) also are relevant in a lower HIV-morbidity state.

BACKGROUND: Detecting recent and rapid spread of HIV can help prioritize prevention and early treatment for those at highest risk of transmission. HIV genetic sequence data can identify transmission clusters, but previous approaches have not distinguished clusters of recent, rapid transmission. We assessed an analytic approach to identify such clusters in the United States. METHODS: We analyzed 156,553 partial HIV-1 polymerase sequences reported to the National HIV Surveillance System and inferred transmission clusters using two genetic distance thresholds (0.5% and 1.5%) and two time periods for diagnoses (all years and 2013–2015, i.e., recent diagnoses). For rapidly growing clusters (with ≥5 diagnoses during 2015), molecular clock phylogenetic analysis estimated the time to most recent common ancestor for all divergence events within the cluster. Cluster transmission rates were estimated using these phylogenies. RESULTS: A distance threshold of 1.5% identified 103 rapidly growing clusters using all diagnoses and 73 using recent diagnoses; at 0.5%, 15 clusters were identified using all diagnoses and 13 using recent diagnoses. Molecular clock analysis estimated that the 13 clusters identified at 0.5% using recent diagnoses had been diversifying for a median of 4.7 years, compared with 6.5–13.2 years using other approaches. The 13 clusters at 0.5% had a transmission rate of 33/100 person-years, compared with previous national estimates of 4/100 person-years. CONCLUSIONS: Our approach identified clusters with transmission rates 8 times those of previous national estimates. This method can identify groups involved in rapid transmission and help programs effectively direct and prioritize limited public health resources.

Introduction Molecular surveillance systems could provide public health benefits to focus strategies to improve the HIV care continuum. Here, we infer the HIV genetic network of Mexico City in 2020, and identify actively growing clusters that could represent relevant targets for intervention. Methods All new diagnoses, referrals from other institutions, as well as persons returning to care, enrolling at the largest HIV clinic in Mexico City were invited to participate in the study. The network was inferred from HIV pol sequences, using pairwise genetic distance methods, with a locally hosted, secure version of the HIV‐TRACE tool: Seguro HIV‐TRACE. Socio‐demographic, clinical and behavioural metadata were overlaid across the network to design focused prevention interventions. Results A total of 3168 HIV sequences from unique individuals were included. One thousand and one‐hundred and fifty (36%) sequences formed 1361 links within 386 transmission clusters in the network. Cluster size varied from 2 to 14 (63% were dyads). After adjustment for covariates, lower age (adjusted odds ratio [aOR]: 0.37, p34 vs.

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.

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

This study introduces an innovative methodological approach to identify potential drivers of structuring HIV-1 transmission clustering patterns between different subpopulations in the culturally and racially/ethnically diverse context of Houston, TX, the largest city in the Southern United States. Using 6332 HIV-1 pol sequences from persons newly diagnosed with HIV during the period 2010–2018, we reconstructed HIV-1 transmission clusters, using the HIV-TRAnsmission Cluster Engine (HIV-TRACE); inferred demographic and risk parameters on HIV-1 transmission dynamics by jointly estimating viral transmission rates across racial/ethnic, age, and transmission risk groups; and modeled the degree of network connectivity by using generalized estimating equations (GEE). Our results indicate that Hispanics/Latinos are most vulnerable to the structure of transmission clusters and serve as a bridge population, acting as recipients of transmissions from Whites (3.0 state changes/year) and from Blacks (2.6 state changes/year) as well as sources of transmissions to Whites (1.8 state changes/year) and to Blacks (1.2 state changes/year). There were high rates of transmission and high network connectivity between younger and older Hispanics/Latinos as well as between younger and older Blacks. Prevention and intervention efforts are needed for transmission clusters that involve younger racial/ethnic minorities, in particular Hispanic/Latino youth, to reduce onward transmission of HIV in Houston.

A disproportionate number of Greenland's Inuit population are chronically infected with Hepatitis B virus (HBV; 5–10%). HBV genotypes B and D are most prevalent in the circumpolar Arctic. Here, we report 39 novel HBV/D sequences from individuals residing in southwestern Greenland. We performed phylodynamic analyses with ancient HBV DNA calibrators to investigate the origin and relationship of these taxa to other HBV sequences. We inferred a substitution rate of 1.4 × 10−5[95% HPD 8.8 × 10−6, 2.0 × 10−5] and a time to the most recent common ancestor of 629 CE [95% HPD 37–1138 CE]. The Greenland taxa form a sister clade to HBV/D2 sequences, specifically New Caledonian and Indigenous Taiwanese sequences. The Greenland sequences share amino acid signatures with subgenotypes D1 and D2 and ~97% sequence identity. Our results suggest the classification of these novel sequences does not fit within the current nomenclature. Thus, we propose these taxa be considered a novel quasi-subgenotype.

In recent years, phylogenetic analysis of HIV sequence data has been used in research studies to investigate transmission patterns between individuals and groups, including analysis of data from HIV prevention clinical trials, in molecular epidemiology, and in public health surveillance programs. Phylogenetic analysis can provide valuable information to inform HIV prevention efforts, but it also has risks, including stigma and marginalization of groups, or potential identification of HIV transmission between individuals. In response to these concerns, an interdisciplinary working group was assembled to address ethical challenges in US-based HIV phylogenetic research. The working group developed recommendations regarding (1) study design; (2) data security, access, and sharing; (3) legal issues; (4) community engagement; and (5) communication and dissemination. The working group also identified areas for future research and scholarship to promote ethical conduct of HIV phylogenetic research.

Accurate understanding of the global spread of emerging viruses is critically important for public health response and for anticipating and preventing future outbreaks. Here, we elucidate when, where and how the earliest sustained SARS-CoV-2 transmission networks became established in Europe and the United States (US). Our results refute prior findings erroneously linking cases in January 2020 with outbreaks that occurred weeks later. Instead, rapid interventions successfully prevented onward transmission of those early cases in Germany and Washington State. Other, later introductions of the virus from China to both Italy and Washington State founded the earliest sustained European and US transmission networks. Our analyses reveal an extended period of missed opportunity when intensive testing and contact tracing could have prevented SARS-CoV-2 from becoming established in the US and Europe., One sentence summary: Sustained SARS-CoV-2 transmission networks became established in Europe and the US several weeks later than previously estimated.

A series of unfortunate events The history of how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread around the planet has been far from clear. Several narratives have been propagated by social media and, in some cases, national policies were forged in response. Now that many thousands of virus sequences are available, two studies analyzed some of the key early events in the spread of SARS-CoV-2. Bedford et al. found that the virus arrived in Washington state in late January or early February. The viral genome from the first case detected had mutations similar to those found in Chinese samples and rapidly spread and dominated subsequent undetected community transmission. The other viruses detected had origins in Europe. Worobey et al. found that early introductions into Germany and the west coast of the United States were extinguished by vigorous public health efforts, but these successes were largely unrecognized. Unfortunately, several major travel events occurred in February, including repatriations from China, with lax public health follow-up. Serial, independent introductions triggered the major outbreaks in the United States and Europe that still hold us in the grip of control measures. Science, this issue p. 571, p. 564, Early SARS-CoV-2 transmission networks in Europe and the United States were extinguished, but later travel introduced more virus that became established., Accurate understanding of the global spread of emerging viruses is critical for public health responses and for anticipating and preventing future outbreaks. Here we elucidate when, where, and how the earliest sustained severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission networks became established in Europe and North America. Our results suggest that rapid early interventions successfully prevented early introductions of the virus from taking hold in Germany and the United States. Other, later introductions of the virus from China to both Italy and Washington state, United States, founded the earliest sustained European and North America transmission networks. Our analyses demonstrate the effectiveness of public health measures in preventing onward transmission and show that intensive testing and contact tracing could have prevented SARS-CoV-2 outbreaks from becoming established in these regions.

Transgender people continue to be at high-risk for HIV acquisition, but little is known about the characteristics of their sexual partners. To address this gap, we examined sociodemographic and sexual characteristics of cisgender men who have sex with men (MSM) on pre-exposure prophylaxis (PrEP) reporting transgender sexual partners. A cohort of 392 MSM in southern California in a randomized clinical trial for PrEP adherence were followed from 2013 to 2016. Multivariable generalized estimating equation and logistic models identified characteristics of MSM reporting transgender sexual partners and PrEP adherence. Only 14 (4%) MSM reported having transgender sexual partners. MSM were more likely to report transgender partners if they were African American, had incident chlamydia, reported injection drug-using sexual partners, or received items for sex. Most associations remained significant in the multivariable model: African American (adjusted odds ratio [AOR] 11.20, P = .01), incident chlamydia (AOR 3.71, P = .04), and receiving items for sex (AOR 5.29, P = .04). There were no significant differences in PrEP adherence between MSM reporting transgender partners and their counterpart. MSM who report transgender sexual partners share characteristics associated with individuals with high HIV prevalence. Identifying this group distinct from larger cohorts of MSM could offer new HIV prevention opportunities for this group of MSM and the transgender community.

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

Protein trafficking in the endosomal system involves the recognition of specific signals within the cytoplasmic domains (CDs) of transmembrane proteins by clathrin adaptors. One such signal is the phosphoserine acidic cluster (PSAC), the prototype of which is in the endoprotease furin. How PSACs are recognized by clathrin adaptors has been controversial. We reported previously that HIV-1 Vpu, which modulates cellular immunoreceptors, contains a PSAC that binds to the μ subunits of clathrin adaptor protein (AP) complexes. Here, we show that the CD of furin binds the μ subunits of AP-1 and AP-2 in a phosphorylation-dependent manner. Moreover, we identify a potential PSAC in a cytoplasmic loop of the cellular transmembrane Serinc3, an inhibitor of the infectivity of retroviruses. The two serines within the PSAC of Serinc3 are phosphorylated by casein kinase II and mediate interaction with the μ subunits in vitro. The sites of these serines vary among mammals in a manner suggesting host–pathogen conflict, yet the Serinc3 PSAC seems dispensable for anti-HIV activity and for counteraction by HIV-1 Nef. The CDs of Vpu and furin and the PSAC-containing loop of Serinc3 each bind the μ subunit of AP-2 (μ2) with similar affinities, but they appear to utilize different basic regions on μ2. The Serinc3 loop requires a region previously reported to bind the acidic plasma membrane lipid phosphatidylinositol 4,5-bisphosphate. These data suggest that the PSACs within different proteins recognize different basic regions on the μ surface, providing the potential to inhibit the activity of viral proteins without necessarily affecting cellular protein trafficking.

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

Summary In exploring the epidemiology of infectious diseases, networks have been used to reconstruct contacts among individuals and/or populations. Summarizing networks using pathogen metadata (e.g. host species and place of isolation) and a phylogenetic tree is a nascent, alternative approach. In this paper, we introduce a tool for reconstructing transmission networks in arbitrary space from phylogenetic information and metadata. Our goals are to provide a means of deriving new insights and infection control strategies based on the dynamics of the pathogen lineages derived from networks and centrality metrics. We created a web-based application, called StrainHub, in which a user can input a phylogenetic tree based on genetic or other data along with characters derived from metadata using their preferred tree search method. StrainHub generates a transmission network based on character state changes in metadata, such as place or source of isolation, mapped on the phylogenetic tree. The user has the option to calculate centrality metrics on the nodes including betweenness, closeness, degree and a new metric, the source/hub ratio. The outputs include the network with values for metrics on its nodes and the tree with characters reconstructed. All of these results can be exported for further analysis. Availability and implementation strainhub.io and https://github.com/abschneider/StrainHub.

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.

PURPOSE OF REVIEW The purpose of this study is to summarize recent advances in public health applications of comparative methods for HIV-1 sequence analysis in real time, including genetic clustering methods. RECENT FINDINGS Over the past 2 years, several groups have reported the deployment of established genetic clustering methods to guide public health decisions for HIV prevention in 'near real time'. However, it remains unresolved how well the readouts of comparative methods like clusters translate to events that are actionable for public health. A small number of recent studies have begun to elucidate the linkage between clusters and HIV-1 incidence, whereas others continue to refine and develop new comparative methods for such applications. SUMMARY Although the use of established methods to cluster HIV-1 sequence databases has become a widespread activity, there remains a critical gap between clusters and public health value.

Summary Combining phylogenetic and network methodologies has the potential to better inform targeted interventions to prevent and treat infectious diseases. This study reconstructed a molecular transmission network for people with recent hepatitis C virus (HCV) infection and modelled the impact of targeting directly acting antiviral (DAA) treatment for HCV in the network. Participants were selected from three Australian studies of recent HCV from 2004 to 2014. HCV sequence data (Core-E2) from participants at the time of recent HCV detection were analysed to infer a network by connecting pairs of sequences whose divergence was ≤.03 substitutions/site. Logistic regression was used to identify factors associated with connectivity. Impact of targeting HCV DAAs at both HIV co-infected and random nodes was simulated (1 million replicates). Among 236 participants, 21% (n=49) were connected in the network. HCV/HIV co-infected participants (47%) were more likely to be connected compared to HCV mono-infected participants (16%) (OR 4.56; 95% CI; 2.13-9.74). Simulations targeting DAA HCV treatment to HCV/HIV co-infected individuals prevented 2.5 times more onward infections than providing DAAs to randomly selected individuals. Results demonstrate that genetic distance-based network analyses can be used to identify characteristics associated with HCV transmission, informing targeted prevention and treatment strategies.

Author(s): Mehta, Sanjay R; Murrell, Ben; Anderson, Christy M; Kosakovsky Pond, Sergei L; Wertheim, Joel O; Young, Jason A; Freitas, Lorri; Richman, Douglas D; Mathews, W Chris; Scheffler, Konrad; Little, Susan J; Smith, Davey M | Abstract: BackgroundBecause recently infected individuals disproportionately contribute to the spread of human immunodeficiency virus (HIV), we evaluated the impact of a primary HIV screening program (the Early Test) implemented in San Diego.MethodsThe Early Test program used combined nucleic acid and serology testing to screen for primary infection targeting local high-risk individuals. Epidemiologic, HIV sequence, and geographic data were obtained from the San Diego County Department of Public Health and the Early Test program. Poisson regression analysis was performed to determine whether the Early Test program was temporally and geographically associated with changes in incident HIV diagnoses. Transmission chains were inferred by phylogenetic analysis of sequence data.ResultsOver time, a decrease in incident HIV diagnoses was observed proportional to the number primary HIV infections diagnosed in each San Diego region (P l .001). Molecular network analyses also showed that transmission chains were more likely to terminate in regions where the program was marketed (P = .002). Although, individuals in these zip codes had infection diagnosed earlier (P = .08), they were not treated earlier (P = .83).ConclusionsThese findings suggests that early HIV diagnoses by this primary infection screening program probably contributed to the observed decrease in new HIV diagnoses in San Diego, and they support the expansion and evaluation of similar programs.

To evaluate if HIV transmission networks could be elucidated from data collected in a short time frame, 131 HIV-1 pol sequences were analyzed which were generated from treatment-naive Korean individuals who were sequentially identified over 1 year. A transmission linkage was inferred when there was a genetic distance

Phylogenetic analysis of pathogens is an increasingly powerful way to reduce the spread of epidemics, including HIV. As a result, phylogenetic approaches are becoming embedded in public health and research programmes, as well as outbreak responses, presenting unique ethical, legal, and social issues that are not adequately addressed by existing bioethics literature. We formed a multidisciplinary working group to explore the ethical issues arising from the design of, conduct in, and use of results from HIV phylogenetic studies, and to propose recommendations to minimise the associated risks to both individuals and groups. We identified eight key ethical domains, within which we highlighted factors that make HIV phylogenetic research unique. In this Review, we endeavoured to provide a framework to assist researchers, public health practitioners, and funding institutions to ensure that HIV phylogenetic studies are designed, done, and disseminated in an ethical manner. Our conclusions also have broader relevance for pathogen phylogenetics. ispartof: LANCET HIV vol:5 issue:11 pages:E656-E666 ispartof: location:Netherlands status: published

Author(s): Wertheim, Joel O; Murrell, Ben; Mehta, Sanjay R; Forgione, Lisa A; Kosakovsky Pond, Sergei L; Smith, Davey M; Torian, Lucia V | Abstract: BackgroundHIV-1 genetic sequences can be used to infer viral transmission history and dynamics. Throughout the United States, HIV-1 sequences from drug resistance testing are reported to local public health departments.MethodsWe investigated whether inferred HIV transmission network dynamics can identify individuals and clusters of individuals most likely to give rise to future HIV cases in a surveillance setting. We used HIV-TRACE, a genetic distance-based clustering tool, to infer molecular transmission clusters from HIV-1 pro/RT sequences from 65736 people in the New York City surveillance registry. Logistic and LASSO regression analyses were used to identify correlates of clustering and cluster growth, respectively. We performed retrospective transmission network analyses to evaluate individual- and cluster-level prioritization schemes for identifying parts of the network most likely to give rise to new cases in the subsequent year.ResultsIndividual-level prioritization schemes predicted network growth better than random targeting. Across the 3600 inferred molecular transmission clusters, previous growth dynamics were superior predictors of future transmission cluster growth compared to individual-level prediction schemes. Cluster-level prioritization schemes considering previous cluster growth relative to cluster size further improved network growth predictions.ConclusionsPrevention efforts based on HIV molecular epidemiology may improve public health outcomes in a US surveillance setting.

Understanding genetic variation in human immunodeficiency virus (HIV) is clinically and immunologically important for patient treatment and vaccine development. We investigated the longitudinal intra-host genetic variation of HIV in over 3,000 individuals in the US National HIV Surveillance System with at least four reported HIV-1 polymerase (pol) sequences. In this population, we identified 149 putative instances of superinfection (i.e. an individual sequentially infected with genetically divergent, polyphyletic viruses). Unexpectedly, we discovered a group of 240 individuals with consecutively sampled viral strains that were >0.015 substitutions/site divergent, despite remaining monophyletic in the phylogeny. Viruses in some of these individuals had a maximum genetic divergence approaching that found between two random, unrelated HIV-1 subtype-B pol sequences within the US population. Individuals with these highly divergent viruses tended to be diagnosed nearly a decade earlier in the epidemic than people with superinfection or virus with less intra-host genetic variation, and they had distinct transmission risk factor profiles. To better understand this genetic variation in cases with extremely divergent, monophyletic viruses, we performed molecular clock phylogenetic analysis. Our findings suggest that, like Hepatitis C virus, extremely divergent HIV lineages can be maintained within an individual and reemerge over a period of years.

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.

Protein trafficking in the endosomal system involves the recognition of specific signals within the cytoplasmic domains (CDs) of transmembrane proteins by clathrin adaptors. One such signal is the phosphoserine acidic cluster (PSAC), the prototype of which is in the endoprotease Furin. How PSACs are recognized by clathrin adaptors has been controversial. We reported previously that HIV-1 Vpu, which modulates cellular immunoreceptors, contains a PSAC that binds to the µ subunits of clathrin adaptor protein (AP) complexes. Here, we show that the CD of Furin binds the µ subunits of AP-1 and AP-2 in a phosphorylation-dependent manner. Moreover, we identify a PSAC in a cytoplasmic loop of the cellular transmembrane Serinc3, an inhibitor of the infectivity of retroviruses. The two serines within the PSAC of Serinc3 are phosphorylated by casein kinase II and mediate interaction with the µ subunits in vitro. The sites of these serines vary among mammals in a manner consistent with host-pathogen conflict, yet the Serinc3-PSAC seems dispensible for anti-HIV activity and for counteraction by HIV-1 Nef. The CDs of Vpu, Furin, and the PSAC-containing loop of Serinc3 each bind the μ subunit of AP-2 (µ2) with similar affinities, but they appear to utilize different basic regions on µ2. The Serinc3 loop requires a region previously reported to bind the acidic plasma membrane lipid phosphatidylinositol-4,5-bisphosphate. These data suggest that the PSACs within different proteins recognize different basic regions on the µ surface, providing the potential to inhibit the activity of viral proteins without necessarily affecting cellular protein trafficking.

Residual viremia is common during antiretroviral therapy (ART) and could be caused by ongoing low-level virus replication or by release of viral particles from infected cells. ART intensification should impact ongoing viral propagation but not virion release. Eighteen acutely infected men were enrolled in a randomized controlled trial and monitored for a median of 107 weeks. Participants started ART with ( n = 9) or without ( n = 9) intensification with maraviroc (MVC) within 90 days of infection. Levels of HIV DNA and cell-free RNA were quantified by droplet digital PCR. Deep sequencing of C2-V3 env , gag , and pol (454 Roche) was performed on longitudinally collected plasma and peripheral blood mononuclear cell (PBMC) samples while on ART. Sequence data were analyzed for evidence of evolution by (i) molecular diversity analysis, (ii) nonparametric test for panmixia, and (iii) tip date randomization within a Bayesian framework. There was a longitudinal decay of HIV DNA after initiation of ART with no difference between MVC intensification groups (−0.08 ± 0.01 versus −0.09 ± 0.01 log 10 copies/week in MVC + versus MVC − groups; P = 0.62). All participants had low-level residual viremia (median, 2.8 RNA copies/ml). Across participants, medians of 56 (interquartile range [IQR], 36 to 74), 29 (IQR, 25 to 35), and 40 (IQR, 31 to 54) haplotypes were generated for env , gag , and pol regions, respectively. There was no clear evidence of viral evolution during ART and no difference in viral diversity or population structure from individuals with or without MVC intensification. Further efforts focusing on elucidating the mechanism(s) of viral persistence in various compartments using recent sequencing technologies are still needed, and potential low-level viral replication should always be considered in cure strategies. IMPORTANCE Residual viremia is common among HIV-infected people on ART. It remains controversial if this viremia is a consequence of propagating infection. We hypothesized that molecular evolution would be detectable during viral propagation and that therapy intensified with the entry inhibitor maraviroc would demonstrate less evolution. We performed a randomized double-blinded treatment trial with 18 acutely infected men (standard ART versus standard ART plus maraviroc). From longitudinally collected blood plasma and cells, levels of HIV DNA and cell-free HIV RNA were quantified by droplet digital PCR, and HIV DNA ( env , gag , and pol coding regions) was deep sequenced (454 Roche). Investigating people who started ART during the earliest stages of their HIV infection, when viral diversity is low, provides an opportunity to detect evidence of viral evolution. Despite using a battery of analytical techniques, no clear and consistent evidence of viral propagation for over 90 weeks of observation could be discerned.

In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoe-leather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, that is, on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from www.github.com/veg/hivtrace, along with the accompanying result visualization module from www.github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens.

BACKGROUND In the United States (US), foreign-born persons are disproportionately affected by HIV and differ epidemiologically from US-born persons with diagnosed HIV infection. Understanding HIV transmission dynamics among foreign-born persons is important to guide HIV prevention efforts for these populations. We conducted molecular transmission network analysis to describe HIV transmission dynamics among foreign-born persons with diagnosed HIV. METHODS Using HIV-1 polymerase nucleotide sequences reported to the US National HIV Surveillance System for persons with diagnosed HIV infection during 2001-2013, we constructed a genetic distance-based transmission network using HIV-TRACE and examined the birth region of potential transmission partners in this network. RESULTS Of 77,686 people, 12,064 (16%) were foreign born. Overall, 28% of foreign-born persons linked to at least one other person in the transmission network. Of potential transmission partners, 62% were born in the United States, 31% were born in the same region as the foreign-born person, and 7% were born in another region of the world. Most transmission partners of male foreign-born persons (63%) were born in the United States, whereas most transmission partners of female foreign-borns (57%) were born in their same world region. DISCUSSION These finding suggests that a majority of HIV infections among foreign-born persons in our network occurred after immigrating to the United States. Efforts to prevent HIV infection among foreign-born persons in the United States should include information of the transmission networks in which these individuals acquire or transmit HIV to develop more targeted HIV prevention interventions.

During primary HIV infection, the presence of minority drug resistance mutations (DRM) may be a consequence of sexual transmission, de novo mutations, or technical errors in identification. Baseline blood samples were collected from 24 HIV-infected antiretroviral-naive, genetically and epidemiologically linked source and recipient partners shortly after the recipient's estimated date of infection. An additional 32 longitudinal samples were available from 11 recipients. Deep sequencing of HIV reverse transcriptase (RT) was performed (Roche/454), and the sequences were screened for nucleoside and nonnucleoside RT inhibitor DRM. The likelihood of sexual transmission and persistence of DRM was assessed using Bayesian-based statistical modeling. While the majority of DRM (>20%) were consistently transmitted from source to recipient, the probability of detecting a minority DRM in the recipient was not increased when the same minority DRM was detected in the source (Bayes factor [BF] = 6.37). Longitudinal analyses revealed an exponential decay of DRM (BF = 0.05) while genetic diversity increased. Our analysis revealed no substantial evidence for sexual transmission of minority DRM (BF = 0.02). The presence of minority DRM during early infection, followed by a rapid decay, is consistent with the “mutation-selection balance” hypothesis, in which deleterious mutations are more efficiently purged later during HIV infection when the larger effective population size allows more efficient selection. Future studies using more recent sequencing technologies that are less prone to single-base errors should confirm these results by applying a similar Bayesian framework in other clinical settings. IMPORTANCE The advent of sensitive sequencing platforms has led to an increased identification of minority drug resistance mutations (DRM), including among antiretroviral therapy-naive HIV-infected individuals. While transmission of DRM may impact future therapy options for newly infected individuals, the clinical significance of the detection of minority DRM remains controversial. In the present study, we applied deep-sequencing techniques within a Bayesian hierarchical framework to a cohort of 24 transmission pairs to investigate whether minority DRM detected shortly after transmission were the consequence of (i) sexual transmission from the source, (ii) de novo emergence shortly after infection followed by viral selection and evolution, or (iii) technical errors/limitations of deep-sequencing methods. We found no clear evidence to support the sexual transmission of minority resistant variants, and our results suggested that minor resistant variants may emerge de novo shortly after transmission, when the small effective population size limits efficient purge by natural selection.

BackgroundMigration and travel are major drivers of the spread of infectious diseases. Geographic proximity and a common language facilitate travel and migration in Mesoamerica, which in turn could affect the spread of HIV in the region.Methods6092 HIV-1 subtype B partial pol sequences sampled from unique antiretroviral treatment-naïve individuals from Mexico (40.7%), Guatemala (24.4%), Honduras (19%), Panama (8.2%), Nicaragua (5.5%), Belize (1.4%), and El Salvador (0.7%) between 2011 and 2016 were included. Phylogenetic and genetic network analyses were performed to infer putative relationships between HIV sequences. The demographic and geographic associations with clustering were analyzed and viral migration patterns were inferred using the Slatkin-Maddison approach on 100 iterations of random subsets of equal number of sequences per location.ResultsA total of 1685/6088 (27.7%) of sequences linked with at least one other sequence, forming 603 putative transmission clusters (range: 2-89 individuals). Clustering individuals were significantly more likely to be younger (median age 29 vs 33years, p10 individuals, including two comprised exclusively of Guatemalans (52 and 89 individuals). Phylogenetic and migration analyses suggested that the Central and Southern regions of Mexico along with Belize were major sources of HIV throughout the region (p

Molecular epidemiology can help clarify the properties and dynamics of HIV-1 transmission networks in both global and regional scales. We studied 143 HIV-1-infected individuals recruited from four medical centers of three cities in South Korea between April 2013 and May 2014. HIV-1 env V3 sequence data were generated (337–793 bp) and analyzed using a pairwise distance-based clustering approach to infer putative transmission networks. Participants whose viruses were ≤2.0% divergent according to Tamura-Nei 93 genetic distance were defined as clustering. We collected demographic, risk, and clinical data and analyzed these data in relation to clustering. Among 143 participants, we identified nine putative transmission clusters of different sizes (range 2–4 participants). The reported risk factor of participants were concordant in only one network involving two participants, that is, both individuals reported homosexual sex as their risk factor. The participants in the other eight networks did not report concordant risk factors, although they were phylogenetically linked. About half of the participants refused to report their risk factor. Overall, molecular epidemiology provides more information to understand local transmission networks and the risks associated with these networks.

Venezuelan equine encephalitis (VEE) complex alphaviruses are important re-emerging arboviruses that cause life-threatening disease in equids during epizootics as well as spillover human infections. We conducted a comprehensive analysis of VEE complex alphaviruses by sequencing the genomes of 94 strains and performing phylogenetic analyses of 130 isolates using complete open reading frames for the nonstructural and structural polyproteins. Our analyses confirmed purifying selection as a major mechanism influencing the evolution of these viruses as well as a confounding factor in molecular clock dating of ancestors. Times to most recent common ancestors (tMRCAs) could be robustly estimated only for the more recently diverged subtypes; the tMRCA of the ID/IAB/IC/II and IE clades of VEE virus (VEEV) were estimated at ca. 149–973 years ago. Evolution of the IE subtype has been characterized by a significant evolutionary shift from the rest of the VEEV complex, with an increase in structural protein substitutions that are unique to this group, possibly reflecting adaptation to its unique enzootic mosquito vector Culex (Melanoconion) taeniopus. Our inferred tree topologies suggest that VEEV is maintained primarily in situ, with only occasional spread to neighboring countries, probably reflecting the limited mobility of rodent hosts and mosquito vectors., Author summary The Venezuelan equine encephalitis (VEE) complex comprises a broadly distributed group of alphaviruses in the Americas that have the potential to emerge and cause severe disease. Historically, VEE complex viruses have caused recurring outbreaks of human and equine encephalitis in Central and South America as well as Mexico, with at least one outbreak resulting in movement of the virus to the southern United States. We present the most comprehensive phylogenetic analysis of complete genomic sequences of the most prominent member of the VEE complex, VEE virus (VEEV). We were able to identify the major forces influencing VEEV evolution, and using the inferred phylogenies we determined that VEEV evolves in geographically segregated lineages with enzootic transmission between rodents and mosquitoes apparently limiting its spread.

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.

Despite evidence of smallpox in antiquity, a new study of a 350 year-old Lithuanian child mummy suggests that the global viral genetic diversity circulating during the 20th century was only around 200 years old.

Test-and-treat programs are central to the global control of HIV, but transmitted drug resistance threatens the effectiveness of these programs. HIV mutations conferring resistance to antiretroviral drugs reduce replicative fitness in vitro, but their effect on propagation in vivo is less understood. Here, we estimate transmission fitness of these mutations in antiretroviral-naïve populations in the U.S. National HIV Surveillance System by comparing their frequency of clustering in a genetic transmission network relative with wild-type viruses. The large dataset (66,221 persons), comprising 30,196 antiretroviral-naïve persons, permitted the evaluation of sixty-nine resistance mutations. Decreased transmission fitness was demonstrated for twenty-three mutations, including M184V. In contrast, many high prevalence mutations (e.g. K103N, Y181C, and L90M) had transmission fitness that was indistinguishable from or exceeded wild-type fitness, permitting the establishment of large, self-sustaining drug resistance reservoirs. We highlight implications of these findings on strategies to preserve global treatment effectiveness.

ObjectiveSexual partner concurrency is common among MSM and may increase the probability of HIV transmission during recent (acute or early) infection. We examined the relationship between concurrency and HIV transmission network characteristics (proxies for HIV transmission) among MSM with recent HIV infection.DesignObservational study integrating behavioral, clinical, and molecular epidemiology.MethodsWe inferred a partial HIV transmission network using 986 HIV-1 pol sequences obtained from HIV-infected individuals in San Diego, California (1996-2015). We further analyzed data from 285 recently HIV-infected MSM in the network who provided information on up to three sexual partners in the past 3 months, including the timing of intercourse with each partner. Concurrency was defined as sexual partners overlapping in time. Logistic and negative binomial regressions were used to investigate the link between concurrency and HIV transmission network characteristics (i.e. clustering and degree or number of connections to others in the network) among these MSM.ResultsOf recently HIV-infected MSM (n = 285), 54% reported concurrent partnerships and 54% were connected by at least one putative transmission link to others (i.e. clustered) in the network (median degree = 1.0; interquartile range: 0.0-3.0). Concurrency was positively associated with HIV transmission network clustering (adjusted odds ratio = 1.83, 95% confidence interval: 1.08, 3.10) and degree (adjusted incidence rate ratio = 1.48, 95% confidence interval: 1.02, 2.15).ConclusionOur findings provide empirical evidence consistent with the hypothesis that concurrency facilitates HIV transmission during recent infection. Interventions to mitigate the impact of concurrency on HIV transmission may help curb the HIV epidemic among MSM.

Author(s): Panichsillapakit, Theppharit; Smith, Davey M; Wertheim, Joel O; Richman, Douglas D; Little, Susan J; Mehta, Sanjay R | Abstract: BackgroundTransmitted drug resistance (TDR) remains an important concern when initiating antiretroviral therapy (ART). Here, we describe the prevalence and phylogenetic relationships of TDR among ART-naive, HIV-infected individuals in San Diego from 1996 to 2013.MethodsData were analyzed from 496 participants of the San Diego Primary Infection Cohort who underwent genotypic resistance testing before initiating therapy. Mutations associated with drug resistance were identified according to the WHO-2009 surveillance list. Network and phylogenetic analyses of the HIV-1 pol sequences were used to evaluate the relationships of TDR within the context of the entire cohort.ResultsThe overall prevalence of TDR was 13.5% (67/496), with an increasing trend over the study period (P = 0.005). TDR was predominantly toward nonnucleoside reverse transcriptase inhibitors (NNRTIs) [8.5% (42/496)], also increasing over the study period (P = 0.005). By contrast, TDR to protease inhibitors and nucleos(t)ide reverse transcriptase inhibitors were 4.4% (22/496) and 3.8% (19/496), respectively, and did not vary with time. TDR prevalence did not differ by age, gender, race/ethnicity, or risk factors. Using phylogenetic analysis, we identified 52 transmission clusters, including 8 with at least 2 individuals sharing the same mutation, accounting for 23.8% (16/67) of the individuals with TDR.ConclusionsBetween 1996 and 2013, the prevalence of TDR significantly increased among recently infected ART-naive individuals in San Diego. Around one-fourth of TDR occurred within clusters of recently infected individuals. These findings highlight the importance of baseline resistance testing to guide selection of ART and for public health monitoring.

It has long been hypothesized that polyomaviruses (PyV; family Polyomaviridae ) codiverged with their animal hosts. In contrast, recent analyses suggested that codivergence may only marginally influence the evolution of PyV. We reassess this question by focusing on a single lineage of PyV infecting hominine hosts, the Merkel cell polyomavirus (MCPyV) lineage. By characterizing the genetic diversity of these viruses in seven African great ape taxa, we show that they exhibit very strong host specificity. Reconciliation analyses identify more codivergence than noncodivergence events. In addition, we find that a number of host and PyV divergence events are synchronous. Collectively, our results support codivergence as the dominant process at play during the evolution of the MCPyV lineage. More generally, our results add to the growing body of evidence suggesting an ancient and stable association of PyV and their animal hosts. IMPORTANCE The processes involved in viral evolution and the interaction of viruses with their hosts are of great scientific interest and public health relevance. It has long been thought that the genetic diversity of double-stranded DNA viruses was generated over long periods of time, similar to typical host evolutionary timescales. This was also hypothesized for polyomaviruses (family Polyomaviridae ), a group comprising several human pathogens, but this remains a point of controversy. Here, we investigate this question by focusing on a single lineage of polyomaviruses that infect both humans and their closest relatives, the African great apes. We show that these viruses exhibit considerable host specificity and that their evolution largely mirrors that of their hosts, suggesting that codivergence with their hosts played a major role in their diversification. Our results provide statistical evidence in favor of an association of polyomaviruses and their hosts over millions of years.

The aim of the analysis was to explore HIV-1 subtype diversity in the United States and understand differences in prevalence of non-B subtypes and circulating recombinant forms (CRFs) between demographic/risk groups and over time.We included HIV-1 polymerase sequences reported to the National HIV Surveillance System for HIV infections diagnosed during 2006-2013 in seven states. We assigned subtype or CRF using the automated subtyping tool COMET, assessed subtype/CRF prevalence by demographic characteristics and country of birth, and determined changes in subtype/CRF by HIV diagnosis year.Of 32,968 sequences, 30,757 (93.3%) were subtype B. The most common non-B subtypes and CRFs were C (1.6%), CRF02_AG (1.4%), A (0.6%), CRF01_AE (0.5%), and G (0.3%). Elevated percentages of non-B infections occurred among persons aged13 years at diagnosis (40.9%), Asians (32.1%), persons born outside the United States (22.6%), and persons with infection attributable to heterosexual contact (12.0%-15.0%). Prevalence of non-B infections increased from 5.9% in 2006 to 8.5% in 2013.Subtype B continues to predominate in the United States. However, the percentage of non-B infections has grown in recent years, and numerous demographic subgroups have much higher prevalence. Subgroups and areas with high prevalence of non-B infections might represent sub-epidemics meriting further investigation.

Background Sexually transmitted infections spread across contact networks. Partner elicitation and notification are commonly used public health tools to identify, notify, and offer testing to persons linked in these contact networks. For HIV-1, a rapidly evolving pathogen with low per-contact transmission rates, viral genetic sequences are an additional source of data that can be used to infer or refine transmission networks. Methods and Findings The New York City Department of Health and Mental Hygiene interviews individuals newly diagnosed with HIV and elicits names of sexual and injection drug using partners. By law, the Department of Health also receives HIV sequences when these individuals enter healthcare and their physicians order resistance testing. Our study used both HIV sequence and partner naming data from 1342 HIV-infected persons in New York City between 2006 and 2012 to infer and compare sexual/drug-use named partner and genetic transmission networks. Using these networks, we determined a range of genetic distance thresholds suitable for identifying potential transmission partners. In 48% of cases, named partners were infected with genetically closely related viruses, compatible with but not necessarily representing or implying, direct transmission. Partner pairs linked through the genetic similarity of their HIV sequences were also linked by naming in 53% of cases. Persons who reported high-risk heterosexual contact were more likely to name at least one partner with a genetically similar virus than those reporting their risk as injection drug use or men who have sex with men. Conclusions We analyzed an unprecedentedly large and detailed partner tracing and HIV sequence dataset and determined an empirically justified range of genetic distance thresholds for identifying potential transmission partners. We conclude that genetic linkage provides more reliable evidence for identifying potential transmission partners than partner naming, highlighting the importance and complementarity of both epidemiological and molecular genetic surveillance for characterizing regional HIV-1 epidemics., Author Summary Understanding the path over which viruses such as HIV have been transmitted may be crucial for directing public health resources and guiding policy decisions. Contact tracing of named sexual and injection drug-use partners of people recently diagnosed with HIV is an indispensible tool for reconstructing this transmission network. Viral genetic sequence data—routinely collected by public health agencies—can also be used to infer the dynamics of HIV transmission. We analyzed partner naming and viral genetic sequence data in 1342 people living with HIV in New York City reported to the New York City Department of Health and Mental Hygiene between 2006 and 2012. Genetically linked partners were more likely to be named partners than named partners were to be genetically linked. This finding indicates that genetic sequence data are better than partner naming data for reconstructing this viral transmission network. Importantly, the success rate in naming a genetically linked partner varied by transmission risk category (e.g., men who have sex with men, heterosexuals, and injection drug users). This study validates the use viral genetic sequences in reconstructing these viral transmission networks in a public health surveillance setting.

Objective: To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. Design: HIV-1 pol sequence data were analyzed to infer the local transmission network. Methods: We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions. Results: HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p=0.014 and p=0.0455, respectively) and predicted risk of transmission (p,0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p,0.05). Conclusions: Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.