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Background: Accurate prevalence estimates of drug use and its harms are important to characterize burden and develop interventions to reduce negative health outcomes and disparities. Lack of a sampling frame for marginalized/stigmatized populations, including persons who use drugs (PWUD) in rural settings, makes this challenging. Respondent-driven sampling (RDS) is frequently used to recruit PWUD. However, the validity of RDS-generated population-level prevalence estimates relies on assumptions that should be evaluated., Methods: RDS was used to recruit PWUD across seven Rural Opioid Initiative studies between 2018-2020. To evaluate RDS assumptions, we computed recruitment homophily and design effects, generated convergence and bottleneck plots, and tested for recruitment and degree differences. We compared sample proportions with three RDS-adjusted estimators (two variations of RDS-I and RDS-II) for five variables of interest (past 30-day use of heroin, fentanyl, and methamphetamine; past 6-month homelessness; and being positive for hepatitis C virus (HCV) antibody) using linear regression with robust confidence intervals. We compared regression estimates for the associations between HCV positive antibody status and (a) heroin use, (b) fentanyl use, and (c) age using RDS-1 and RDS-II probability weights and no weights using logistic and modified Poisson regression and random-effects meta-analyses., Results: Among 2,842 PWUD, median age was 34 years and 43% were female. Most participants (54%) reported opioids as their drug of choice, however regional differences were present (e.g., methamphetamine range: 4-52%). Many recruitment chains were not long enough to achieve sample equilibrium. Recruitment homophily was present for some variables. Differences with respect to recruitment and degree varied across studies. Prevalence estimates varied only slightly with different RDS weighting approaches, most confidence intervals overlapped. Variations in measures of association varied little based on weighting approach., Conclusions: RDS was a useful recruitment tool for PWUD in rural settings. However, several violations of key RDS assumptions were observed which slightly impacts estimation of proportion although not associations., (© 2024. The Author(s).)

Effective infectious disease surveillance in high-risk regions is critical for clinical care and pandemic preemption; however, few clinical diagnostics are available for the wide range of potential human pathogens. Here, we conduct unbiased metagenomic sequencing of 593 samples from febrile Nigerian patients collected in three settings: i) population-level surveillance of individuals presenting with symptoms consistent with Lassa Fever (LF); ii) real-time investigations of outbreaks with suspected infectious etiologies; and iii) undiagnosed clinically challenging cases. We identify 13 distinct viruses, including the second and third documented cases of human blood-associated dicistrovirus, and a highly divergent, unclassified dicistrovirus that we name human blood-associated dicistrovirus 2. We show that pegivirus C is a common co-infection in individuals with LF and is associated with lower Lassa viral loads and favorable outcomes. We help uncover the causes of three outbreaks as yellow fever virus, monkeypox virus, and a noninfectious cause, the latter ultimately determined to be pesticide poisoning. We demonstrate that a local, Nigerian-driven metagenomics response to complex public health scenarios generates accurate, real-time differential diagnoses, yielding insights that inform policy., (© 2023. Springer Nature Limited.)

Inference of effective population size from genomic data can provide unique information about demographic history and, when applied to pathogen genetic data, can also provide insights into epidemiological dynamics. The combination of nonparametric models for population dynamics with molecular clock models which relate genetic data to time has enabled phylodynamic inference based on large sets of time-stamped genetic sequence data. The methodology for nonparametric inference of effective population size is well-developed in the Bayesian setting, but here we develop a frequentist approach based on nonparametric latent process models of population size dynamics. We appeal to statistical principles based on out-of-sample prediction accuracy in order to optimize parameters that control shape and smoothness of the population size over time. Our methodology is implemented in a new R package entitled mlesky . We demonstrate the flexibility and speed of this approach in a series of simulation experiments and apply the methodology to a dataset of HIV-1 in the USA. We also estimate the impact of non-pharmaceutical interventions for COVID-19 in England using thousands of SARS-CoV-2 sequences. By incorporating a measure of the strength of these interventions over time within the phylodynamic model, we estimate the impact of the first national lockdown in the UK on the epidemic reproduction number., (© The Author(s) 2023. Published by Oxford University Press.)

Genetic characterisation of circulating influenza viruses directs annual vaccine strain selection and mitigation of infection spread. We used next-generation sequencing to locally generate whole genomes from 116 A(H1N1)pdm09 and 118 A(H3N2) positive patient swabs collected across Uganda between 2010 and 2018. We recovered sequences from 92% (215/234) of the swabs, 90% (193/215) of which were whole genomes. The newly-generated sequences were genetically and phylogenetically compared to the WHO-recommended vaccines and other Africa strains sampled since 1994. Uganda strain hemagglutinin (n = 206), neuraminidase (n = 207), and matrix protein (MP, n = 213) sequences had 95.23-99.65%, 95.31-99.79%, and 95.46-100% amino acid similarity to the 2010-2020 season vaccines, respectively, with several mutated hemagglutinin antigenic, receptor binding, and N-linked glycosylation sites. Uganda influenza type-A virus strains sequenced before 2016 clustered uniquely while later strains mixed with other Africa and global strains. We are the first to report novel A(H1N1)pdm09 subclades 6B.1A.3, 6B.1A.5(a,b), and 6B.1A.6 (± T120A) that circulated in Eastern, Western, and Southern Africa in 2017-2019. Africa forms part of the global influenza ecology with high viral genetic diversity, progressive antigenic drift, and local transmissions. For a continent with inadequate health resources and where social distancing is unsustainable, vaccination is the best option. Hence, African stakeholders should prioritise routine genome sequencing and analysis to direct vaccine selection and virus control., (© 2023. The Author(s).)

Bats are distinctive among mammals due to their ability to fly, use laryngeal echolocation, and tolerate viruses. However, there are currently no reliable cellular models for studying bat biology or their response to viral infections. Here, we created induced pluripotent stem cells (iPSCs) from two species of bats: the wild greater horseshoe bat (Rhinolophus ferrumequinum) and the greater mouse-eared bat (Myotis myotis). The iPSCs from both bat species showed similar characteristics and had a gene expression profile resembling that of cells attacked by viruses. They also had a high number of endogenous viral sequences, particularly retroviruses. These results suggest that bats have evolved mechanisms to tolerate a large load of viral sequences and may have a more intertwined relationship with viruses than previously thought. Further study of bat iPSCs and their differentiated progeny will provide insights into bat biology, virus host relationships, and the molecular basis of bats' special traits., Competing Interests: Declaration of interests T.P.Z., M.D., and A.G.S. are inventors on patents and patent applications on the use of bat iPS cells, owned by the Icahn School of Medicine at Mount Sinai, New York. T.P.Z. and R.A.Y. are founders and shareholders of Paratus Sciences, and R.A.Y. is a founder and shareholder of Syros Pharmaceuticals, Camp4 Therapeutics, Omega Therapeutics, and Dewpoint Therapeutics. The A.G.S. laboratory has received research support from Pfizer, Senhwa Biosciences, Kenall Manufacturing, Avimex, Johnson & Johnson, Dynavax, 7Hills Pharma, Pharmamar, ImmunityBio, Accurius, Nanocomposix, Hexamer, N-Fold LLC, Model Medicines, and Merck, outside of the reported work. A.G.S. has consulting agreements for the following companies involving cash and/or stock: Vivaldi Biosciences, Contrafect, 7Hills Pharma, Avimex, Vaxalto, Pagoda, Accurius, Esperovax, Farmak, Applied Biological Laboratories, and Pfizer, outside of the reported work. A.G.S. is inventor on patents and patent applications on the use of antivirals and vaccines for the treatment and prevention of virus infections and cancer, owned by the Icahn School of Medicine at Mount Sinai, New York, outside of the reported work. A.M. is the creator of Omics Bioinformatics and owns all the stocks of this company. R.P.S. has a consulting agreement with Sema4 involving cash and is also a stockholder of this company. A.P. and S.D.W.F. are employees of Microsoft Corporation. S.D.W.F. is co-founder of DIOSynVax, Ltd. and an inventor on patent applications on the design of vaccine immunogens for the prevention of virus infections, outside of the reported work., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Climate change is a complex problem involving nonlinearities and feedback that operate across scales. No single discipline or way of thinking can effectively address the climate crisis. Teams of natural scientists, social scientists, engineers, economists, and policymakers must work together to understand, predict, and mitigate the rapidly accelerating impacts of climate change. Transdisciplinary approaches are urgently needed to address the role that microorganisms play in climate change. Here, we demonstrate with case studies how diverse teams and perspectives provide climate-change insight related to the range expansion of emerging fungal pathogens, technological solutions for harmful cyanobacterial blooms, and the prediction of disease-causing microorganisms and their vector populations using massive networks of monitoring stations. To serve as valuable members of a transdisciplinary climate research team, microbiologists must reach beyond the boundaries of their immediate areas of scientific expertise and engage in efforts to build open-minded teams aimed at scalable technologies and adoptable policies.

The COVID-19 pandemic caught the world largely unprepared, including scientific and policy communities. On April 10-13, 2022, researchers across academia, industry, government, and nonprofit organizations met at the Keystone symposium "Lessons from the Pandemic: Responding to Emerging Zoonotic Viral Diseases" to discuss the successes and challenges of the COVID-19 pandemic and what lessons can be applied moving forward. Speakers focused on experiences not only from the COVID-19 pandemic but also from outbreaks of other pathogens, including the Ebola virus, Lassa virus, and Nipah virus. A general consensus was that investments made during the COVID-19 pandemic in infrastructure, collaborations, laboratory and manufacturing capacity, diagnostics, clinical trial networks, and regulatory enhancements-notably, in low-to-middle income countries-must be maintained and strengthened to enable quick, concerted responses to future threats, especially to zoonotic pathogens., (© 2022 New York Academy of Sciences.)

Characterizing the genetic diversity of pathogens within the host promises to greatly improve surveillance and reconstruction of transmission chains. For bacteria, it also informs our understanding of inter-strain competition and how this shapes the distribution of resistant and sensitive bacteria. Here we study the genetic diversity of Streptococcus pneumoniae within 468 infants and 145 of their mothers by deep sequencing whole pneumococcal populations from 3,761 longitudinal nasopharyngeal samples. We demonstrate that deep sequencing has unsurpassed sensitivity for detecting multiple colonization, doubling the rate at which highly invasive serotype 1 bacteria were detected in carriage compared with gold-standard methods. The greater resolution identified an elevated rate of transmission from mothers to their children in the first year of the child's life. Comprehensive treatment data demonstrated that infants were at an elevated risk of both the acquisition and persistent colonization of a multidrug-resistant bacterium following antimicrobial treatment. Some alleles were enriched after antimicrobial treatment, suggesting that they aided persistence, but generally purifying selection dominated within-host evolution. Rates of co-colonization imply that in the absence of treatment, susceptible lineages outcompeted resistant lineages within the host. These results demonstrate the many benefits of deep sequencing for the genomic surveillance of bacterial pathogens., (© 2022. The Author(s).)

Background: Kenya introduced Rotarix ® (GlaxoSmithKline Biologicals, Rixensart, Belgium) vaccination into its national immunization programme beginning July 2014. The impact of this vaccination program on the local epidemiology of various known enteropathogens is not fully understood., Methods: We used a custom TaqMan Array Card (TAC) to screen for 28 different enteropathogens in 718 stools from children aged less than 13 years admitted to Kilifi County Hospital, coastal Kenya, following presentation with diarrhea in 2013 (before vaccine introduction) and in 2016-2018 (after vaccine introduction). Pathogen positivity rate differences between pre- and post-Rotarix ® vaccination introduction were examined using both univariate and multivariable logistic regression models., Results: In 665 specimens (92.6%), one or more enteropathogen was detected, while in 323 specimens (48.6%) three or more enteropathogens were detected. The top six detected enteropathogens were: enteroaggregative Escherichia coli (EAggEC; 42.1%), enteropathogenic Escherichia coli (EPEC; 30.2%), enterovirus (26.9%), rotavirus group A (RVA; 24.8%), parechovirus (16.6%) and norovirus GI/GII (14.4%). Post-rotavirus vaccine introduction, there was a significant increase in the proportion of samples testing positive for EAggEC (35.7% vs. 45.3%, p = 0.014), cytomegalovirus (4.2% vs. 9.9%, p = 0.008), Vibrio cholerae (0.0% vs. 2.3%, p = 0.019), Strongyloides species (0.8% vs. 3.6%, p = 0.048) and Dientamoeba fragilis (2.1% vs. 7.8%, p = 0.004). Although not reaching statistical significance, the positivity rate of adenovirus 40/41 (5.8% vs. 7.3%, p = 0.444), norovirus GI/GII (11.2% vs. 15.9%, p = 0.089), Shigella species (8.7% vs. 13.0%, p = 0.092) and Cryptosporidium spp. (11.6% vs. 14.7%, p = 0.261) appeared to increase post-vaccine introduction. Conversely, the positivity rate of sapovirus decreased significantly post-vaccine introduction (7.8% vs. 4.0%, p = 0.030) while that of RVA appeared not to change (27.4% vs. 23.5%, p = 0.253). More enteropathogen coinfections were detected per child post-vaccine introduction compared to before (mean: 2.7 vs. 2.3; p = 0.0025)., Conclusions: In this rural Coastal Kenya setting, childhood enteropathogen infection burden was high both pre- and post-rotavirus vaccination introduction. Children who had diarrheal admissions post-vaccination showed an increase in coinfections and changes in specific enteropathogen positivity rates. This study highlights the utility of multipathogen detection platforms such as TAC in understanding etiology of childhood acute gastroenteritis in resource-limited regions., (© 2022. The Author(s).)

Genomic characterization of circulating influenza type-A viruses (IAVs) directs the selection of appropriate vaccine formulations and early detection of potentially pandemic virus strains. However, longitudinal data on the genomic evolution and transmission of IAVs in Africa are scarce, limiting Africa's benefits from potential influenza control strategies. We searched seven databases: African Journals Online, Embase, Global Health, Google Scholar, PubMed, Scopus, and Web of Science according to the PRISMA guidelines for studies that sequenced and/or genomically characterized Africa IAVs. Our review highlights the emergence and diversification of IAVs in Africa since 1993. Circulating strains continuously acquired new amino acid substitutions at the major antigenic and potential N-linked glycosylation sites in their hemagglutinin proteins, which dramatically affected vaccine protectiveness. Africa IAVs phylogenetically mixed with global strains forming strong temporal and geographical evolution structures. Phylogeographic analyses confirmed that viral migration into Africa from abroad, especially South Asia, Europe, and North America, and extensive local viral mixing sustained the genomic diversity, antigenic drift, and persistence of IAVs in Africa. However, the role of reassortment and zoonosis remains unknown. Interestingly, we observed substitutions and clades and persistent viral lineages unique to Africa. Therefore, Africa's contribution to the global influenza ecology may be understated. Our results were geographically biased, with data from 63% (34/54) of African countries. Thus, there is a need to expand influenza surveillance across Africa and prioritize routine whole-genome sequencing and genomic analysis to detect new strains early for effective viral control.

Background: Human immunodeficiency virus (HIV) and syphilis infection continue at disproportionate rates among minority men who have sex with men (MSM) in the United States. The integration of HIV genetic clustering with partner services can provide important insight into local epidemic trends to guide interventions and control efforts., Methods: We evaluated contact networks of index persons defined as minority men and transgender women diagnosed with early syphilis and/or HIV infection between 2018 and 2020 in 2 North Carolina regions. HIV clusters were constructed from pol sequences collected through statewide surveillance. A combined "HIV-risk" network, which included persons with any links (genetic or sexual contact) to HIV-positive persons, was evaluated by component size, demographic factors, and HIV viral suppression., Results: In total, 1289 index persons were identified and 55% named 1153 contacts. Most index persons were Black (88%) and young (median age 30 years); 70% had early syphilis and 43% had prevalent HIV infection. Most people with HIV (65%) appeared in an HIV cluster. The combined HIV-risk network (1590 contact network and 1500 cluster members) included 287 distinct components; however, 1586 (51%) were in a single component. Fifty-five percent of network members with HIV had no evidence of viral suppression. Overall, fewer index persons needed to be interviewed to identify 1 HIV-positive member without viral suppression (1.3 vs 4.0 for contact tracing)., Conclusions: Integration of HIV clusters and viral loads illuminate networks with high HIV prevalence, indicating recent and ongoing transmission. Interventions intensified toward these networks may efficiently reach persons for HIV prevention and care re-engagement., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Influenza type-A viruses (IAVs) present a global burden of human respiratory infections and mortality. Genome reassortment is an important mechanism through which epidemiologically novel influenza viruses emerge and a core step in the safe reassortment-incompetent live-attenuated influenza vaccine development. Currently, there are no data on the rate, spatial and temporal distribution, and role of reassortment in the evolution and diversification of IAVs circulating in Africa. We aimed to detect intra-subtype reassortment among Africa pandemic H1N1pdm09 (2009-10), seasonal H1N1pdm09 (2011-20), and seasonal H3N2 viruses and characterize the genomic architecture and temporal and spatial distribution patterns of the resulting reassortants. Our study was nested within the Uganda National Influenza Surveillance Programme. Next-generation sequencing was used to generate whole genomes (WGs) from 234 H1N1pdm09 ( n  = 116) and H3N2 ( n  = 118) viruses sampled between 2010 and 2018 from seven districts in Uganda. We combined our newly generated WGs with 658 H1N1pdm09 and 1131 H3N2 WGs sampled between 1994 and 2020 across Africa and identified reassortants using an automated Graph Incompatibility Based Reassortment Finder software. Viral reassortment rates were estimated using a coalescent reassortant constant population model. Phylogenetic analysis was used to assess the effect of reassortment on viral genetic evolution. We observed a high frequency of intra-subtype reassortment events, 12 · 4 per cent (94/758) and 20 · 9 per cent (256/1,224), and reassortants, 13 · 3 per cent (101/758) and 38 · 6 per cent (472/1,224), among Africa H1N1pdm09 and H3N2 viruses, respectively. H1N1pdm09 reassorted at higher rates (0.1237-0.4255) than H3N2 viruses (0 · 00912-0.0355 events/lineage/year), a case unique to Uganda. Viral reassortants were sampled in 2009 through 2020, except in 2012. 78 · 2 per cent (79/101) of H1N1pdm09 reassortants acquired new non-structural, while 57 · 8 per cent (273/472) of the H3N2 reassortants had new hemagglutinin (H3) genes. Africa H3N2 viruses underwent more reassortment events involving larger reassortant sets than H1N1pdm09 viruses. Viruses with a specific reassortment architecture circulated for up to five consecutive years in specific countries and regions. The Eastern (Uganda and Kenya) and Western Africa harboured 84 · 2 per cent (85/101) and 55 · 9 per cent (264/472) of the continent's H1N1pdm09 and H3N2 reassortants, respectively. The frequent reassortment involving multi-genes observed among Africa IAVs showed the intracontinental viral evolution and diversification possibly sustained by viral importation from outside Africa and/or local viral genomic mixing and transmission. Novel reassortant viruses emerged every year, and some persisted in different countries and regions, thereby presenting a risk of influenza outbreaks in Africa. Our findings highlight Africa as part of the global influenza ecology and the advantage of implementing routine whole-over partial genome sequencing and analyses to monitor circulating and detect emerging viruses. Furthermore, this study provides evidence and heightens our knowledge on IAV evolution, which is integral in directing vaccine strain selection and the update of master donor viruses used in recombinant vaccine development., (© The Author(s) 2022. Published by Oxford University Press.)

Background: Most regions in Indonesia experience annual dengue epidemics. However, the province of East Nusa Tenggara has consistently reported low incidence. We conducted a dengue molecular epidemiology study in Kupang, the capital of the province., Methods: Dengue patients were recruited from May 2016 to September 2017. Dengue virus (DENV) screening was performed using NS1 and immunoglobulin G (IgG)/IgM detection. Serotype was determined using reverse transcription polymerase chain reaction and the envelope genes were sequenced to infer the genetic identity and phylogeny., Results: From 119 patients, dengue was confirmed in 62 (52%). Compared with official data, underreporting of dengue incidence was observed. The majority (36%) of patients were children <10 y of age. Most patients (80%) experienced mild fever. All serotypes were detected, with DENV-3 as the predominant (57%). Kupang DENV-1 isolate was classified as genotype IV, an old and endemic strain, DENV-2 as cosmopolitan, DENV-3 as genotype I and DENV-4 as genotype II. Most isolates showed relatively low evolutionary rates and are closely related with strains from Bali and Timor Leste., Conclusions: The low dengue incidence was most likely caused by sustained local circulation of endemic viruses. This study provides information on the epidemiology of dengue in a low-endemicity setting that should help future mitigation and disease management., (© The Author(s) 2021. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.)

Next generation sequencing (NGS)-based studies have vastly increased our understanding of viral diversity. Viral sequence data obtained from NGS experiments are a rich source of information, these data can be used to study their epidemiology, evolution, transmission patterns, and can also inform drug and vaccine design. Viral genomes, however, represent a great challenge to bioinformatics due to their high mutation rate and forming quasispecies in the same infected host, bringing about the need to implement advanced bioinformatics tools to assemble consensus genomes well-representative of the viral population circulating in individual patients. Many tools have been developed to preprocess sequencing reads, carry-out de novo or reference-assisted assembly of viral genomes and assess the quality of the genomes obtained. Most of these tools however exist as standalone workflows and usually require huge computational resources. Here we present ( V iral G enomes E asily A nalyzed), a Snakemake workflow for analyzing RNA viral genomes. VGEA enables users to map sequencing reads to the human genome to remove human contaminants, split bam files into forward and reverse reads, carry out de novo assembly of forward and reverse reads to generate contigs, pre-process reads for quality and contamination, map reads to a reference tailored to the sample using corrected contigs supplemented by the user's choice of reference sequences and evaluate/compare genome assemblies. We designed a project with the aim of creating a flexible, easy-to-use and all-in-one pipeline from existing/stand-alone bioinformatics tools for viral genome analysis that can be deployed on a personal computer. VGEA was built on the Snakemake workflow management system and utilizes existing tools for each step: fastp (Chen et al., 2018) for read trimming and read-level quality control, BWA (Li & Durbin, 2009) for mapping sequencing reads to the human reference genome, SAMtools (Li et al., 2009) for extracting unmapped reads and also for splitting bam files into fastq files, IVA (Hunt et al., 2015) for de novo assembly to generate contigs, shiver (Wymant et al., 2018) to pre-process reads for quality and contamination, then map to a reference tailored to the sample using corrected contigs supplemented with the user's choice of existing reference sequences, SeqKit (Shen et al., 2016) for cleaning shiver assembly for QUAST, QUAST (Gurevich et al., 2013) to evaluate/assess the quality of genome assemblies and MultiQC (Ewels et al., 2016) for aggregation of the results from fastp, BWA and QUAST. Our pipeline was successfully tested and validated with SARS-CoV-2 ( n  = 20), HIV-1 ( n  = 20) and Lassa Virus ( n  = 20) datasets all of which have been made publicly available. VGEA is freely available on GitHub at: https://github.com/pauloluniyi/VGEA under the GNU General Public License., Competing Interests: Simon D.W. Frost is employed by Microsoft Research and is an Academic Editor for PeerJ. All other authors have declared that no competing interests exist., (©2021 Oluniyi et al.)

Background: We evaluated features of HIV transmission networks involving persons diagnosed during incident HIV infection (IHI) to assess network-based opportunities to curtail onward transmission., Methods: Transmission networks were constructed using partial pol sequences reported to North Carolina surveillance among persons with recent (2014-2018) and past (<2014) HIV diagnoses. IHI were defined as documented acute infections or seroconversion. Demographic and virologic features of HIV genetic clusters (<1.5% pairwise genetic distance) involving ≥ 1 IHI were assessed. Persons with viral genetic links and who had diagnoses >90 days prior to an IHI were further characterized. We assessed named partner outcomes among IHI index persons using contact tracing data., Findings: Of 4,405 HIV diagnoses 2014-2018 with sequences, there were 323 (7%) IHI index persons; most were male (88%), Black (65%), young (68% <30 years), and reported sex with men (MSM) risk (79%). Index persons were more likely to be cluster members compared to non-index persons diagnosed during the same period (72% vs. 49%) . In total, 162 clusters were identified involving 233 IHI, 577 recent diagnoses, and 163 past diagnoses. Most IHI cases (53%) had viral linkages to ≥1 previously diagnosed person without evidence of HIV viral suppression in the year prior to the diagnosis of the IHI index. In contact tracing, only 53% IHI cases named an HIV-positive contact, resulting in 0.5 previously diagnosed persons detected per IHI investigated. When combined with viral analyses, the detection rate of viremic previously diagnosed persons increased to 1.3., Interpretation: Integrating public health with molecular epidemiology, revealed that more than half of IHI have viral links to persons with previously diagnosed unsuppressed HIV infection which was largely unrecognized by traditional contact tracing. Enhanced partner services to support engagement and retention in HIV care and improved case finding supported by rapid phylogenetic analysis are tools to substantially reduce onward HIV transmission., Competing Interests: AMD, MSC, WCM, and JJE report grant funding by the NIH paid to their institution. SDWF reports being a paid employee of Microsoft Health Futures and receiving consulting fees through the NIH grant funding this work. MSC reports leadership roles for the HIV Prevention Trials Network, COVID-19 Prevention Network, Fogarty International Center, and McGill University International Advisory Board member. EV reports consulting fees from the University of North Carolina at Chapel Hill for scientific advice outside of this manuscript. WCM reports leadership roles with the American STD Association and as Editor-in-Chief of the STD journal and receiving honoraria for prior manuscript writing for the NIH. JJE reports clinical research contracts with Gilead Sciences, ViiV Healthcare, and Janssen paid to his institution, consulting fees paid to him by Merck, Janssen, Gilead Sciences, and ViV Healthcare, and participation on a Data Safety and Monitoring Board for Westat Inc. All these relationships occurred outside of this manuscript. AEC, ES, NA, VM, and KE report no competing interests., (© 2021 The Author(s).)

Crimean-Congo hemorrhagic fever virus (CCHFV) is the most geographically widespread of the tick-borne viruses. However, African strains of CCHFV are poorly represented in sequence databases. In addition, almost all sequence data collected to date have been obtained from cases of human disease, while information regarding the circulation of the virus in tick and animal reservoirs is severely lacking. Here, we characterize the complete coding region of a novel CCHFV strain, detected in African blue ticks ( Rhipicephalus (Boophilus) decoloratus ) feeding on cattle in an abattoir in Kampala, Uganda. These cattle originated from a farm in Mbarara, a major cattle-trading hub for much of Uganda. Phylogenetic analysis indicates that the newly sequenced strain belongs to the African genotype II clade, which predominantly contains the sequences of strains isolated from West Africa in the 1950s, and South Africa in the 1980s. Whilst the viral S (nucleoprotein) and L (RNA polymerase) genome segments shared >90% nucleotide similarity with previously reported genotype II strains, the glycoprotein-coding M segment shared only 80% nucleotide similarity with the next most closely related strains, which were derived from ticks in Western India and Northern China. This genome segment also displayed a large number of non-synonymous mutations previously unreported in the genotype II strains. Characterization of this novel strain adds to our limited understanding of the natural diversity of CCHFV circulating in both ticks and in Africa. Such data can be used to inform the design of vaccines and diagnostics, as well as studies exploring the epidemiology and evolution of the virus for the establishment of future CCHFV control strategies.

Background: Chikungunya virus (CHIKV) is an important emerging and re-emerging public health problem worldwide. In Indonesia, where the virus is endemic, epidemiological information from outside of the main islands of Java and Bali is limited., Methodology/principal Findings: Four hundred and seventy nine acutely febrile patients presenting between September 2017-2019 were recruited from three city hospitals situated in Ambon, Maluku; Banjarmasin, Kalimantan; and Batam, Batam Island as part of a multi-site observational study. CHIKV RNA was detected in a single serum sample while a separate sample was IgM positive. IgG seroprevalence was also low across all three sites, ranging from 1.4-3.2%. The single RT-PCR positive sample from this study and 24 archived samples collected during other recent outbreaks throughout Indonesia were subjected to complete coding region sequencing to assess the genetic diversity of Indonesian strains. Phylogenetic analysis revealed all to be of a single clade, which was distinct from CHIKV strains recently reported from neighbouring regions including the Philippines and the Pacific Islands., Conclusions/significance: Chikungunya virus strains from recent outbreaks across Indonesia all belong to a single clade. However, low-level seroprevalence and molecular detection of CHIKV across the three study sites appears to contrast with the generally high seroprevalences that have been reported for non-outbreak settings in Java and Bali, and may account for the relative lack of CHIKV epidemiological data from other regions of Indonesia., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: Commercial funder Microsoft Research provided financial support in the form of a gift to the London School of Hygiene and Tropical Medicine, intended to support salary for SCBS. SDWF is a paid employee of Microsoft Research, which provided support in the form of salary. Microsoft Research had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Controlling the regional re-emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after its initial spread in ever-changing personal contact networks and disease landscapes is a challenging task. In a landscape context, contact opportunities within and between populations are changing rapidly as lockdown measures are relaxed and a number of social activities re-activated. Using an individual-based metapopulation model, we explored the efficacy of different control strategies across an urban-rural gradient in Wales, UK. Our model shows that isolation of symptomatic cases or regional lockdowns in response to local outbreaks have limited efficacy unless the overall transmission rate is kept persistently low. Additional isolation of non-symptomatic infected individuals, who may be detected by effective test-and-trace strategies, is pivotal to reducing the overall epidemic size over a wider range of transmission scenarios. We define an 'urban-rural gradient in epidemic size' as a correlation between regional epidemic size and connectivity within the region, with more highly connected urban populations experiencing relatively larger outbreaks. For interventions focused on regional lockdowns, the strength of such gradients in epidemic size increased with higher travel frequencies, indicating a reduced efficacy of the control measure in the urban regions under these conditions. When both non-symptomatic and symptomatic individuals are isolated or regional lockdown strategies are enforced, we further found the strongest urban-rural epidemic gradients at high transmission rates. This effect was reversed for strategies targeted at symptomatic individuals only. Our results emphasize the importance of test-and-trace strategies and maintaining low transmission rates for efficiently controlling SARS-CoV-2 spread, both at landscape scale and in urban areas.

The people of Indonesia have been afflicted by dengue, a mosquito-borne viral disease, for over 5 decades. The country is the world's largest archipelago with diverse geographic, climatic, and demographic conditions that may impact the dynamics of disease transmissions. A dengue epidemiology study was launched by us to compare and understand the dynamics of dengue and other arboviral diseases in three cities representing western, central, and eastern Indonesia, namely, Batam, Banjarmasin, and Ambon, respectively. A total of 732 febrile patients were recruited with dengue-like illness during September 2017-2019 and an analysis of their demographic, clinical, and virological features was performed. The seasonal patterns of dengue-like illness were found to be different in the three regions. Among all patients, 271 (37.0%) were virologically confirmed dengue, while 152 (20.8%) patients were diagnosed with probable dengue, giving a total number of 423 (57.8%) dengue patients. Patients' age and clinical manifestations also differed between cities. Mostly, mild dengue fever was observed in Batam, while more severe cases were prominent in Ambon. While all dengue virus (DENV) serotypes were detected, distinct serotypes dominated in different locations: DENV-1 in Batam and Ambon, and DENV-3 in Banjarmasin. We also assessed the diagnostic features in the study sites, which revealed different patterns of diagnostic agreements, particularly in Ambon. To detect the possibility of infection with other arboviruses, further testing on 461 DENV RT-PCR-negative samples was performed using pan-flavivirus and -alphavirus RT-PCRs; however, only one chikungunya infection was detected in Ambon. A diverse dengue epidemiology in western, central, and eastern Indonesia was observed, which is likely to be influenced by local geographic, climatic, and demographic conditions, as well as differences in the quality of healthcare providers and facilities. Our study adds a new understanding on dengue epidemiology in Indonesia., (Copyright © 2020 Sasmono, Santoso, Pamai, Yohan, Afida, Denis, Hutagalung, Johar, Hayati, Yudhaputri, Haryanto, Stubbs, Blacklaws, Myint and Frost.)

Next generation sequencing technologies are becoming more accessible and affordable over the years, with entire genome sequences of several pathogens being deciphered in few hours. However, there is the need to analyze multiple genomes within a short time, in order to provide critical information about a pathogen of interest such as drug resistance, mutations and genetic relationship of isolates in an outbreak setting. Many pipelines that currently do this are stand-alone workflows and require huge computational requirements to analyze multiple genomes. We present an automated and scalable pipeline called BAGEP for monomorphic bacteria that performs quality control on FASTQ paired end files, scan reads for contaminants using a taxonomic classifier, maps reads to a reference genome of choice for variant detection, detects antimicrobial resistant (AMR) genes, constructs a phylogenetic tree from core genome alignments and provide interactive short nucleotide polymorphism (SNP) visualization across core genomes in the data set. The objective of our research was to create an easy-to-use pipeline from existing bioinformatics tools that can be deployed on a personal computer. The pipeline was built on the Snakemake framework and utilizes existing tools for each processing step: fastp for quality trimming, snippy for variant calling, Centrifuge for taxonomic classification, Abricate for AMR gene detection, snippy-core for generating whole and core genome alignments, IQ-TREE for phylogenetic tree construction and vcfR for an interactive heatmap visualization which shows SNPs at specific locations across the genomes. BAGEP was successfully tested and validated with Mycobacterium tuberculosis ( n  = 20) and Salmonella enterica serovar Typhi ( n  = 20) genomes which are about 4.4 million and 4.8 million base pairs, respectively. Running these test data on a 8 GB RAM, 2.5 GHz quad core laptop took 122 and 61 minutes on respective data sets to complete the analysis. BAGEP is a fast, calls accurate SNPs and an easy to run pipeline that can be executed on a mid-range laptop; it is freely available on: https://github.com/idolawoye/BAGEP., Competing Interests: Simon D.W. Frost is employed by Microsoft Research and is an Academic Editor for PeerJ., (©2020 Olawoye et al.)

Population structure influences genealogical patterns, however, data pertaining to how populations are structured are often unavailable or not directly observable. Inference of population structure is highly important in molecular epidemiology where pathogen phylogenetics is increasingly used to infer transmission patterns and detect outbreaks. Discrepancies between observed and idealized genealogies, such as those generated by the coalescent process, can be quantified, and where significant differences occur, may reveal the action of natural selection, host population structure, or other demographic and epidemiological heterogeneities. We have developed a fast non-parametric statistical test for detection of cryptic population structure in time-scaled phylogenetic trees. The test is based on contrasting estimated phylogenies with the theoretically expected phylodynamic ordering of common ancestors in two clades within a coalescent framework. These statistical tests have also motivated the development of algorithms which can be used to quickly screen a phylogenetic tree for clades which are likely to share a distinct demographic or epidemiological history. Epidemiological applications include identification of outbreaks in vulnerable host populations or rapid expansion of genotypes with a fitness advantage. To demonstrate the utility of these methods for outbreak detection, we applied the new methods to large phylogenies reconstructed from thousands of HIV-1 partial pol sequences. This revealed the presence of clades which had grown rapidly in the recent past and was significantly concentrated in young men, suggesting recent and rapid transmission in that group. Furthermore, to demonstrate the utility of these methods for the study of antimicrobial resistance, we applied the new methods to a large phylogeny reconstructed from whole genome Neisseria gonorrhoeae sequences. We find that population structure detected using these methods closely overlaps with the appearance and expansion of mutations conferring antimicrobial resistance. [Antimicrobial resistance; coalescent; HIV; population structure.]., (© The Author(s) 2020. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.)

Population-level comparisons of prokaryotic genomes must take into account the substantial differences in gene content resulting from horizontal gene transfer, gene duplication and gene loss. However, the automated annotation of prokaryotic genomes is imperfect, and errors due to fragmented assemblies, contamination, diverse gene families and mis-assemblies accumulate over the population, leading to profound consequences when analysing the set of all genes found in a species. Here, we introduce Panaroo, a graph-based pangenome clustering tool that is able to account for many of the sources of error introduced during the annotation of prokaryotic genome assemblies. Panaroo is available at https://github.com/gtonkinhill/panaroo .

Background: Dengue virus (DENV) infects hundreds of thousands of people annually in Indonesia. However, DENV sequence data from the country are limited, as samples from outbreaks must be shipped across long-distances to suitably equipped laboratories to be sequenced. This approach is time-consuming, expensive, and frequently results in failure due to low viral load or degradation of the RNA genome., Methods: We evaluated a method designed to address this challenge, using the 'Primal Scheme' multiplex PCR tiling approach to rapidly generate short, overlapping amplicons covering the complete DENV coding-region, and sequencing the amplicons on the portable Nanopore MinION device. The resulting sequence data was assessed in terms of genome coverage, consensus sequence accuracy and by phylogenetic analysis., Results: The multiplex approach proved capable of producing near complete coding-region coverage from all samples tested ([Formula: see text] = 99.96%, n = 18), 61% of which could not be fully amplified using the current, long-amplicon PCR, approach. Nanopore-generated consensus sequences were found to be between 99.17-99.92% identical to those produced by high-coverage Illumina sequencing. Consensus accuracy could be improved by masking regions below 20X coverage depth (99.69-99.92%). However, coding-region coverage was reduced at this depth ([Formula: see text] = 93.48%). Nanopore and Illumina consensus sequences generated from the same samples formed monophyletic clades on phylogenetic analysis, and Indonesian consensus sequences accurately clustered by geographical origin., Conclusion: The multiplex, short-amplicon approach proved superior for amplifying DENV genomes from clinical samples, particularly when the virus was present at low concentrations. The accuracy of Nanopore-generated consensus sequences from these amplicons was sufficient for identifying the geographic origin of the samples, demonstrating that the approach can be a useful tool for identifying and monitoring DENV clades circulating in low-resource settings across Indonesia. However, the inaccuracies in Nanopore-generated consensus sequences mean that the approach may not be appropriate for higher resolution transmission studies, particularly when more accurate sequencing technologies are available.

Since the 1990s, several distinct clusters of human immunodeficiency virus-type 1 (HIV-1) CRF01&#95;AE related to a large epidemic in China have been identified, but it is yet poorly understood whether its transmission has dispersed globally. We aimed to characterize and quantify the genetic relationship of HIV-1 CRF01&#95;AEs circulating in China and other countries. Using representative sequences of Chinese clusters as queries, all relevant CRF01&#95;AE pol sequences in two large databases (the Los Alamos HIV sequence database and the UK HIV Drug Resistance Database) were selected with the online basic local alignment search (BLAST) tool. Phylogenetic and phylogeographic analyses were then carried out to characterize possible linkage of CRF01&#95;AE strains between China and the rest of the world. We identified that 269 strains isolated in other parts of the world were associated with five major Chinese CRF01&#95;AE clusters. 80.7% were located within CN.01AE.HST/IDU-2, most of which were born in Southeast Asia. 17.8% were clustered with CN.01AE.MSM-4 and -5. Two distinct sub-clusters associated with Chinese men who have sex with men (MSM) emerged in HK-United Kingdom and Japan after 2000. Our analysis suggests that HIV-1 CRF01&#95;AE strains related to viral transmission in China were initially brought to the United Kingdom or other countries during the 1990s by Asian immigrants or returning international tourists from Southeast Asia, and then after having circulated among MSM in China for several years, these Chinese strains dispersed outside again, possibly through MSM network. This study provided evidence of regional and global dispersal of Chinese CRF01&#95;AE strains. It would also help understand the global landscape of HIV epidemic associated with CRF01&#95;AE transmission and highlight the need for further international collaborative study in this field., (Copyright © 2020 An, Han, Zhao, English, Frost, Zhang and Shang.)

HYpothesis testing using PHYlogenies (HyPhy) is a scriptable, open-source package for fitting a broad range of evolutionary models to multiple sequence alignments, and for conducting subsequent parameter estimation and hypothesis testing, primarily in the maximum likelihood statistical framework. It has become a popular choice for characterizing various aspects of the evolutionary process: natural selection, evolutionary rates, recombination, and coevolution. The 2.5 release (available from www.hyphy.org) includes a completely re-engineered computational core and analysis library that introduces new classes of evolutionary models and statistical tests, delivers substantial performance and stability enhancements, improves usability, streamlines end-to-end analysis workflows, makes it easier to develop custom analyses, and is mostly backward compatible with previous HyPhy releases., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

We present fastbaps, a fast solution to the genetic clustering problem. Fastbaps rapidly identifies an approximate fit to a Dirichlet process mixture model (DPM) for clustering multilocus genotype data. Our efficient model-based clustering approach is able to cluster datasets 10-100 times larger than the existing model-based methods, which we demonstrate by analyzing an alignment of over 110 000 sequences of HIV-1 pol genes. We also provide a method for rapidly partitioning an existing hierarchy in order to maximize the DPM model marginal likelihood, allowing us to split phylogenetic trees into clades and subclades using a population genomic model. Extensive tests on simulated data as well as a diverse set of real bacterial and viral datasets show that fastbaps provides comparable or improved solutions to previous model-based methods, while being significantly faster. The method is made freely available under an open source MIT licence as an easy to use R package at https://github.com/gtonkinhill/fastbaps., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Over 40 species of nonhuman primates host simian immunodeficiency viruses (SIVs). In natural hosts, infection is generally assumed to be nonpathogenic due to a long coevolutionary history between host and virus, although pathogenicity is difficult to study in wild nonhuman primates. We used whole-blood RNA-seq and SIV prevalence from 29 wild Ugandan red colobus (Piliocolobus tephrosceles) to assess the effects of SIV infection on host gene expression in wild, naturally SIV-infected primates. We found no evidence for chronic immune activation in infected individuals, suggesting that SIV is not immunocompromising in this species, in contrast to human immunodeficiency virus in humans. Notably, an immunosuppressive gene, CD101, was upregulated in infected individuals. This gene has not been previously described in the context of nonpathogenic SIV infection. This expands the known variation associated with SIV infection in natural hosts and may suggest a novel mechanism for tolerance of SIV infection in the Ugandan red colobus., (Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution 2019. This work is written by US Government employees and is in the public domain in the US.)

Objectives: In many populations, men who have sex with men (MSM) are at a high risk of HIV infection. This study aimed to estimate the burden of HIV, other STIs and risk behaviours among Rwandan MSM., Methods: In this cross-sectional study, we recruited through peer referral men aged between 18 and 60 years, who reported sex with men at least once in the 12 months prior to the survey. Representativeness was increased using 'seeds' from a variety of sources. Signed informed consent was obtained from all participants. Data on demographics, risk behaviours and self-reported STIs were collected through an interviewer-administered questionnaire. We screened all eligible participants for HIV using the Rwanda-approved protocol for rapid HIV detection., Results: 504 MSM were recruited from five major cities in Rwanda. Participants were mostly young (median age 23 years, range 18-55 years) and unmarried (484/504, 96.0%). Thirteen per cent (65/504) of the participants reported past gonorrhoea and/or syphilis infection. Of 504 MSM, 53 (10.5%) reported they were diagnosed and treated for gonorrhoea in the past 12 months and 24 (4.8%) tested positive for HIV. A high proportion (232/504, 46%) reported receiving payment for sex by a man, with almost half of these reporting on more than three occasions (107/232, 46%). Many reported having had an HIV test within the past 12 months (385/504, 76.4%). In multivariate logistic regression models controlling for age, being paid for sex was associated with higher odds of past STI (OR 3.36 (1.82-6.43]; P<0.001) and testing HIV positive (OR 3.13, P<0.05)., Conclusion: Further research is needed to understand the high rate of payment for sex in this population, which appears to be a major risk factor for STI including HIV., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Identifying structure in collections of sequence data sets remains a common problem in genomics. hierBAPS, a popular algorithm for identifying population structure in haploid genomes, has previously only been available as a MATLAB binary. We provide an R implementation which is both easier to install and use, automating the entire pipeline. Additionally, we allow for the use of multiple processors, improve on the default settings of the algorithm, and provide an interface with the ggtree library to enable informative illustration of the clustering results. Our aim is that this package aids in the understanding and dissemination of the method, as well as enhancing the reproducibility of population structure analyses., Competing Interests: No competing interests were disclosed.

The evolution of viral pathogens is shaped by strong selective forces that are exerted during jumps to new hosts, confrontations with host immune responses and antiviral drugs, and numerous other processes. However, while undeniably strong and frequent, adaptive evolution is largely confined to small parts of information-packed viral genomes, and the majority of observed variation is effectively neutral. The predictions and implications of the neutral theory have proven immensely useful in this context, with applications spanning understanding within-host population structure, tracing the origins and spread of viral pathogens, predicting evolutionary dynamics, and modeling the emergence of drug resistance. We highlight the multiple ways in which the neutral theory has had an impact, which has been accelerated in the age of high-throughput, high-resolution genomics.

Background: Venues form part of the sampling frame for time-location sampling, an approach often used for HIV surveillance. While sampling location is often regarded as a nuisance factor, venues may play a central role in structuring risk networks. We investigated individual reports of risk behaviors and infections among men who have sex with men (MSM) attending different venues to examine structuring of HIV risk behaviors. However, teasing apart 'risky people' from 'risky places' is difficult, as individuals cannot be randomized to attend different venues. However, we can emulate this statistically using marginal structural models, which inversely weight individuals according to their estimated probability of attending the venue., Methods: We conducted a cross-sectional survey of 609 MSM patrons of 14 bars in San Diego, California, recruited using the Priorities for Local AIDS Control Efforts (PLACE) methodology, which consists of a multi-level identification and assessment of venues for HIV risk through population surveys., Results and Discussion: Venues differed by many factors, including participants' reported age, ethnicity, number of lifetime male partners, past sexually transmitted infection (STI), and HIV status. In multivariable marginal structural models, venues demonstrated structuring of HIV+ status, past STI, and methamphetamine use, independently of individual-level characteristics., Conclusions: Studies using time-location sampling should consider venue as an important covariate, and the use of marginal structural models may help to identify risky venues. This may assist in widespread, economically feasible and sustainable targeted surveillance and prevention. A more mechanistic understanding of how 'risky venues' emerge and structure risk is needed.

Respondent-driven sampling (RDS) is an approach to sampling design and analysis which utilizes the networks of social relationships that connect members of the target population, using chain-referral. RDS sampling will typically oversample participants with many acquaintances. Naïve estimators, such as the sample average, will thus be biased towards the state of the most highly connected individuals. Current methodology cannot estimate population size from RDS, and promotes inverse probability weighted estimators for population parameters such as HIV prevalence. We propose to use the timing of recruitment, typically collected and discarded, in order to estimate the population size via a counting process model. Once population size and degree frequencies are made available, prevalence can be debiased in a post-stratified framework. We adapt methods developed for inference in epidemiology and software reliability to estimate the population size, degree counts and frequencies. A fundamental advantage of our approach is that it makes the assumptions of the sampling design explicit. This enables verification of the assumptions, maximum likelihood estimation, extension with covariates, and model selection. We develop large-sample theory, proving consistency and asymptotic normality. We further compare our estimators to other estimators in the RDS literature, through simulation and real-world data. In both cases, we find our estimators to outperform current methods. The likelihood problem in the model we present is separable, and thus efficiently solvable. We implement these estimators in an accompanying R package, chords, available on CRAN., (© 2017, The International Biometric Society.)

To characterize HIV-1 transmission dynamics in regions where the burden of HIV-1 is greatest, the 'Phylogenetics and Networks for Generalised HIV Epidemics in Africa' consortium (PANGEA-HIV) is sequencing full-genome viral isolates from across sub-Saharan Africa. We report the first 3,985 PANGEA-HIV consensus sequences from four cohort sites (Rakai Community Cohort Study, n=2,833; MRC/UVRI Uganda, n=701; Mochudi Prevention Project, n=359; Africa Health Research Institute Resistance Cohort, n=92). Next-generation sequencing success rates varied: more than 80% of the viral genome from the gag to the nef genes could be determined for all sequences from South Africa, 75% of sequences from Mochudi, 60% of sequences from MRC/UVRI Uganda, and 22% of sequences from Rakai. Partial sequencing failure was primarily associated with low viral load, increased for amplicons closer to the 3' end of the genome, was not associated with subtype diversity except HIV-1 subtype D, and remained significantly associated with sampling location after controlling for other factors. We assessed the impact of the missing data patterns in PANGEA-HIV sequences on phylogeny reconstruction in simulations. We found a threshold in terms of taxon sampling below which the patchy distribution of missing characters in next-generation sequences has an excess negative impact on the accuracy of HIV-1 phylogeny reconstruction, which is attributable to tree reconstruction artifacts that accumulate when branches in viral trees are long. The large number of PANGEA-HIV sequences provides unprecedented opportunities for evaluating HIV-1 transmission dynamics across sub-Saharan Africa and identifying prevention opportunities. Molecular epidemiological analyses of these data must proceed cautiously because sequence sampling remains below the identified threshold and a considerable negative impact of missing characters on phylogeny reconstruction is expected.

Phylogenetic methods are being increasingly used to help understand the transmission dynamics of measurably evolving viruses, including HIV. Clusters of highly similar sequences are often observed, which appear to follow a 'power law' behaviour, with a small number of very large clusters. These clusters may help to identify subpopulations in an epidemic, and inform where intervention strategies should be implemented. However, clustering of samples does not necessarily imply the presence of a subpopulation with high transmission rates, as groups of closely related viruses can also occur due to non-epidemiological effects such as over-sampling. It is important to ensure that observed phylogenetic clustering reflects true heterogeneity in the transmitting population, and is not being driven by non-epidemiological effects. We qualify the effect of using a falsely identified 'transmission cluster' of sequences to estimate phylodynamic parameters including the effective population size and exponential growth rate under several demographic scenarios. Our simulation studies show that taking the maximum size cluster to re-estimate parameters from trees simulated under a randomly mixing, constant population size coalescent process systematically underestimates the overall effective population size. In addition, the transmission cluster wrongly resembles an exponential or logistic growth model 99% of the time. We also illustrate the consequences of false clusters in exponentially growing coalescent and birth-death trees, where again, the growth rate is skewed upwards. This has clear implications for identifying clusters in large viral databases, where a false cluster could result in wasted intervention resources.

Background: The Philippines has one of the fastest-growing HIV epidemics in the world. Possible reasons for this include increased testing, increased local transmission, and possibly more aggressive strains of HIV. This study sought to determine whether local molecular subtypes of HIV have changed., Methods: Viruses from 81 newly diagnosed, treatment-naive HIV patients were genotyped using protease and reverse transcriptase genes. Demographic characteristics and CD4 count data were collected., Results: The cohort had an average age of 29 years (range 19-51 years), CD4+ count of 255 cells/mm 3 (range 2-744 cells/mm 3 ), and self-reported acquisition time of 2.42 years (range 0.17-8.17 years). All were male, including 79 men who have sex with men (MSM). The genotype distribution was 77% CRF01&#95;AE, 22% B, and 1% C. Previous data from 1985-2000 showed that most Philippine HIV infections were caused by subtype B (71%, n=100), followed by subtype CRF01&#95;AE (20%). Comparison with the present cohort showed a significant shift in subtype (p<0.0001). Comparison between CRF01&#95;AE and B showed a lower CD4+ count (230 vs. 350 cells/mm 3 , p=0.03). Survival data showed highly significant survival associated with antiretroviral (ARV) treatment (p<0.0001), but no significant difference in mortality or CD4 count increase on ARVs between subtypes., Conclusions: The molecular epidemiology of HIV in the Philippines has changed, with the more aggressive CRF01&#95;AE now being the predominant subtype., (Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Hepatitis E virus (HEV) is the most common cause of acute viral hepatitis globally. HEV comprises four genotypes with different geographic distributions and host ranges. We utilize this natural case-control study for investigating the evolution of zoonotic viruses compared to single-host viruses, using 244 near-full-length HEV genomes. Genome-wide estimates of the ratio of nonsynonymous to synonymous evolutionary changes ( dN / dS ratio) located a region of overlapping reading frames, which is subject to positive selection in genotypes 3 and 4. The open reading frames (ORFs) involved have functions related to host-pathogen interaction, so genotype-specific evolution of these regions may reflect their fitness. Bayesian inference of evolutionary rates shows that genotypes 3 and 4 have significantly higher rates than genotype 1 across all ORFs. Reconstruction of the phylogenies of zoonotic genotypes demonstrates significant intermingling of isolates between hosts. We speculate that the genotype-specific differences may result from cyclical adaptation to different hosts in genotypes 3 and 4. IMPORTANCE Hepatitis E virus (HEV) is increasingly recognized as a pathogen that affects both the developing and the developed world. While most often clinically mild, HEV can be severe or fatal in certain demographics, such as expectant mothers. Like many other viral pathogens, HEV has been classified into several distinct genotypes. We show that most of the HEV genome is evolutionarily constrained. One locus of positive selection is unusual in that it encodes two distinct protein products. We are the first to detect positive selection in this overlap region. Genotype 1, which infects humans only, appears to be evolving differently from genotypes 3 and 4, which infect multiple species, possibly because genotypes 3 and 4 are unable to achieve the same fitness due to repeated host jumps., (Copyright © 2017 American Society for Microbiology.)

The emergence of pathogenic RNA viruses into new hosts can have dramatic consequences for both livestock and public health. Here we characterize the viral genetic changes that were observed in a previous study which experimentally adapted a field isolate of duck influenza virus to swine respiratory cells. Both pre-existing and de novo mutations were selected during this adaptation. We compare the in vitro growth dynamics of the adapted virus with those of the original strain as well as all possible reassortants using reverse genetics. This full factorial design showed that viral gene segments are involved in complex epistatic interactions on virus fitness, including negative and sign epistasis. We also identify two point mutations at positions 67 and 113 of the HA2 subunit of the hemagglutinin protein conferring a fast growth phenotype on the naïve avian virus in swine cells. These HA2 mutations enhance the pH dependent, HA-mediated membrane fusion. A global H1 maximum-likelihood phylogenetic analysis, combined with comprehensive ancestry reconstruction and tests for directional selection, confirmed the field relevance of the mutation at position 113 of HA2. Most notably, this mutation was associated with the establishment of the H1 'avian-like' swine influenza lineage, regarded as the most likely to cause the next influenza pandemic in humans. This multidisciplinary approach to study the genetics of viral adaptation provides unique insights on the underlying processes leading to influenza emergence in a new host species, and identifies specific targets for future surveillance and functional studies.

The risk of acquiring sexually transmitted infections (STIs) depends on individual behavior and the network of risky partnerships in which an individual participates. STI epidemics often spread rapidly and primarily among individuals central to transmission networks; and thus they often defy the mass-action principle since incidence is not proportional to the infectious fraction of the population. Here, we estimate the contact network structure for an Atlanta, Georgia community with heterogeneous sexual and drug-related risk behaviors and build a detailed transmission model for HIV through this population. We show that accurate estimation of epidemic incidence requires careful measurement and inclusion of diverse factors including concurrency (having multiple partners), the duration of partnerships, serosorting (preference for partners with matching disease state), and heterogeneity in the number and kinds of partners. In the focal population, we find that injection drug users (IDUs) do not directly cause many secondary infections; yet they bridge the heterosexual and men-who-have-sex-with-men (MSM) populations and are thereby indirectly responsible for extensive transmission., (Copyright © 2010 Elsevier B.V. All rights reserved.)