Utility of various genome lengths in diversity and evolution analyses of Hepatitis E virus.

The aim of this study was to investigate to what extent fragments of the HEV genome could be used for accurate diagnostics and inference of viral population-scale processes. For this, we selected all the published whole genome sequences from the NCBI GenBank and trimmed them to various fragment lengths (ORF1,2,3, ORF1, ORF2, ORF3, 493nt in ORF2 and 148 nt in ORF2). Each of the fragment lengths was used to infer the richness and diversity of the viral sequence types, typing accuracy, and potential use in phylodynamics. The results obtained from the different fragments were compared. We observed that, generally, the longer the nucleic acid fragment used in typing, the better the accuracy in predicting the viral subtype. However, the dominant HEV subtypes circulating in Europe were relatively well classified even by the 493nt fragment, with false negative rates as low as 8 in 1000 typed sequences. Most fragments also give comparable results in analyses of population size, albeit with shorter fragments showing a broader 95% highest posterior density interval and less obvious increase of the viral effective population size. The reconstructed phylogenies of a heterochronous subset indicated a good concordance between all the fragments, with the major clades following similar branching patterns. Furthermore, we have used the HEV sequence data from the Netherlands available in the HEVnet database as a case study for reconstruction of population size changes in the past decades. This data showed that molecular and epidemiological results are concordant and point to an increase in the viral effective population size underlying the observed increase in incidence of acute HEV infection cases. In the absence of whole genome sequencing data, the 493bp fragment can be used for analyzing HEV strains currently circulating in Europe, as it is informative for describing short term population-scale processes.

Phylodynamics of avian influenza A(H5N1) viruses from outbreaks in Brazil.

Our study identified strains of the A/H5N1 virus in analyzed samples of subsistence poultry, wild birds, and mammals, belonging to clade 2.3.4.4b, genotype B3.2, with very high genetic similarity to strains from Chile, Uruguay, and Argentina. This suggests a migratory route for wild birds across the Pacific, explaining the phylogenetic relatedness. The Brazilian samples displayed similarity to strains that had already been previously detected in South America. Phylogeographic analysis suggests transmission of US viruses from Europe and Asia, co-circulating with other lineages in the American continent. As mutations can influence virulence and host specificity, genomic surveillance is essential to detect those changes, especially in critical regions, such as hot spots in the HA, NA, and PB2 sequences. Mutations in the PB2 gene (D701N and Q591K) associated with adaptation and transmission in mammals were detected suggesting a potential zoonotic risk. Nonetheless, resistance to neuraminidase inhibitors (NAIs) was not identified, however, continued surveillance is crucial to detect potential resistance. Our study also mapped the spread of the virus in the Southern hemisphere, identifying possible entry routes and highlighting the importance of surveillance to prevent outbreaks and protect both human and animal populations.

Phylodynamics unveils invading and diffusing patterns of dengue virus serotype-1 in Guangdong, China from 1990 to 2019 under a global genotyping framework.

BACKGROUND: The strong invasiveness and rapid expansion of dengue virus (DENV) pose a great challenge to global public health. However, dengue epidemic patterns and mechanisms at a genetic scale, particularly in term of cross-border transmissions, remain poorly understood. Importation is considered as the primary driver of dengue outbreaks in China, and since 1990 a frequent occurrence of large outbreaks has been triggered by the imported cases and subsequently spread to the western and northern parts of China. Therefore, this study aims to systematically reveal the invasion and diffusion patterns of DENV-1 in Guangdong, China from 1990 to 2019. METHODS: These analyses were performed on 179 newly assembled genomes from indigenous dengue cases in Guangdong, China and 5152 E gene complete sequences recorded in Chinese mainland. The genetic population structure and epidemic patterns of DENV-1 circulating in Chinese mainland were characterized by phylogenetics, phylogeography, phylodynamics based on DENV-1 E-gene-based globally unified genotyping framework. RESULTS: Multiple serotypes of DENV were co-circulating in Chinese mainland, particularly in Guangdong and Yunnan provinces. A total of 189 transmission clusters in 38 clades belonging to 22 subgenotypes of genotype I, IV and V of DENV-1 were identified, with 7 Clades of Concern (COCs) responsible for the large outbreaks since 1990. The epidemic periodicity was inferred from the data to be approximately 3 years. Dengue transmission events mainly occurred from Great Mekong Subregion-China (GMS-China), Southeast Asia (SEA), South Asia Subcontinent (SASC), and Oceania (OCE) to coastal and land border cities respectively in southeastern and southwestern China. Specially, Guangzhou was found to be the most dominant receipting hub, where DENV-1 diffused to other cities within the province and even other parts of the country. Genome phylogeny combined with epidemiological investigation demonstrated a clear local consecutive transmission process of a 5C1 transmission cluster (5C1-CN4) of DENV-1 in Guangzhou from 2013 to 2015, while the two provinces of Guangdong and Yunnan played key roles in ongoing transition of dengue epidemic patterns. In contextualizing within Invasion Biology theories, we have proposed a derived three-stage model encompassing the stages of invasion, colonization, and dissemination, which is supposed to enhance our understanding of dengue spreading patterns. CONCLUSIONS: This study demonstrates the invasion and diffusion process of DENV-1 in Chinese mainland within a global genotyping framework, characterizing the genetic diversities of viral populations, multiple sources of importation, and periodic dynamics of the epidemic. These findings highlight the potential ongoing transition trends from epidemic to endemic status offering a valuable insight into early warning, prevention and control of rapid spreading of dengue both in China and worldwide.

spread.gl: visualising pathogen dispersal in a high-performance browser application.

Phylogeographic analyses are able to exploit the location data associated with sampled molecular sequences to reconstruct the spatio-temporal dispersal history of a pathogen. Visualisation software is commonly used to facilitate the interpretation of the accompanying estimation results, as these are not always easily interpretable. spread.gl is a powerful, open-source and feature-rich browser application that enables smooth, intuitive and user-friendly visualisation of both discrete and continuous phylogeographic inference results, enabling the animation of pathogen geographic dispersal through time. spread.gl can render and combine the visualisation of several data layers, including a geographic layer (e.g., a world map), multiple layers that contain information extracted from the input phylogeny, and different types of layers that represent environmental data. As such, users can explore which environmental data may have shaped pathogen dispersal patterns, that can subsequently be formally tested through more principled statistical analyses. We showcase the visualisation features of spread.gl on several representative pathogen dispersal examples, including the smooth animation of a phylogeny encompassing over 17,000 genomic sequences resulting from a large-scale SARS-CoV-2 analysis.

Population structure and history of Mycobacterium bovis European 3 clonal complex reveal transmission across ecological corridors of unrecognized importance in Portugal.

Mycobacterium bovis causes animal tuberculosis in livestock and wildlife, with an impact on animal health and production, wildlife management, and public health. In this work, we sampled a multi-host tuberculosis community from the official hotspot risk area of Portugal over 16 years, generating the largest available data set in the country. Using phylogenetic and ecological modeling, we aimed to reconstruct the history of circulating lineages across the livestock-wildlife interface to inform intervention and the implementation of genomic surveillance within the official eradication plan. We find evidence for the co-circulation of M. bovis European 1 (Eu1), Eu2, and Eu3 clonal complexes, with Eu3 providing sufficient temporal signal for further phylogenetic investigation. The Eu3 most recent common ancestor (bovine) was dated in the 1990s, subsequently transitioning to wildlife (red deer and wild boar). Isolate clustering based on sample metadata was used to inform phylogenetic inference, unravelng frequent transmission between two clusters that represent an ecological corridor of previously unrecognized importance in Portugal. The latter was associated with transmission at the livestock-wildlife interface toward locations with higher temperature and precipitation, lower agriculture and road density, and lower host densities. This is the first analysis of M. bovis Eu3 complex in Iberia, shedding light on background ecological factors underlying long-term transmission and informing where efforts could be focused within the larger hotspot risk area of Portugal. IMPORTANCE: Efforts to strengthen surveillance and control of animal tuberculosis (TB) are ongoing worlwide. Here, we developed an eco-phylodynamic framework based on discrete phylogenetic approaches informed by M. bovis whole-genome sequence data representing a multi-host transmission system at the livestock-wildlife interface, within a rich ecological landscape in Portugal, to understand transmission processes and translate this knowledge into disease management benefits. We find evidence for the co-circulation of several M. bovis clades, with frequent transmission of the Eu3 lineage among cattle and wildlife populations. Most transition events between different ecological settings took place toward host, climate and land use gradients, underscoring animal TB expansion and a potential corridor of unrecognized importance for M. bovis maintenance. Results stress that animal TB is an established wildlife disease without ecological barriers, showing that control measures in place are insufficient to prevent long-distance transmission and spillover across multi-host communities, demanding new interventions targeting livestock-wildlife interactions.

HIV-1 transmission dynamics among people who inject drugs on the US/Mexico border during the COVID-19 pandemic: a prosepective cohort study.

Background: We examined HIV prevalence and transmission dynamics among people who inject drugs in the U.S./Mexico border region during the COVID-19 pandemic. Methods: People who inject drugs aged ≥18 years from 3 groups were recruited: people who inject drugs who live in San Diego (SD) and engaged in cross-border drug use in Tijuana, Mexico (SD CBDUs), and people who inject drugs in SD and Tijuana (TJ) who did not engage in cross-border drug use (NCBDUs). We computed HIV prevalence at baseline and bivariate incidence-density rates (IR) at 18-month follow-up. Bayesian phylogenetic analysis was used to identify local transmission clusters, estimate their age, and effective reproductive number (Re) over time within the clusters. Findings: At baseline (n = 612), 26% of participants were female, 9% engaged in sex work, and HIV prevalence was 8% (4% SD CBDU, 4% SD NCBDU, 16% TJ NCBDU). Nine HIV seroconversions occurred over 18 months, IR: 1.357 per 100 person-years (95% CI: 0.470, 2.243); 7 in TJ NCBDU and 2 in SD CBDU. Out of 16 identified phylogenetic clusters, 9 (56%) had sequences from both the U.S. and Mexico (mixed-country). The age of three youngest mixed-country dyads (2018-2021) overlapped with the COVID-related US-Mexico border closure in 2020. One large mixed-country cluster (N = 15) continued to grow during the border closure (Re = 4.8, 95% Highest Posterior Density (HPD) 1.5-9.1) with 47% engaging in sex work. Interpretation: Amidst the COVID-19 pandemic and the border closure, cross-border HIV clusters grew. Efforts to end the HIV epidemic in the U.S. should take into account cross-border HIV-1 transmission from Tijuana. Mobile harm reduction services and coordination with municipal HIV programs to initiate anti-retroviral therapy and pre-exposure prophylaxisis are needed to reduce transmission. Funding: This research was supported by the James B. Pendleton Charitable Trust and the San Diego Center for AIDS Research.

Genomic epidemiology of Staphylococcus aureus from the Iberian Peninsula highlights the expansion of livestock associated-CC398 towards wildlife.

Staphylococcus aureus is a versatile pathobiont, exhibiting a broad host range, including humans, other mammals, and avian species. Host specificity determinants, virulence, and antimicrobial resistance genes are often shared by strains circulating at the animal-human interface. While transmission dynamics studies have shown strain exchange between humans and livestock, knowledge of the source, genetic diversification, and transmission drivers of S. aureus in wildlife lag behind. In this work, we explore a wide array of S. aureus genomes from different sources in the Iberian Peninsula to understand population structure, gene content and niche adaptation at the human-livestock-wildlife nexus. Through Bayesian inference, we address the hypothesis that S. aureus strains in wildlife originate from humanized landscapes, either from contact with humans or through interactions with livestock. Phylogenetic reconstruction applied to whole genome sequence data was completed with a dataset of 450 isolates featuring multiple clones from the 1990-2022 period and a subset of CC398 strains representing the 2008-2022 period. Phylodynamic signatures of S. aureus from the Iberian Peninsula suggest widespread circulation of most clones among humans before jumping to other hosts. The number of transitions of CC398 strains within each host category (human, livestock, wildlife) was high (88.26 %), while the posterior probability of transitions from livestock to wildlife was remarkably high (0.99). Microbial genome-wide association analysis did not evidence genome rearrangements nor biomarkers suggesting S. aureus niche adaptation to wildlife, thus supporting recent spill overs. Altogether, our findings indicate that S. aureus isolates collected in the past years from wildlife most likely represent multiple introduction events from livestock. The clonal origin of CC398 and its potential to disseminate and evolve through different animal host species are highlighted, calling for management practices at the livestock-wildlife axis to improve biosecurity and thus restrict S. aureus transmission and niche expansion along gradients of human influence.

High pathogenic avian influenza A(H5) viruses of clade 2.3.4.4b in Europe-Why trends of virus evolution are more difficult to predict.

Since 2016, A(H5Nx) high pathogenic avian influenza (HPAI) virus of clade 2.3.4.4b has become one of the most serious global threats not only to wild and domestic birds, but also to public health. In recent years, important changes in the ecology, epidemiology, and evolution of this virus have been reported, with an unprecedented global diffusion and variety of affected birds and mammalian species. After the two consecutive and devastating epidemic waves in Europe in 2020-2021 and 2021-2022, with the second one recognized as one of the largest epidemics recorded so far, this clade has begun to circulate endemically in European wild bird populations. This study used the complete genomes of 1,956 European HPAI A(H5Nx) viruses to investigate the virus evolution during this varying epidemiological outline. We investigated the spatiotemporal patterns of A(H5Nx) virus diffusion to/from and within Europe during the 2020-2021 and 2021-2022 epidemic waves, providing evidence of ongoing changes in transmission dynamics and disease epidemiology. We demonstrated the high genetic diversity of the circulating viruses, which have undergone frequent reassortment events, providing for the first time a complete overview and a proposed nomenclature of the multiple genotypes circulating in Europe in 2020-2022. We described the emergence of a new genotype with gull adapted genes, which offered the virus the opportunity to occupy new ecological niches, driving the disease endemicity in the European wild bird population. The high propensity of the virus for reassortment, its jumps to a progressively wider number of host species, including mammals, and the rapid acquisition of adaptive mutations make the trend of virus evolution and spread difficult to predict in this unfailing evolving scenario.

The emergence and circulation of human immunodeficiency virus (HIV)-1 subtype C.

Introduction. Human immunodeficiency virus (HIV)-1 subtype C is the most prevalent globally and is thought to have originated in non-human primates in the Democratic Republic of Congo.Hypothesis/Gap Statement. Although the global dominance of HIV-1 subtype C is well established, a thorough understanding of its evolutionary history and transmission dynamics across various risk populations remains elusive. The current knowledge is insufficient to fully capture the global diversification and dissemination of this subtype.Aim. We for the first time sought to investigate the global evolutionary history and spatiotemporal dynamics of HIV-1 subtype C using a selection of maximum-likelihood-based phylodynamic approaches on a total of 1210 near full-length genomic sequences sampled from 32 countries, collected in 4 continents, with sampling dates between 1986-2019 among various risk groups were analysed.Methodology. We subsampled the HIV-1 subtype C genomic datasets based on continent and risk group traits, and performed nucleotide substitution model selection analysis, maximum likelihood (ML) phylogenetic reconstruction, phylogenetic tree topology similarity analysis, temporal signal analysis and traced the timings of viral spread both geographically and by risk group.Results. Based on the phylodynamic analyses of four datasets (full1210, locrisk626, loc562 and risk393), we inferred the time to the most recent common ancestor (TMRCA) in the 1930s and an evolutionary rate of 0.0023 substitutions per site per year. The total number of introduction events of HIV-1 subtype C between continents and between risk groups is estimated to be 71 and 115, respectively. The largest number of introductions occurred from Africa to Europe (n=32), from not-recorded to heterosexual (n=40) and from heterosexual to not-recorded (n=51) risk groups.Conclusion. Our results emphasize that HIV subtype C has mainly spread from Africa to Europe, likely through heterosexual transmission.

The Number and Pattern of Viral Genomic Reassortments are not Necessarily Identifiable from Segment Trees.

Reassortment is an evolutionary process common in viruses with segmented genomes. These viruses can swap whole genomic segments during cellular co-infection, giving rise to novel progeny formed from the mixture of parental segments. Since large-scale genome rearrangements have the potential to generate new phenotypes, reassortment is important to both evolutionary biology and public health research. However, statistical inference of the pattern of reassortment events from phylogenetic data is exceptionally difficult, potentially involving inference of general graphs in which individual segment trees are embedded. In this paper, we argue that, in general, the number and pattern of reassortment events are not identifiable from segment trees alone, even with theoretically ideal data. We call this fact the fundamental problem of reassortment, which we illustrate using the concept of the "first-infection tree," a potentially counterfactual genealogy that would have been observed in the segment trees had no reassortment occurred. Further, we illustrate four additional problems that can arise logically in the inference of reassortment events and show, using simulated data, that these problems are not rare and can potentially distort our observation of reassortment even in small data sets. Finally, we discuss how existing methods can be augmented or adapted to account for not only the fundamental problem of reassortment, but also the four additional situations that can complicate the inference of reassortment.

Molecular characterization of the meq oncogene of Marek's disease virus in vaccinated Brazilian poultry farms reveals selective pressure on prevalent strains.

Marek's disease virus (MDV) has become an increasingly virulent pathogen in the poultry industry despite vaccination efforts to control it. Brazil has experienced a significant rise of Marek's disease (MD) outbreaks in recent years. Our study aimed to analyze the complete meq gene sequences to understand the molecular epidemiological basis of MD outbreaks in Brazilian vaccinated layer farms. We detected a high incidence rate of visceral MD (67.74%) and multiple circulating MDV strains. The most prevalent and geographically widespread genotype presented several clinical and molecular characteristics of a highly virulent strain and evolving under positive selective pressure. Phylogenetic and phylogeographic analysis revealed a closer relationship with strains from the USA and Japan. This study sheds light on the circulation of MDV strains capable of infecting vaccinated birds. We emphasize the urgency of adopting preventive measures to manage MDV outbreaks threatening the poultry farming industry.

Underdetected dispersal and extensive local transmission drove the 2022 mpox epidemic.

The World Health Organization declared mpox a public health emergency of international concern in July 2022. To investigate global mpox transmission and population-level changes associated with controlling spread, we built phylogeographic and phylodynamic models to analyze MPXV genomes from five global regions together with air traffic and epidemiological data. Our models reveal community transmission prior to detection, changes in case reporting throughout the epidemic, and a large degree of transmission heterogeneity. We find that viral introductions played a limited role in prolonging spread after initial dissemination, suggesting that travel bans would have had only a minor impact. We find that mpox transmission in North America began declining before more than 10% of high-risk individuals in the USA had vaccine-induced immunity. Our findings highlight the importance of broader routine specimen screening surveillance for emerging infectious diseases and of joint integration of genomic and epidemiological information for early outbreak control.

Phylodynamic evolution of HIV-1 A6 sub-subtype epidemics in Poland.

The human immunodeficiency virus type 1 (HIV-1) A6 sub-subtype is highly prevalent in Eastern Europe. Over the past decade, the dissemination of the A6 lineage has been expanding in Poland. The recent Russian invasion of Ukraine may further escalate the spread of this sub-subtype. While evolutionary studies using viral sequences have been instrumental in identifying the HIV epidemic patterns, the origins, and dynamics of the A6 sub-subtype in Poland remain to be explored. We analyzed 1185 HIV-1 A6 pol sequences from Poland, along with 8318 publicly available sequences from other countries. For analyses, phylogenetic tree construction, population dynamics inference, Bayesian analysis, and discrete phylogeographic modeling were employed. Of the introduction events to Poland, 69.94% originated from Ukraine, followed by 29.17% from Russia. Most A6 sequences in Poland (53.16%) formed four large clades, with their introductions spanning 1993-2008. Central and Southern Polish regions significantly influenced migration events. Transmissions among men who have sex with men (MSM) emerged as the dominant risk group for virus circulation, representing 72.92% of migration events. Sequences from migrants were found primarily outside the large clades. Past migration from Ukraine has fueled the spread of the A6 sub-subtype and the current influx of war-displaced people maintains the growing national epidemic.

Genetic characterization and molecular epidemiological analysis of enterovirus C99 in China.

Enterovirus C99 (EV-C99) is a newly identified EV serotype within the species Enterovirus C. Few studies on EV-C99 have been conducted globally. More information and research on EV-C99 are needed to assess its genetic characteristics, phylogenetic relationships, and associations with enteroviral diseases. Here, the phylogenetic characteristics of 11 Chinese EV-C99 strains have been reported. The full-length genomic sequences of these 11 strains show 79.4-80.5% nucleotide identity and 91.7-94.3% amino acid (aa) identity with the prototype EV-C99. A maximum likelihood phylogenetic tree constructed based on the entire VP1 coding region identified 13 genotypes (A-M), revealing a high degree of variation among the EV-C99 strains. Phylogeographic analysis showed that the Xinjiang Uygur Autonomous Region is an important source of EV-C99 epidemics in various regions of China. Recombination analysis revealed inter-serotype recombination events of 16 Chinese EV-C99 strains in 5' untranslated regions and 3D regions, resulting in the formation of a single recombination form. Additionally, the Chinese strain of genotype J showed rich aa diversity in the P1 region, indicating that the genotype J of EV-C99 is still going through variable dynamic changes. This study contributes to the global understanding of the EV-C99 genome sequence and holds substantial implications for the surveillance of EV-C99.

Investigating the rise of Omicron variant through genomic surveillance of SARS-CoV-2 infections in a highly vaccinated university population.

Novel variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge as the coronavirus disease 2019 (COVID-19) pandemic extends into its fourth year. Understanding SARS-CoV-2 circulation in university populations is vital for effective interventions in higher education settings and will inform public health policy during pandemics. In this study, we generated 793 whole-genome sequences collected over an entire academic year in a university population in Indiana, USA. We clearly captured the rapidity with which Delta variant was wholly replaced by Omicron variant across the West Lafayette campus over the length of two academic semesters in a community with high vaccination rates. This mirrored the emergence of Omicron throughout the state of Indiana and the USA. Further, phylogenetic analyses demonstrated that there was a more diverse set of potential geographic origins for Omicron viruses introduction into campus when compared to Delta. Lastly, statistics indicated that there was a more significant role for international and out-of-state migration in the establishment of Omicron variants at Purdue. This surveillance workflow, coupled with viral genomic sequencing and phylogeographic analyses, provided critical insights into SARS-CoV-2 transmission dynamics and variant arrival.

Transmission dynamics of drug-resistant tuberculosis in Ningbo, China: an epidemiological and genomic analysis.

Background: Tuberculosis (TB), particularly drug-resistant TB (DR-TB), remains a significant public health concern in Ningbo, China. Understanding its molecular epidemiology and spatial distribution is paramount for effective control. Methods: From December 24, 2020, to March 12, 2023, we collected clinical Mycobacterium tuberculosis (MTB) strains in Ningbo, with whole-genome sequencing performed on 130 MTB strains. We analyzed DR-related gene mutations, conducted phylogenetic and phylodynamic analyses, identified recent transmission clusters, and assessed spatial distribution. Results: Among 130 DR-TB cases, 41% were MDR-TB, 36% pre-XDR-TB, 19% RR-TB, and 3% HR-TB. The phylogenetic tree showed that 90% of strains were Lineage 2 (Beijing genotype), while remaining 10% were Lineage 4 (Euro-American genotype). The spatial analysis identified hotspots of DR-TB in Ningbo's northern region, particularly in traditional urban centers. 31 (24%) of the DR-TB cases were grouped into 7 recent transmission clusters with a large outbreak cluster containing 15 pre-XDR-TB patients. Epidemiological analyses suggested a higher risk of recent DR-TB transmission among young adult patients who frequently visited Internet cafes, game rooms, and factories. Conclusion: Our study provides comprehensive insights into the epidemiology and genetics of DR-TB in Ningbo. The presence of genomic clusters highlights recent transmission events, indicating the need for targeted interventions. These findings are vital for informing TB control strategies in Ningbo and similar settings.

Inferring HIV transmission patterns from viral deep-sequence data via latent typed point processes.

Viral deep-sequencing data play a crucial role toward understanding disease transmission network flows, providing higher resolution compared to standard Sanger sequencing. To more fully utilize these rich data and account for the uncertainties in outcomes from phylogenetic analyses, we propose a spatial Poisson process model to uncover human immunodeficiency virus (HIV) transmission flow patterns at the population level. We represent pairings of individuals with viral sequence data as typed points, with coordinates representing covariates such as gender and age and point types representing the unobserved transmission statuses (linkage and direction). Points are associated with observed scores on the strength of evidence for each transmission status that are obtained through standard deep-sequence phylogenetic analysis. Our method is able to jointly infer the latent transmission statuses for all pairings and the transmission flow surface on the source-recipient covariate space. In contrast to existing methods, our framework does not require preclassification of the transmission statuses of data points, and instead learns them probabilistically through a fully Bayesian inference scheme. By directly modeling continuous spatial processes with smooth densities, our method enjoys significant computational advantages compared to previous methods that rely on discretization of the covariate space. We demonstrate that our framework can capture age structures in HIV transmission at high resolution, bringing valuable insights in a case study on viral deep-sequencing data from Southern Uganda.

Application of phylodynamics to identify spread of antimicrobial-resistant Escherichia coli between humans and canines in an urban environment.

The transmission of antimicrobial resistant bacteria in the urban environment is poorly understood. We utilized genomic sequencing and phylogenetics to characterize the transmission dynamics of antimicrobial resistant Escherichia coli (AMR-Ec) cultured from putative canine (caninep) and human feces present on urban sidewalks in San Francisco, California. We isolated a total of fifty-six AMR-Ec isolates from human (n = 20) and caninep (n = 36) fecal samples from the Tenderloin and South of Market (SoMa) neighborhoods of San Francisco. We then analyzed phenotypic and genotypic antimicrobial resistance (AMR) of the isolates, as well as clonal relationships based on cgMLST and single nucleotide polymorphisms (SNPs) of the core genomes. Using Bayesian inference, we reconstructed the transmission dynamics between humans and caninesp from multiple local outbreak clusters using the marginal structured coalescent approximation (MASCOT). Our results provide evidence for multiple sharing events of AMR-Ec between humans and caninesp. In particular, we found one instance of likely transmission from caninesp to humans as well as an additional local outbreak cluster consisting of one caninep and one human sample. Based on this analysis, it appears that non-human feces act as an important reservoir of clinically relevant AMR-Ec within the urban environment for this study population. This work showcases the utility of genomic epidemiology to reconstruct potential pathways by which antimicrobial resistance spreads.

Estimates of early outbreak-specific SARS-CoV-2 epidemiological parameters from genomic data.

We estimate the basic reproductive number and case counts for 15 distinct Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks, distributed across 11 populations (10 countries and one cruise ship), based solely on phylodynamic analyses of genomic data. Our results indicate that, prior to significant public health interventions, the reproductive numbers for 10 (out of 15) of these outbreaks are similar, with median posterior estimates ranging between 1.4 and 2.8. These estimates provide a view which is complementary to that provided by those based on traditional line listing data. The genomic-based view is arguably less susceptible to biases resulting from differences in testing protocols, testing intensity, and import of cases into the community of interest. In the analyses reported here, the genomic data primarily provide information regarding which samples belong to a particular outbreak. We observe that once these outbreaks are identified, the sampling dates carry the majority of the information regarding the reproductive number. Finally, we provide genome-based estimates of the cumulative number of infections for each outbreak. For 7 out of 11 of the populations studied, the number of confirmed cases is much bigger than the cumulative number of infections estimated from the sequence data, a possible explanation being the presence of unsequenced outbreaks in these populations.

Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong.

Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are often computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare, and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among 5 locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression that we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior density (HPD) and greatly overlap with HPDs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster after training. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models.