DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction.

In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks and patterns of spread is critical to inform public health programs. Projections of transmission growth or decline among specific risk groups can aid in optimizing interventions, particularly when resources are limited. Phylogenetic trees have been widely used in the detection of transmission chains and high-risk populations. Moreover, tree topology and the incorporation of population parameters (phylodynamics) can be useful in reconstructing the evolutionary dynamics of an epidemic across space and time among individuals. We now demonstrate the utility of phylodynamic trees for transmission modeling and forecasting, developing a phylogeny-based deep learning system, referred to as DeepDynaForecast. Our approach leverages a primal-dual graph learning structure with shortcut multi-layer aggregation, which is suited for the early identification and prediction of transmission dynamics in emerging high-risk groups. We demonstrate the accuracy of DeepDynaForecast using simulated outbreak data and the utility of the learned model using empirical, large-scale data from the human immunodeficiency virus epidemic in Florida between 2012 and 2020. Our framework is available as open-source software (MIT license) at github.com/lab-smile/DeepDynaForcast.

Application of Phylodynamic Tools to Inform the Public Health Response to COVID-19: Qualitative Analysis of Expert Opinions.

BACKGROUND: In the wake of the SARS-CoV-2 pandemic, scientists have scrambled to collect and analyze SARS-CoV-2 genomic data to inform public health responses to COVID-19 in real time. Open source phylogenetic and data visualization platforms for monitoring SARS-CoV-2 genomic epidemiology have rapidly gained popularity for their ability to illuminate spatial-temporal transmission patterns worldwide. However, the utility of such tools to inform public health decision-making for COVID-19 in real time remains to be explored. OBJECTIVE: The aim of this study is to convene experts in public health, infectious diseases, virology, and bioinformatics-many of whom were actively engaged in the COVID-19 response-to discuss and report on the application of phylodynamic tools to inform pandemic responses. METHODS: In total, 4 focus groups (FGs) occurred between June 2020 and June 2021, covering both the pre- and postvariant strain emergence and vaccination eras of the ongoing COVID-19 crisis. Participants included national and international academic and government researchers, clinicians, public health practitioners, and other stakeholders recruited through purposive and convenience sampling by the study team. Open-ended questions were developed to prompt discussion. FGs I and II concentrated on phylodynamics for the public health practitioner, while FGs III and IV discussed the methodological nuances of phylodynamic inference. Two FGs per topic area to increase data saturation. An iterative, thematic qualitative framework was used for data analysis. RESULTS: We invited 41 experts to the FGs, and 23 (56%) agreed to participate. Across all the FG sessions, 15 (65%) of the participants were female, 17 (74%) were White, and 5 (22%) were Black. Participants were described as molecular epidemiologists (MEs; n=9, 39%), clinician-researchers (n=3, 13%), infectious disease experts (IDs; n=4, 17%), and public health professionals at the local (PHs; n=4, 17%), state (n=2, 9%), and federal (n=1, 4%) levels. They represented multiple countries in Europe, the United States, and the Caribbean. Nine major themes arose from the discussions: (1) translational/implementation science, (2) precision public health, (3) fundamental unknowns, (4) proper scientific communication, (5) methods of epidemiological investigation, (6) sampling bias, (7) interoperability standards, (8) academic/public health partnerships, and (9) resources. Collectively, participants felt that successful uptake of phylodynamic tools to inform the public health response relies on the strength of academic and public health partnerships. They called for interoperability standards in sequence data sharing, urged careful reporting to prevent misinterpretations, imagined that public health responses could be tailored to specific variants, and cited resource issues that would need to be addressed by policy makers in future outbreaks. CONCLUSIONS: This study is the first to detail the viewpoints of public health practitioners and molecular epidemiology experts on the use of viral genomic data to inform the response to the COVID-19 pandemic. The data gathered during this study provide important information from experts to help streamline the functionality and use of phylodynamic tools for pandemic responses.

Lessons Learned and Yet-to-Be Learned on the Importance of RNA Structure in SARS-CoV-2 Replication.

SARS-CoV-2, the etiological agent responsible for the COVID-19 pandemic, is a member of the virus family Coronaviridae, known for relatively extensive (~30-kb) RNA genomes that not only encode for numerous proteins but are also capable of forming elaborate structures. As highlighted in this review, these structures perform critical functions in various steps of the viral life cycle, ultimately impacting pathogenesis and transmissibility. We examine these elements in the context of coronavirus evolutionary history and future directions for curbing the spread of SARS-CoV-2 and other potential human coronaviruses. While we focus on structures supported by a variety of biochemical, biophysical, and/or computational methods, we also touch here on recent evidence for novel structures in both protein-coding and noncoding regions of the genome, including an assessment of the potential role for RNA structure in the controversial finding of SARS-CoV-2 integration in "long COVID" patients. This review aims to serve as a consolidation of previous works on coronavirus and more recent investigation of SARS-CoV-2, emphasizing the need for improved understanding of the role of RNA structure in the evolution and adaptation of these human viruses.

Early Emergence Phase of SARS-CoV-2 Delta Variant in Florida, US.

SARS-CoV-2, the causative agent of COVID-19, emerged in late 2019. The highly contagious B.1.617.2 (Delta) variant of concern (VOC) was first identified in October 2020 in India and subsequently disseminated worldwide, later becoming the dominant lineage in the US. Understanding the local transmission dynamics of early SARS-CoV-2 introductions may inform actionable mitigation efforts during subsequent pandemic waves. Yet, despite considerable genomic analysis of SARS-CoV-2 in the US, several gaps remain. Here, we explore the early emergence of the Delta variant in Florida, US using phylogenetic analysis of representative Florida and globally sampled genomes. We find multiple independent introductions into Florida primarily from North America and Europe, with a minority originating from Asia. These introductions led to three distinct clades that demonstrated varying relative rates of transmission and possessed five distinct substitutions that were 3-21 times more prevalent in the Florida sample as compared to the global sample. Our results underscore the benefits of routine viral genomic surveillance to monitor epidemic spread and support the need for more comprehensive genomic epidemiology studies of emerging variants. In addition, we provide a model of epidemic spread of newly emerging VOCs that can inform future public health responses.

Severe Acute Respiratory Syndrome Coronavirus 2 Delta Vaccine Breakthrough Transmissibility in Alachua County, Florida.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant has caused a dramatic resurgence in infections in the United Sates, raising questions regarding potential transmissibility among vaccinated individuals. METHODS: Between October 2020 and July 2021, we sequenced 4439 SARS-CoV-2 full genomes, 23% of all known infections in Alachua County, Florida, including 109 vaccine breakthrough cases. Univariate and multivariate regression analyses were conducted to evaluate associations between viral RNA burden and patient characteristics. Contact tracing and phylogenetic analysis were used to investigate direct transmissions involving vaccinated individuals. RESULTS: The majority of breakthrough sequences with lineage assignment were classified as Delta variants (74.6%) and occurred, on average, about 3 months (104 ±â€…57.5 days) after full vaccination, at the same time (June-July 2021) of Delta variant exponential spread within the county. Six Delta variant transmission pairs between fully vaccinated individuals were identified through contact tracing, 3 of which were confirmed by phylogenetic analysis. Delta breakthroughs exhibited broad viral RNA copy number values during acute infection (interquartile range, 1.2-8.64 Log copies/mL), on average 38% lower than matched unvaccinated patients (3.29-10.81 Log copies/mL, P < .00001). Nevertheless, 49% to 50% of all breakthroughs, and 56% to 60% of Delta-infected breakthroughs exhibited viral RNA levels above the transmissibility threshold (4 Log copies/mL) irrespective of time after vaccination. CONCLUSIONS: Delta infection transmissibility and general viral RNA quantification patterns in vaccinated individuals suggest limited levels of sterilizing immunity that need to be considered by public health policies. In particular, ongoing evaluation of vaccine boosters should specifically address whether extra vaccine doses curb breakthrough contribution to epidemic spread.

Optimizing viral genome subsampling by genetic diversity and temporal distribution (TARDiS) for phylogenetics.

SUMMARY: TARDiS is a novel phylogenetic tool for optimal genetic subsampling. It optimizes both genetic diversity and temporal distribution through a genetic algorithm. AVAILABILITY AND IMPLEMENTATION: TARDiS, along with example datasets and a user manual, is available at https://github.com/smarini/tardis-phylogenetics.

Predator-Prey Dynamics of Intra-Host Simian Immunodeficiency Virus Evolution Within the Untreated Host.

The dynamic nature of the SIV population during disease progression in the SIV/macaque model of AIDS and the factors responsible for its behavior have not been documented, largely owing to the lack of sufficient spatial and temporal sampling of both viral and host data from SIV-infected animals. In this study, we detail Bayesian coalescent inference of the changing collective intra-host viral effective population size (Ne ) from various tissues over the course of infection and its relationship with what we demonstrate is a continuously changing immune cell repertoire within the blood. Although the relative contribution of these factors varied among hosts and time points, the adaptive immune response best explained the overall periodic dynamic behavior of the effective virus population. Data exposing the nature of the relationship between the virus and immune cell populations revealed the plausibility of an eco-evolutionary mathematical model, which was able to mimic the large-scale oscillations in Ne through virus escape from relatively few, early immunodominant responses, followed by slower escape from several subdominant and weakened immune populations. The results of this study suggest that SIV diversity within the untreated host is governed by a predator-prey relationship, wherein differing phases of infection are the result of adaptation in response to varying immune responses. Previous investigations into viral population dynamics using sequence data have focused on single estimates of the effective viral population size (Ne ) or point estimates over sparse sampling data to provide insight into the precise impact of immune selection on virus adaptive behavior. Herein, we describe the use of the coalescent phylogenetic frame- work to estimate the relative changes in Ne over time in order to quantify the relationship with empirical data on the dynamic immune composition of the host. This relationship has allowed us to expand on earlier simulations to build a predator-prey model that explains the deterministic behavior of the virus over the course of disease progression. We show that sequential viral adaptation can occur in response to phases of varying immune pressure, providing a broader picture of the viral response throughout the entire course of progression to AIDS.

SARS-CoV-2 shifting transmission dynamics and hidden reservoirs potentially limit efficacy of public health interventions in Italy.

We investigated SARS-CoV-2 transmission dynamics in Italy, one of the countries hit hardest by the pandemic, using phylodynamic analysis of viral genetic and epidemiological data. We observed the co-circulation of multiple SARS-CoV-2 lineages over time, which were linked to multiple importations and characterized by large transmission clusters concomitant with a high number of infections. Subsequent implementation of a three-phase nationwide lockdown strategy greatly reduced infection numbers and hospitalizations. Yet we present evidence of sustained viral spread among sporadic clusters acting as "hidden reservoirs" during summer 2020. Mathematical modelling shows that increased mobility among residents eventually catalyzed the coalescence of such clusters, thus driving up the number of infections and initiating a new epidemic wave. Our results suggest that the efficacy of public health interventions is, ultimately, limited by the size and structure of epidemic reservoirs, which may warrant prioritization during vaccine deployment.

Molecular Evolution of Human Norovirus GII.2 Clusters.

BACKGROUND: The human norovirus GII.2 outbreak during the 2016-2017 winter season was of unprecedented scale and geographic distribution. METHODS: We analyzed 519 complete VP1 gene sequences of the human norovirus GII.2 genotype sampled during the 2016-2017 winter season, as well as prior (dating back to 1976) from 7 countries. Phylodynamic analyses of these sequences were performed using maximum likelihood and Bayesian statistical frameworks in order to estimate viral evolutionary and population dynamics associated with the outbreak. RESULTS: Our results revealed an increase in the genetic diversity of human norovirus GII.2 during the recent Asian outbreak and diversification was characterized by at least eight distinct clusters. Bayesian estimation of viral population dynamics revealed a highly fluctuating effective population size, increasing in frequency during the past 15 years. CONCLUSION: Despite an increasing viral diversity, we found no evidence of an elevated evolutionary rate or significant selection pressure in human norovirus GII.2, indicating viral evolutionary adaptation was not responsible for the volatility of or spread of the virus during this time.

Employing Molecular Phylodynamic Methods to Identify and Forecast HIV Transmission Clusters in Public Health Settings: A Qualitative Study.

Molecular HIV surveillance is a promising public health strategy for curbing the HIV epidemic. Clustering technologies used by health departments to date are limited in their ability to infer/forecast cluster growth trajectories. Resolution of the spatiotemporal dynamics of clusters, through phylodynamic and phylogeographic modelling, is one potential strategy to develop a forecasting tool; however, the projected utility of this approach needs assessment. Prior to incorporating novel phylodynamic-based molecular surveillance tools, we sought to identify possible issues related to their feasibility, acceptability, interpretation, and utility. Qualitative data were collected via focus groups among field experts (n = 17, 52.9% female) using semi-structured, open-ended questions. Data were coded using an iterative process, first through the development of provisional themes and subthemes, followed by independent line-by-line coding by two coders. Most participants routinely used molecular methods for HIV surveillance. All agreed that linking molecular sequences to epidemiological data is important for improving HIV surveillance. We found that, in addition to methodological challenges, a variety of implementation barriers are expected in relation to the uptake of phylodynamic methods for HIV surveillance. The participants identified several opportunities to enhance current methods, as well as increase the usability and utility of promising works-in-progress.

Evaluation of global HIV/SIV envelope gp120 RNA structure and evolution within and among infected hosts.

Lentiviral RNA genomes contain structural elements that play critical roles in viral replication. Although structural features of 5'-untranslated regions have been well characterized, attempts to identify important structures in other genomic regions by Selective 2'-Hydroxyl Acylation analyzed by Primer Extension (SHAPE) have led to conflicting structural and mechanistic conclusions. Previous approaches accounted neither for sequence heterogeneity that is ubiquitous in viral populations, nor for selective constraints operating at the protein level. We developed an approach that augments SHAPE with phylogenetic analyses and applied it to investigate structure in coding regions (cRNA) within the HIV and SIV envelope genes. Analysis of single-genome SHAPE data with phylogenetic information from diverse lentiviral sequences argues against the conservation of a putative global gp120 RNA structure but points to the existence of core RNA sub-structures. Our findings establish a framework for considering sequence heterogeneity and protein function in de novo RNA structure inference approaches.

Insights into the Impact of CD8+ Immune Modulation on Human Immunodeficiency Virus Evolutionary Dynamics in Distinct Anatomical Compartments by Using Simian Immunodeficiency Virus-Infected Macaque Models of AIDS Progression.

A thorough understanding of the role of human immunodeficiency virus (HIV) intrahost evolution in AIDS pathogenesis has been limited by the need for longitudinally sampled viral sequences from the vast target space within the host, which are often difficult to obtain from human subjects. CD8+ lymphocyte-depleted macaques infected with simian immunodeficiency virus (SIV) provide an increasingly utilized model of pathogenesis due to clinical manifestations similar to those for HIV-1 infection and AIDS progression, as well as a characteristic rapid disease onset. Comparison of this model with SIV-infected non-CD8+ lymphocyte-depleted macaques also provides a unique opportunity to investigate the role of CD8+ cells in viral evolution and population dynamics throughout the duration of infection. Using several different phylogenetic methods, we analyzed viral gp120 sequences obtained from extensive longitudinal sampling of multiple tissues and enriched leukocyte populations from SIVmac251-infected macaques with or without CD8+ lymphocyte depletion. SIV evolutionary and selection patterns in non-CD8+ lymphocyte-depleted animals were characterized by sequential population turnover and continual viral adaptation, a scenario readily comparable to intrahost evolutionary patterns during human HIV infection in the absence of antiretroviral therapy. Alternatively, animals that were depleted of CD8+ lymphocytes exhibited greater variation in population dynamics among tissues and cell populations over the course of infection. Our findings highlight the major role for CD8+ lymphocytes in prolonging disease progression through continual control of SIV subpopulations from various anatomical compartments and the potential for greater independent viral evolutionary behavior among these compartments in response to immune modulation.IMPORTANCE Although developments in combined antiretroviral therapy (cART) strategies have successfully prolonged the time to AIDS onset in HIV-1-infected individuals, a functional cure has yet to be found. Improvement of drug interventions for a virus that is able to infect a wide range of tissues and cell types requires a thorough understanding of viral adaptation and infection dynamics within this target milieu. Although it is difficult to accomplish in the human host, longitudinal sampling of multiple anatomical locations is readily accessible in the SIV-infected macaque models of neuro-AIDS. The significance of our research is in identifying the impact of immune modulation, through differing immune selective pressures, on viral evolutionary behavior in a multitude of anatomical compartments. The results provide evidence encouraging the development of a more sophisticated model that considers a network of individual viral subpopulations within the host, with differing infection and transmission dynamics, which is necessary for more effective treatment strategies.