Biology subjects

Wertheim, J. O.

Publications and source records attributed to Wertheim, J. O..

12 recordsLinked to original sources

bioRxiv2026

Dairy cattle movement networks govern the spread and persistence of H5N1 B3.13 in the United States

Avian influenza virus H5N1 is predominantly found in wild and domestic birds. H5N1 genotype B3.13 was first detected in United States dairy cattle in March 2024 and spread through much of the country during 2024 and 2025, resulting in the largest known H5N1 outbreak in domestic mammals. By analysing viral genomic data jointly with historical cattle movement patterns, we find that live cattle movement is the predominant contributor to H5N1 spatial spread, rather than wild or domestic birds. Using phylogeographic methods we estimate that >40% of interstate viral transmissions occurred before B3.13's first detection and >70% occurred before interstate dairy cattle movement restrictions were implemented in April 2024. After this implementation, interstate transmission slowed but within-state spread persisted, driven by local cattle network density and movement volume. Our epidemic simulations demonstrate that the connectivity of counties within and around the Texas Panhandle - where the earliest cases were documented - predisposed the region to become an outbreak epicentre. Counterfactual simulations indicate that interstate restrictions needed to have begun 2-3 months earlier in order to limit the epizootic substantively, given the extent of cryptic spread before detection. Network-informed interventions outperformed geographically-defined containment, but response speed (rather than intervention strength) was the limiting factor in our epidemic models, underscoring the need for surveillance systems capable of detecting pathogen emergence before widespread dissemination.

evolutionary biology↗

bioRxiv2026

The emergence and molecular evolution of H5N1 influenza viruses in United States dairy cattle

Prior to 2024, highly pathogenic avian influenza H5N1 clade 2.3.4.4b viruses circulated predominantly in wild birds and poultry. In 2024 and 2025, 2.3.4.4b genotypes B3.13 and D1.1 were detected in United States dairy cattle. Using whole-genome and segment-specific phylodynamic inference, we estimate that B3.13 and D1.1 spilled over from wild birds into dairy cattle in late 2023 and late 2024, respectively. Spillover occurred shortly after the formation of the reassortant genotypes and was followed by months of cryptic transmission prior to detection. We found that both B3.13 and D1.1 evolved at higher rates in cattle relative to birds, primarily due to relaxed purifying selection. Site-specific analyses identified genomic sites under positive selection in cattle relative to birds, indicating adaptation and likely contributing to improved viral fitness after spillover. Intensified genomic surveillance in dairy cattle is essential as population immunity introduces additional selection pressures, with ever-changing risk for human emergence.

evolutionary biology↗

bioRxiv2025

Dynamics of natural selection preceding human viral epidemics and pandemics.

Using a phylogenetic framework to characterize natural selection, we investigate the hypothesis that zoonotic viruses require adaptation prior to zoonosis to sustain human-to-human transmission. Examining the zoonotic emergence of Ebola virus, Marburg virus, influenza A virus, SARS-CoV, and SARS-CoV-2, we find no evidence of a change in the intensity of natural selection immediately prior to a host switch, compared with typical selection within reservoir hosts. We conclude that extensive pre-zoonotic adaptation is not necessary for human-to-human transmission of zoonotic viruses. In contrast, the reemergence of H1N1 influenza A virus in 1977 showed a change in selection, consistent with the hypothesis of passage in a laboratory setting prior to its reintroduction into the human population, purportedly during a vaccine trial. Holistic phylogenetic analysis of selection regimes can be used to detect evolutionary signals of host switching or laboratory passage, providing insight into the circumstances of past and future viral emergence.

evolutionary biology↗

bioRxiv2024

Genomic Epidemiology of Monkeypox Virus During the 2022 Outbreak in New York City

New York City (NYC) was one of the hotspots of monkeypox virus (MPXV) infections in the United States during the multi-country mpox outbreak in 2022. This study used the most comprehensive dataset to date to investigate the genomic characteristics of MPXV in NYC. We performed Nextclade lineage assignment, phylogenetic and mutational analyses on 1,138 specimens from 748 individuals at the NYC Public Health Lab in the context of 2,968 MPXV sequences sampled globally. Nextclade lineage assignment showed B.1.12 as a NYC specific lineage and phylogenetic analysis showed NYC and North America specific clades. The majority of mutations showed signatures of APOBEC3 activity. When looking at the intra-host genomic diversity for MPXV, distinct MPXV genomic profiles were observed in 6.4% of individuals with multiple sampled specimens, with at least 4.2% of NYC cases due to multiple MPXV infections from distinct viral strains. Further, 13% of the sequences in infected patients had a lack of concordance between epidemiologic and genetic linkages. This study identified NYC-specific MPXV genomic profiles and provided a conservative estimate of simultaneous infections with multiple MPXV variants, likely due to behavioral risk factors during the peak of the outbreak in July 2022. Improving concordance between genomic and epidemiological clusters for mpox investigations may require expanding partnerships with testing labs, clinics, and community groups to enhance the representativeness of MPXV samples that are available for sequencing.

genomics↗

bioRxiv2023

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 has led to increased sampling of related sarbecoviruses circulating primarily in horseshoe bats. These viruses undergo frequent recombination and exhibit spatial structuring across Asia. Employing recombination-aware phylogenetic inference on bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed just [~]1-3 years prior to their emergence in humans. Phylogeographic analyses examining the movement of related sarbecoviruses demonstrate that they traveled at similar rates to their horseshoe bat hosts and have been circulating for thousands of years in Asia. The closest-inferred bat virus ancestor of SARS-CoV likely circulated in western China, and that of SARS-CoV-2 likely circulated in a region comprising southwest China and northern Laos, both a substantial distance from where they emerged. This distance and recency indicate that the direct ancestors of SARS-CoV and SARS-CoV-2 could not have reached their respective sites of emergence via the bat reservoir alone. Our recombination-aware dating and phylogeographic analyses reveal a more accurate inference of evolutionary history than performing only whole-genome or single gene analyses. These results can guide future sampling efforts and demonstrate that viral genomic fragments extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.

evolutionary biology↗

bioRxiv2022

Multiple-trait subsampling for optimized ancestral trait reconstruction

Large datasets along with sampling bias represent a challenge for phylodynamic reconstructions, particularly when the study data are obtained from various heterogeneous sources and/or through convenience sampling. In this study, we evaluate the presence of unbalanced sampled distribution by collection date, location, and risk group of HIV-1 subtype C using a compre-hensive subsampling strategy, and assess their impact on the reconstruction of the viral spatial and risk group dynamics using phylogenetic comparative methods. Our study shows that the most suitable dataset for ancestral trait reconstruction can be obtained through subsampling by collection date, location, and risk group, particularly using multigene datasets. We also demonstrate that sampling bias is inflated when considerable information for a given trait is unavailable or of poor quality, as we observed for the risk group in the analysis of HIV-1 subtype C. In conclusion, we suggest that, even if traits are not well recorded, including them deliberately optimizes the representativeness of the original dataset rather than completely excluding them. Therefore, we advise the inclusion of as many traits as possible with the aid of subsampling approaches in order to optimize the dataset for phylodynamic analysis while reducing the computational burden. This will benefit research communities investigating the evolutionary and spatiotemporal patterns of infectious diseases.

bioinformatics↗

bioRxiv2022

Phylogeographic analysis reveals an ancient East African origin of the human herpes simplexvirus 2 dispersal out-of-Africa.

Human herpes simplex virus 2 (HSV-2) is a globally ubiquitous, slow evolving DNA virus. HSV-2 genomic diversity can be divided into two main groups: an African lineage and worldwide lineage. Competing hypotheses have been put forth to explain the history of HSV-2. HSV-2 may have originated in Africa and then followed the first wave of human migration out of Africa between 50-100 kya. Alternatively, HSV-2 may have migrated out of Africa via the trans-Atlantic slave trade within the last 150-500 years. The lack of HSV-2 genomes from West and Central Africa, combined with a lack of molecular clock signal in HSV-2 has precluded robust testing of these competing hypotheses. Here, we expand the geographic sampling of HSV-2 genomes in order to resolve the geography and timing of divergence events within HSV-2. We analyze 65 newly sequenced HSV-2 genomes collected from primarily West and Central Africa along with 330 previously published genomes sampled over a 47-year period. Evolutionary simulations confirm that the molecular clock in HSV-2 is too slow to be detected using available data. However, phylogeographic analysis indicates that all biologically plausible evolutionary rates would place the ancestor of the worldwide lineage in East Africa, arguing against the trans-Atlantic slave trade as the source of worldwide diversity. The best supported evolutionary rates between 4.2x10-8 and 5.6x10-8 substitutions/site/year suggest a most recent common ancestor for HSV-2 around 90-120 kya and initial dispersal around 21.9-29.3 kya. These dates suggest HSV-2 left Africa during subsequent waves of human migration out of East Africa.

evolutionary biology↗

bioRxiv2021

Accuracy in near-perfect virus phylogenies

AO_SCPLOWBSTRACTC_SCPLOWPhylogenetic trees from real-world data often include short edges with very few substitutions per site, which can lead to partially resolved trees and poor accuracy. Theory indicates that the number of sites needed to accurately reconstruct a fully resolved tree grows at a rate proportional to the inverse square of the length of the shortest edge. However, when inferred trees are partially resolved due to short edges, "accuracy" should be defined as the rate of discovering false splits (clades on a rooted tree) relative to the actual number found. Thus, accuracy can be high even if short edges are common. Specifically, in a "near-perfect" parameter space in which trees are large, the tree length{xi} (the sum of all edge lengths), is small, and rate variation is minimal, the expected false positive rate is less than{xi} /3; the exact value depends on tree shape and sequence length. This expected false positive rate is far below the false negative rate for small{xi} and often well below 5% even when some assumptions are relaxed. We show this result analytically for maximum parsimony and explore its extension to maximum likelihood using theory and simulations. For hypothesis testing, we show that measures of split "support" that rely on bootstrap resampling consistently imply weaker support than that implied by the false positive rates in near-perfect trees. The near-perfect parameter space closely fits several empirical studies of human virus diversification during outbreaks and epidemics, including Ebolavirus, Zika virus, and SARS-CoV-2, reflecting low substitution rates relative to high transmission/sampling rates in these viruses.

evolutionary biology↗

bioRxiv2020

Timing the SARS-CoV-2 Index Case in Hubei Province

Understanding when SARS-CoV-2 emerged is critical to evaluating our current approach to monitoring novel zoonotic pathogens and understanding the failure of early containment and mitigation efforts for COVID-19. We employed a coalescent framework to combine retrospective molecular clock inference with forward epidemiological simulations to determine how long SARS-CoV-2 could have circulated prior to the time of the most recent common ancestor. Our results define the period between mid-October and mid-November 2019 as the plausible interval when the first case of SARS-CoV-2 emerged in Hubei province. By characterizing the likely dynamics of the virus before it was discovered, we show that over two-thirds of SARS-CoV-2-like zoonotic events would be self-limited, dying out without igniting a pandemic. Our findings highlight the shortcomings of zoonosis surveillance approaches for detecting highly contagious pathogens with moderate mortality rates.

evolutionary biology↗

bioRxiv2020

The emergence of SARS-CoV-2 in Europe and the US

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

genetics↗

bioRxiv2019

StrainHub: A phylogenetic tool to construct pathogen transmission networks

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

bioinformatics↗

bioRxiv2018

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

MotivationThe ability to simulate epidemics as a function of model parameters allows insights that are unobtainable from real datasets. Further, reconstructing transmission networks for fast-evolving viruses like HIV may have the potential to greatly enhance epidemic intervention, but transmission network reconstruction methods have been inadequately studied, largely because it is difficult to obtain \"truth\" sets on which to test them and properly measure their performance.\n\nResultsWe introduce FAVITES, a robust framework for simulating realistic datasets for epidemics that are caused by fast-evolving pathogens like HIV. FAVITES creates a generative model to produce contact networks, transmission networks, phylogenetic trees, and sequence datasets, and to add error to the data. FAVITES is designed to be extensible by dividing the generative model into modules, each of which is expressed as a fixed API that can be implemented using various models. We use FAVITES to simulate HIV datasets and study the realism of the simulated datasets. We then use the simulated data to study the impact of the increased treatment efforts on epidemiological outcomes. We also study two transmission network reconstruction methods and their effectiveness in detecting fast-growing clusters.\n\nAvailability and implementationFAVITES is available at https://github.com/niemasd/FAVITES, and a Docker image can be found on DockerHub (https://hub.docker.com/r/niemasd/favites).

bioinformatics↗