Biology subjects

Lemey, P.

Publications and source records attributed to Lemey, P..

At least 19 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

Phylodynamic analysis reveals asymmetric and accelerating global spread of dengue virus

Dengue virus (DENV) continues to expand globally, with increasing incidence in both endemic and non-endemic countries. Leveraging a large global dataset of DENV genomes starting from the 1940s, we reconstructed global and regional patterns of DENV spread using phylogeographic and phylodynamic methods. Our analyses reveal that the current global diversity of urban DENV originated in Asia in the first half of the 20th century. During the more than 100 years since, we find that the highest density of between-country spread occurs within Asia and the region continues to be a global source, seeding transmission in Africa and the Americas. Global spread is, however, not balanced. Even though there is more travel to South America, we show that DENV lineages primarily enter North America (mostly from South Asia) through a link defined by seasonal synchrony across the Northern Hemisphere. Along with a substantial increase in global travel starting ~2010, the rate of spread to the Americas is increasing, establishing new lineages associated with large recent outbreaks. DENV lineages do not frequently spread back to Asia from the Americas or Africa, and we posit this is due to higher genetic diversity in Asia, leading to stiffer competition for invading lineages. Within the Americas, the network of DENV dispersal initiates in North America, primarily the Caribbean, and then is maintained by major hubs in South America. Overall, we find that travel volume, rather than climate factors, is mostly responsible for long-term patterns of DENV spread globally and within the Americas. Our results highlight key nodes in the global dynamics of DENV lineages, and suggest spread will continue to accelerate in a more connected world.

genomics↗

bioRxiv2026

Better data, better trees: GenBank-GISAID deduplication and source-specific artifact masking in viral genomics

GenBank and GISAID are the primary repositories for viral genomic data, but integrating records across them remains a challenge. The same sequence could be made available in both databases without any cross-reference linking the two entries. Consequently, there is no systematic way to identify this redundancy, which compromises the compilation of representative, non-redundant large-scale datasets. In parallel, the growth of viral genomic data has increased the risk of systematic technical artifacts introduced during sequencing or assembly. These artifacts can inflate substitution rate estimates and degrade temporal signal, biasing evolutionary rate estimates. To address both challenges, here we present a formal, reproducible workflow integrating two newly developed complementary tools: G2G matcher for cross-repository harmonization and Lab-Specific Bias FILTer (LSBFILT) for masking of laboratory-specific artifacts. Using the Eastern/Central/South African (ECSA) chikungunya virus lineage as a proof-of-concept, we demonstrate that our integrated workflow restores temporal signal and provides a robust, curated dataset for downstream phylodynamic analyses. Critically, restricting masking of homoplastic sites to specific sequences reduces the substitution rate estimate from an inflated 8.517 x 10-4 to 5.078 x 10-4 substitutions/site/year and increases the coefficient of determination (R2) of the root-to-tip regression analysis from 0.353 to 0.677. By enabling systematic cross-repository harmonization and source-specific artifact masking, we provide the molecular epidemiological community with scalable tools to reconcile fragmented genomic data and reduce technical biases, fostering more accurate and reproducible phylogenetic analysis. G2G matcher is available at https://github.com/andrezaleite/G2G-Matcher, and LSBFILT at https://github.com/khourious/LSBFILT.

bioinformatics↗

bioRxiv2026

Reconciling fast Hepatitis B evolutionary rates with ancient co-divergence

Estimating evolutionary rates and divergence times for hepatitis B virus (HBV) has long been complicated by conflicting calibration approaches and extensive rate variation. To unlock the full potential of ancient and modern HBV genomic data, we develop a Bayesian mixed-effects molecular clock model that accounts for various sources of rate variation including time-dependent rate decay. Our analyses reveal a pronounced decline in evolutionary rates over time, reconciling HBV divergence estimates with human migration events across both deep and more recent timescales. We show that HBV spread into Europe through both Neolithic farming expansions and later steppe migrations, paralleling patterns proposed for Indo-European language origins. Phylogeographic reconstructions suggest that the Neolithic-associated lineage dispersed at approximately 1 km/year, consistent with archaeological estimates, while genotype D expanded during the Bronze Age at an almost threefold higher rate, plausibly driven by technological innovations underlying steppe expansions. Historical overlap between these lineages facilitated recombination, giving rise to genotype E, which has become a dominant HBV genotype in Africa. These findings demonstrate that ancient viral genomes, when analyzed with models capturing complex rate dynamics, provide a powerful lens on human prehistory and the processes shaping pathogen diversity.

evolutionary biology↗

bioRxiv2026

Bovine H5N1 influenza viruses have adapted to more efficiently use receptors abundant in cattle

Sustained mammal-to-mammal transmission of high pathogenicity H5N1 avian influenza viruses is reshaping the host range of these pathogens. One of the longest-running mammalian transmission chains involves the B3.13 genotype circulating in U.S. dairy cattle which was detected in early 2024. Genomic analyses revealed selection and rapid fixation of haemagglutinin mutations D104G and V147M. We demonstate, via glycomic profiling, that bovine tissues, including the mammary gland, are enriched in N- and O-linked glycans capped with N-glycolylneuraminic acid (NeuGc), a sialic acid absent in humans and birds, which instead express only N-acetylneuraminic acid (NeuAc). Early cattle H5 viruses poorly recognized NeuGc, but D104G and V147M enabled efficient engagement of both NeuAc- and NeuGc-containing receptors. These mutations enhanced replication in bovine mammary tissue without major attenuation of replication in human lung and primary nasal epithelial cells. NeuGc-driven receptor adaptation therefore promotes viral fitness in cattle while potentially limiting immediate zoonotic risk. Deep mutational scanning further identified alternative haemagglutinin substitutions that confer NeuGc usage and represent surveillance markers for emerging cattle H5 lineages.

microbiology↗

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↗

bioRxiv2026

Emergence of mpox in Guinea: sporadic clade IIa cases and a clade IIb upsurge

BackgroundMpox virus (MPXV) has caused recurrent outbreaks in West Africa. However, Guinea had not previously reported laboratory-confirmed cases or MPXV genomic data. MethodsSuspected cases were identified in the NZerekore region as well as in the Conakry (Sept 2024- Dec 2025) and confirmed by real-time PCR in regional and central laboratories, respectively. Whole-genome sequencing using nanopore technology was performed in-country, followed by phylogenetic and time-scaled evolutionary analyses. FindingsThe first mpox case was clinically diagnosed in September 2024 in the NZerekore region and laboratory-confirmed by the prefectural laboratory in Gueckedou. In total, seven cases were confirmed in Forest Guinea, of which five complete or almost complete MPXV genomes were recovered. All belonged to MPXV clade IIa. Genomic divergence, ancestral dating, and low APOBEC3-associated mutation frequencies were consistent with multiple independent zoonotic spillover events. In June 2025, one of the first mpox cases of an unfolding outbreak was confirmed in Conakry. Whole genome sequencing revealed MPXV clade IIb lineage G.1. By December 2025, the number of laboratory-confirmed mpox cases nationwide increased to 2,151. A total of nine outbreak strains were sequenced, all belonging to Clade IIb. The genomes clustered with contemporaneous genomes from Sierra Leone and showed high APOBEC3-associated mutation frequencies, suggesting sustained human-to-human transmission in the region. InterpretationThese data demonstrate simultaneous circulation of MPXV clade IIa and IIb strains in Guinea, likely resulting from zoonotic spillover and human-to-human transmission, respectively. Decentralised diagnostics and in-country sequencing facilitated rapid case confirmation and genomic surveillance, highlighting the importance of these critical capacities for outbreak preparedness and response. FundingGerman Federal Ministry of Health and the German Center for Infection Research (DZIF).

genomics↗

bioRxiv2026

3,500 years of sheeppox virus evolution inferred from archaeological and codicological genomes

Sheeppox virus (SPPV) is a major livestock pathogen causing economic hardship through reduced production and death of vulnerable sheep, with written descriptions of sheeppox-like disease recorded since antiquity. We report 21 novel ancient SPPV genomes spanning the Eurasian steppe Bronze Age ([~]1,700 BCE) to the Early Modern period in Western Europe, including multiple genomes obtained from medieval parchment. We estimate that major capripoxvirus lineages diverged [~]11,500-3,700 years ago, overlapping known translocations and bio-cultural developments in sheep. Our dataset supports SPPV diverging first within the lineage leading to goatpox virus and lumpy skin disease virus, and that known gene inactivation events within SPPV and goatpox virus occur in our earliest SPPV genomes. These findings reveal that the food security of Eurasian communities have been threatened by sheeppox for over 3,700 years, and provide new insights to the genomic evolution and potential host adaptation of sheeppox virus. TeaserAncient viral genomes from manuscripts and teeth illuminate the evolutionary history of sheeppox virus.

genetics↗

bioRxiv2026

Evolutionary history of Jamestown Canyon virus disentangles complex multi-vector ecology

Jamestown Canyon virus (JCV) is a re-emerging mosquito-borne virus of increasing concern in North America. It has been historically understudied, leading to significant gaps in our understanding of its evolutionary history, ecological maintenance, and transmission dynamics. Here, we generated 658 whole-genome JCV sequences from the Northeast United States, including 84% (500/597) of all JCV-positive mosquitoes detected in Connecticut from 1997-2022. Then we applied phylodynamic methods to demonstrate how mosquito phenology and host interaction structure the persistence and spread of JCV. Our phylogenetic analyses estimate that JCV was introduced in the Northeast by at least the early 1700s and the primary introductions of lineages A and B into Connecticut occurred during the mid-1800s to mid-1900s. Further, we estimate that JCV evolves at a rate of [~]3 x 10-5 s/s/y, making it one of the slowest evolving known RNA viruses, because the virus spends [~]10 months per year in evolutionary stasis while over-wintering in mosquito eggs. To investigate ecological drivers of JCV spread in Connecticut, we paired discrete trait and continuous phylogeographic reconstructions with mosquito surveillance data. We estimate that JCV has a low diffusion rate of [~]30-60 km2/year, which is more similar to slow-moving tick-borne viruses than other mosquito-borne viruses. We found that univoltine Aedes mosquitoes were likely to maintain the virus across years through overwintering in eggs, accounting for its slow evolution and dispersal, while multivoltine mosquitoes contribute to periodic bursts of spatial diffusion and amplification within seasons. By characterizing seasonal dynamics of JCV, we demonstrate the utility of dense sequencing and phylodynamics to disentangle complex transmission cycles, offering a framework to rapidly advance our evolutionary and ecological knowledge of understudied viruses.

ecology↗

bioRxiv2025

RNA virus genomes from centuries- to millennia-old Adelie penguin mummies

Direct studies of long-term RNA virus evolution are largely limited to chemically-fixed specimens from museums collected over the past two centuries. Detecting genomic traces of RNA viruses in older, buried remains is considered highly unlikely. The cold, dry conditions of Antarctica may represent an exception. Here, natural mummification of penguins and seals--animals that form large colonies where RNA viruses circulate--is common, potentially facilitating RNA virus genome recovery. Here, we show that Adelie penguin (Pygoscelis adeliae) mummies, ranging in age from recent to nearly two millennia, indeed contain ancient viral genome fragments. Metatranscriptomic analyses yielded near-complete genome sequences of a picornavirus (Megrivirus epengu) and a rotavirus D (Rotavirus deltagastroenteritidis) from relatively recent specimens. We further retrieved rotavirus D sequences from a 280-year-old individual and a near-complete rotavirus G (Rotavirus gammagastroenteritidis) genome from a 2000-year-old one. These findings pave the way to direct studies of RNA virus evolution across millennia.

molecular biology↗

bioRxiv2025

Genomic evidence for co-evolution and sporadic host shifts in leishmaniaviruses

The association between Leishmania parasites and the double-stranded RNA virus, Leishmaniavirus (LRV), significantly impacts human health by modulating disease severity. Despite its clinical importance, the evolutionary history of this symbiosis remains largely unknown. This study presents one of the first formal investigations of their co-phylogenetic history across different taxonomic hierarchical levels; based on total RNA sequencing of cultivated isolates, simultaneously capturing the parasite`s transcriptome and the viral genome. We found strong support for phylogenetic congruence between Leishmania and LRV at both the subgenus and species level; based on genetic distance correlations and formal co-phylogenetic statistics. Focusing on the interactions of L. (V.) braziliensis and L. (V.) guyanensis with LRV1, we observed weaker co-phylogenetic signals though frequent instances of intraspecific host switching. Together, our findings indicate that LRV has been a persistent evolutionary partner of Leishmania, providing a framework for understanding the emergence and maintenance of virus-mediated disease phenotypes.

evolutionary biology↗

bioRxiv2025

Parallel algorithms for phylogenetic inference under a structured coalescent approximation

While advances in molecular epidemiology and computational modeling have enhanced our capacity to track pathogen evolution, the accurate reconstruction of spatiotemporal transmission dynamics remains essential for developing epidemic preparedness frame-works and implementing outbreak response measures. Structured coalescent models offer a phylogeographic framework by restricting lineage coalescence events to geographically proximate host populations. Although the Bayesian structured coalescent approximation (BASTA) provides a tractable approach, contemporary phylogeographic analyses involving dozens of geographic localities and hundreds to thousands of viral genomes substantially exceed the computational capacity of existing implementations. The BASTA likelihood scales cubically with deme count and quadratically with sequence count due to matrix exponentiation and pairwise coalescent probability calculations. Here, we introduce a comprehensive algorithmic restructuring of the structured coalescent likelihood that eliminates redundancies, optimizes memory access, and exposes parallelization opportunities. Our approach reorganizes computations along three dimensions: (i) independent calculation of deme-transition probability matrices across time intervals; (ii) simultaneous evaluation of partial likelihood vectors within temporal slices; and (iii) concurrent aggregation of coalescent probabilities. Algorithmic restructuring cuts average coalescent likelihood computation by 7-8 fold, and parallelization further boosts performance to 10-26 fold, enabling joint phylogeographic analyses of dengue virus across 10 South American countries and H5N1 avian influenza across 20 Eurasian regions to finish in a fraction of prior time. This computational efficiency also enables comparison between backward-in-time structured coalescent approximations and forward-in-time phylogeographic methods, revealing that the former provides appropriately conservative posterior estimates, particularly at intermediate phylogenetic depths. We integrate our implementation into the popular BEAST X and BEAGLE software packages, with an accompanying interface in BEAUti X to easily set up the analyses, providing researchers with an accessible and scalable tool for real-time phylogeographic surveillance of rapidly evolving pathogens.

bioinformatics↗

bioRxiv2025

nf-core/viralmetagenome: A Novel Pipeline for Untargeted Viral Genome Reconstruction

MotivationEukaryotic viruses present significant challenges for genome reconstruction and variant analysis due to their extensive diversity and potential genome segmentation. While de novo assembly followed by reference database matching and scaffolding is a commonly used approach, the manual execution of this workflow is extremely time-consuming, particularly due to the extensive reference curation required. Here, we address the critical need for an automated, scalable pipeline that can efficiently handle viral metagenomic analysis without manual intervention. ResultsWe present nf-core/viralmetagenome, a comprehensive viral metagenomic pipeline for untargeted genome reconstruction and variant analysis of eukaryotic DNA and RNA viruses. Viral-metagenome is implemented as a Nextflow workflow that processes short-read metagenomic samples to automatically detect and assemble viral genomes, while also performing variant analysis. The pipeline features automated reference selection, consensus quality control metrics, comprehensive documentation, and seamless integration with containerization technologies, including Docker and Singularity. We demonstrate the utility and accuracy of our approach through validation on both simulated and real datasets, showing robust performance across diverse viral families in metage-nomic samples. Availabilitynf-core/viralmetagenome is freely available at https://github.com/nf-core/viralmetagenome with comprehensive documentation at https://nf-co.re/viralmetagenome Contactjoon.klaps@kuleuven.be Supplementary informationSupplementary data are available at https://github.com/Joon-Klaps/nf-core-viralmetagenome-manuscript online.

bioinformatics↗

bioRxiv2025

Comparative performance of novel viral landscape phylogeography approaches

The fast rate of evolution in RNA viruses implies that their evolutionary and ecological processes occur on the same time scale. Genome sequences of these pathogens can therefore contain information about the processes that govern their transmission and dispersal. In particular, landscape phylogeographic approaches use phylogeographic reconstructions to investigate the impact of environmental factors and variables on the spatial spread of viruses. Here, we extend and improve existing approaches and develop three novel landscape phylogeographic methods that can test the impact of continuous environmental factors on the diffusion velocity of viral lineages. In order to evaluate the different methods, we also implemented two simulation frameworks to test and compare their statistical performance. The results enable us to formulate clear guidelines for the use of three complementary landscape phylogeographic approaches that have sufficient statistical power and low rates of false positives. Our open-source methods are available to the scientific community and can be used to investigate the drivers of viral spread, with potential benefits for understanding virus epidemiology and designing tailored intervention strategies.

evolutionary biology↗

bioRxiv2024

HIPSTR: highest independent posterior subtree reconstruction in TreeAnnotator X

In Bayesian phylogenetic and phylodynamic studies it is common to summarise the posterior distribution of trees with a time-calibrated consensus phylogeny. While the maximum clade credibility (MCC) tree is often used for this purpose, we here show that a novel consensus tree method - the highest independent posterior subtree reconstruction, or HIPSTR - contains consistently higher supported clades over MCC. We also provide faster computational routines for estimating both consensus trees in an updated version of TreeAnnotator X, an open-source software program that summarizes the information from a sample of trees and returns many helpful statistics such as individual clade credibilities contained in the consensus tree. HIPSTR and MCC reconstructions on two Ebola virus and two SARS-CoV-2 data sets show that HIPSTR yields consensus trees that consistently contain clades with higher support compared to MCC trees. The MCC trees regularly fail to include several clades with very high posterior probability ([≥] 0.95) as well as a large number of clades with moderate to high posterior probability ([≥] 0.50), whereas HIPSTR achieves near-perfect performance in this respect. HIPSTR also exhibits favorable computational performance over MCC in TreeAnnotator X. Comparison to the recently developed CCD0-MAP algorithm yielded mixed results, and requires more in-depth exploration in follow-up studies. TreeAnnotator X - which is part of the BEAST X (v10.5.0) software package - is available at https://github.com/beast-dev/beast-mcmc/releases.

bioinformatics↗

bioRxiv2024

Grains, trade and war in the multimodal transmission of Rice yellow mottle virus: an historical and phylogeographical retrospective

Rice yellow mottle virus (RYMV) is a major pathogen of rice in Africa. RYMV has a narrow host range limited to rice and a few related poaceae species. We explore the links between the spread of RYMV in East Africa and rice history since the second half of the 19th century. The phylogeography of RYMV in East Africa was reconstructed from coat protein gene sequences (ORF4) of 335 isolates sampled over two million square kilometers between 1966 and 2020. Dispersal patterns obtained from ORF2a and ORF2b, and full-length sequences converged to the same scenario. The following imprints of rice cultivation on RYMV epidemiology were unveiled. RYMV emerged in the middle of the 19th century in the Eastern Arc Mountains where slash-and-burn rice cultivation was practiced. Several spillovers from wild hosts to cultivated rice occurred. RYMV was then rapidly introduced into the adjacent large rice growing Kilombero valley. Harvested seeds are contaminated by debris of virus infected plants that subsist after threshing and winnowing. Long-distance dispersal of RYMV is consistent (i) with rice introduction along the caravan routes from the Indian Ocean Coast to Lake Victoria in the second half of the 19th century, (ii) seed movement from East Africa to West Africa at the end of the 19th century, from Lake Victoria to the north of Ethiopia in the second half of the 20th century and to Madagascar at the end of the 20th century, (iii) and, unexpectedly, with rice transport at the end of the First World War as a troop staple food from the Kilombero valley towards the South of Lake Malawi. Overall, RYMV dispersal was associated to a broad range of human activities, some unsuspected. Consequently, RYMV has a wide dispersal capacity, its dispersal metrics estimated from phylogeographic reconstructions are similar to those of highly mobile zoonotic viruses. Author summaryRice yellow mottle virus (RYMV) poses a major threat to rice production in Africa. We explored through a multidisciplinary approach the links between the history of rice in East Africa since the second half of the 19th century and the spread of RYMV. The results illuminate the causes of RYMV diffusion. We show the role of long-distance caravan trade, the impact of the First World War and the consequences of seed exchange in the dispersal of RYMV. The paradoxical role of seeds in the spread of RYMV - which is vector transmitted and not seed transmitted - is explained in the light of rice biology and agronomy. Overall, this study reveals the wide range of transmission ways, some unexpected, in the dispersal of plant viruses. It also highlights the role of human transmission of pathogens, even vector-borne, and sheds light on the risk of transmission of RYMV and of other plant viruses from Africa to other continents.

evolutionary biology↗

bioRxiv2024

Evolutionary genomics of a zoonotic parasite across the Neotropical Realm

The Neotropical realm, one of the most biodiverse regions on Earth, houses a broad range of zoonoses that pose serious public health threats. Protozoan parasites of the Leishmania (Viannia) braziliensis species complex cause zoonotic leishmaniasis in Latin America with clinical symptoms ranging from simple cutaneous to destructive, disfiguring mucosal lesions. We present the first comprehensive genome-wide continental study including 257 cultivated isolates representing most of the geographical distribution of this major human pathogen. The L. braziliensis species complex is genetically highly heterogeneous, consisting of divergent parasite groups that are associated with different environments and vary greatly in diversity. Apart from several small ecologically isolated groups with little diversity, our sampling identifies two major parasite groups, one associated with the Amazon and the other with the Atlantic Forest biomes. These groups show different recombination histories, as suggested by high levels of heterozygosity and effective population sizes in the Amazonian group in contrast to high levels of linkage and clonality in the Atlantic group. We argue that these differences are linked to strong eco-epidemiological differences between the two regions. In contrast to geographically focused studies, our study provides a broad understanding of the molecular epidemiology of zoonotic parasites circulating in tropical America.

evolutionary biology↗

bioRxiv2024

Modeling the velocity of evolving lineages and predicting dispersal patterns

Accurate estimation of the dispersal velocity or speed of evolving organisms is no mean feat. In fact, existing probabilistic models in phylogeography or spatial population genetics generally do not provide an adequate framework to define velocity in a relevant manner. For instance, the very concept of instantaneous speed simply does not exist under one of the most popular approaches that models the evolution of spatial coordinates as Brownian trajectories running along a phylogeny (Lemey et al., 2010). Here, we introduce a new family of models - the so-called "Phylogenetic Integrated Velocity" (PIV) models - that use Gaussian processes to explicitly model the velocity of evolving lineages instead of focusing on the fluctuation of spatial coordinates over time. We describe the properties of these models and show an increased accuracy of velocity estimates compared to previous approaches. Analyses of West Nile virus data in the U.S.A. indicate that PIV models provide sensible predictions of the dispersal of evolving pathogens at a one-year time horizon. These results demonstrate the feasibility and relevance of predictive phylogeography in monitoring epidemics in time and space.

evolutionary biology↗