Our group focuses on developing a quantitative understanding of the tempo and mode of pathogen evolution, particularly in viruses with pandemic potential. As George Simpson put it in 1944, “tempo” refers to the pace of evolution—how it speeds up or slows down over time—while “mode” relates to the patterns and processes behind evolution, of which tempo is only one part. Understanding both is essential for tracing the evolutionary dynamics of pathogens and piece together their natural history.
We bring together concepts from pathogen evolution and ecology, phylogenetics, and population genetics theory to create new tools and insights for reconstructing pathogen outbreaks, tracing their origins in non-human reservoirs, and evaluating their potential to cause new epidemics or pandemics. Our research advances our understanding of pathogen evolutionary history, with direct public health implications—enabling us to assess the risk of pathogen spillovers into humans, accurately determine the timing of outbreaks, identify key factors influencing pathogen evolutionary dynamics, such as emergence of drug-resistant and immune escape mutations, and contribute to the development of treatments by uncovering virus-host associations over time.
Learn more about our team, see our publications, and explore our ongoing research projects. The group is currently looking for students and postdocs, so come join us!
The group is currently looking for students and postdocs, so come join us!
Our goal is to develop a quantitative framework to understand how both methodological factors (such as the choice of sequence evolution model, sampling frequency, and duration) and biological factors (like population size, host characteristics, strength of selection, and mutation and recombination rates) impact inferences of molecular clock rates. These factors are critical in shaping our estimates of pathogen evolutionary histories. We analyse genomic sequence data from pandemic and epidemic viruses, including SARS-CoV-2, influenza A virus, and HIV, alongside other animal and plant pathogens. In parallel, we simulate populations under various evolutionary forces and sampling strategies to investigate how these forces impact clock rate estimations over time.
The emergence of SARS-CoV-2 has underscored the urgent need to understand how zoonotic viruses evolve across different hosts and over time. These viruses typically originate in animal reservoirs, cross species barriers, and then adapt to new hosts, such as humans. Accurately estimating viral evolutionary rates is crucial for understanding these processes and reconstructing their natural history. A key observation during the early stages of the COVID-19 pandemic was the elevated evolutionary rate of SARS-CoV-2 compared to related coronaviruses in bats, along with the rapid evolution of highly divergent variants like Alpha, early Omicron variants such as BA.1/BA.2, and more recently, JN.1. These variants likely accumulated mutations within chronically infected hosts, raising important questions about the pace and mechanisms of viral evolution, particularly in viruses with pandemic potential, over time and across hosts.
Our research aims to tackle these questions by investigating the sources of viral evolutionary rate variation in both humans and animal hosts. We seek to evaluate whether the emergence of novel viral variants in humans is driven by periods of accelerated evolution. By analyzing evolutionary signatures of rapid mutation accumulation in newly emergent pandemic viruses, we are developing a quantitative framework for inferring evolutionary rates from a mechanistic evolutionary perspective. Ultimately, this work will provide valuable insights into the dynamics that drive zoonotic viruses, the emergence of variants capable of crossing species barriers, and the factors contributing to the generation of novel variants with higher fitness advantages in humans.
We want to put together our understanding of pathogen evolutionary dynamics and the factors that influence evolutionary rate estimates to address critical questions in public health. This includes accurately estimating epidemic onset dates over short evolutionary timescales (a few years to decades) and determining the origin of pathogens in animal reservoirs over much longer periods (thousands to millions of years). For shorter timescales, our insights help improve estimates of pathogen origin dates, viral growth rates, and reproduction numbers, as well as the emergence of new viral lineages—especially in regions where limited sequencing data increases uncertainties around the spread and evolution of viruses. On longer timescales, our estimates provide a clearer picture of how long humans have been exposed to specific pathogens, how frequently these pathogens have caused disease outbreaks, and their potential to trigger future epidemics and pandemics.
You can find an up-to-date and complete list of publications on Google Scholar. A selection of papers in each of our research areas are listed below:
We are always keen to hear from dedicated and motivated researchers. If you are interested in joining us as an Mbiol or DPhil student, or as a Postdoctoral researcher, please get in touch with Mahan at mahan.ghafari@ndm.ox.ac.uk for further information and upcoming positions.
Our group welcomes people of all ethnicities, religions, nationalities, socio-economic backgrounds, gender identities, sexual orientations, ages, and abilities. We are committed to promoting equity and inclusion both within our group and in the broader community.
DPhil students: We have a new DPhil project available through the DPhil in Biology programme, on "Investigating sources of evolutionary rate variation in viruses with pandemic potential over time and across different hosts".
Mbiol students: We are offering two new Year 4 projects in the Microbiology and Infectious Disease section, focused on investigating signatures of adaptive and purifying selection in viruses.
Address: Department of Biology, University of Oxford, Oxford, UK
Email: mahan.ghafari@ndm.ox.ac.uk