Next-generation molecular and evolutionary epidemiology of infectious disease

• Dr Oliver Pybus, Oxford University, UK
• Audio recording (mp3)

Biography

Dr Pybus investigates the evolutionary and ecological dynamics of infectious diseases, particularly pathogenic RNA viruses. Current research concerns viral adaptation and natural selection; the evolutionary behaviour of influenza; the molecular epidemiology and epidemic history of HIV and hepatitis C; the evolution of endogenous retroviruses; and phylogenetic and population genetic methods of gene sequence analysis.  

• Professor Andrew Rambaut, Edinburgh University, UK

Biography

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• Professor Christophe Fraser, Imperial College London, UK

Biography

Biography is not avaliable

• Professor Andrew Rambaut, Edinburgh University, UK

Biography

Biography is not avaliable 

• Professor Leslie Real, Emory University, USA
• Audio recording (mp3)

Biography

Biography is not avaliable

• Professor Dan Haydon, University of Glasgow, UK
• Audio recording (mp3)

Biography

Dan Haydon is Professor of Population Ecology and Epidemiology at the University of Glasgow.  Haydon undertook his PhD at the University of Texas at Austin, and post-docs at the Universities of Oxford, British Columbia, Edinburgh, and Guelph before moving to Glasgow in 2004.  Haydon has worked on FMDV with virologists and epidemiologists at the Institute of Animal Health Pirbright since 1992.  He maintains a diverse set of interests that span theoretical and quantitative approaches to ecological and evolutionary problems including population and ecosystem dynamics, evolutionary ecology, infectious disease ecology and epidemiology.   He was the founding director of the Boyd Orr Centre for Population and Ecosystem Health, and currently is Director of the Institute of Biodiversity, Animal Health and Comparative Medicine within the College of Medical, Veterinary and Life Sciences.   He was elected to the Royal Society of Edinburgh in 2008. 

Abstract

Foot and mouth disease virus (FMDV) is a single positive stranded RNA virus in the family Picornaviridae that causes a serious acute acting disease of cloven-hoofed animals.  The viral genome is ~8.2kb.  In this presentation we will discuss analyses of a series of 20 viral isolates taken from different tissues from 4 sequentially infected cows and sequenced using Illumina technology.  We will describe how the fine polymorphic structure of these virus populations changes from the inoculum used to infect the first animal, within individuals over time, and onward down the chain as a consequence of natural transmission.  We will discuss two approaches to how we can distinguish ‘real’ variation from artifacts induced during sample preparation and sequencing.  The first based on independently replicated sample preparation and sequencing reactions; the second based on a model of the process of sample preparation and sequencing, parameterized using sequence data in which various stages of sample preparation are omitted. 

• Professor Marc Suchard, University of California, Los Angeles, USA
• Audio recording (mp3)

Biography

Marc Suchard, MD, PhD (Biomathematics) is helping to develop the nascent field of evolutionary medicine. This field harnesses the power of methods and theory from evolutionary biology to advance our understanding of human disease processes. Just as phylogenetic approaches have stimulated the field of evolution at large, they posses the potential to revolutionize evolutionary medicine, particularly in the study of rapidly evolving pathogens. To bridge the gap between phylogenetics and human-pathogen biology, Dr Suchard's interests focus on the development of novel reconstruction methods drawing heavily on statistical, mathematical and computation techniques. Some of his current projects involve jointly estimating alignments and phylogenies from molecular sequence data and mapping recombination hot-spots in the HIV genome. 

Abstract

Statistical methods for comparing relative rates of synonymous and nonsynonymous substitutions maintain a central role in detecting positive selection. To identify selection, researchers often estimate the ratio of these relative rates at individual alignment sites.  A reliable way to perform such estimation fits a codon-based evolutionary model that captures heterogeneity of $\dnds$ values across sites. Unfortunately, the large state space of possible codons makes codon-based models computationally prohibitive for massive data sets, containing hundreds or even thousands of sequences.  Alternatives crudely estimate the numbers of  synonymous and nonsynonymous substitutions at each site and use these counts to identify positively selected sites.  Although these counting approaches scale well to massive data sets, they fail to account for ancestral state reconstruction uncertainty and to provide site-specific estimates.  We propose a hybrid solution that borrows the computational strength of counting methods, but augments these methods with empirical Bayes modeling of synonymous and nonsynonymous substitution rates.  The result is a fast and reliable method capable to identify sites under positive selection and to estimate site-specific $\dnds$ values in large data sets.  Importantly, our hybrid approach, set in a Bayesian framework, integrates over the posterior distribution of phylogenies and reconstructions to quantify uncertainty about site-specific $\dnds$ estimates.  Comparisons with mixture codon-based models demonstrate that this hybrid method competes well with these more principal statistical procedures and in some cases even outperforms them.  We illustrate the utility of our method using human immunodeficiency virus and feline panleukopenia & canine parvovirus evolution examples.

• Dr Philippe Lemey, University of Leuven, Belgium
• Audio recording (mp3)

Biography

Philippe Lemey completed his PhD in Medical Sciences (2005) at the K.U. Leuven, Belgium. He then spent 2 years at the University of Oxford doing post-doctoral research in the Department of Zoology before returning to the Rega Institute, K.U. Leuven in 2007, where he took up a tenure-track faculty position in 2010. His research interests are focused on the evolutionary processes that shape viral genetic diversity, spanning large-scale epidemic processes as well as small-scale transmission histories and within-host evolutionary processes. He is the senior editor of the second edition of the Phylogenetic Handbook and an ERC starting grant holder.

Abstract

The influence of phylogeography is spreading throughout biology. Although different methodologies exist to study the geographical history of genetic lineages, recent developments towards model-based approaches that take a probabilistic perspective on spatiotemporal diffusion are gaining popularity in pathogen phylogeography. Such phylogenetic diffusion models, however, typically fit parameter-rich models to sparse spatial data leaving their potential for hypothesis testing largely unexploited.
Here, we demonstrate how a discrete diffusion model can be extended to simultaneously reconstruct spatiotemporal history and test the contribution of potential diffusion predictors. Using a large collection of human influenza A/H3N2 viruses sampled between 2002 and 2006, we illustrate how this approach allows for an integration of viral genetic data and human mobility measures to gain insights into influenza source sink dynamics. Finally, we examine the power of these models fitted to seasonal dynamics in predicting pandemic spread of pandemic H1N1

• Dr Oliver Pybus, Oxford University, UK
• Audio recording (mp3)

Biography

Dr Pybus investigates the evolutionary and ecological dynamics of infectious diseases, particularly pathogenic RNA viruses. Current research concerns viral adaptation and natural selection; the evolutionary behaviour of influenza; the molecular epidemiology and epidemic history of HIV and hepatitis C; the evolution of endogenous retroviruses; and phylogenetic and population genetic methods of gene sequence analysis.  

• Professor Paul Kellam, Wellcome Trust Sanger Institute, UK
• Audio recording (mp3)

Biography

Paul Kellam is the Viral Genomics group leader and Senior Investigator at the Wellcome Trust Sanger Institute and a Professor of Viral Pathogenesis at UCL. Paul has a degree in Microbiology from Reading University and a PhD investigating HIV drug resistance from the Wellcome Foundation laboratories and Imperial College, London. Kellam’s research has resulted in over 100 publications of with an H-index of 30. At UCL the Kellam lab investigates how the B-cell transcriptional environment influences the normal and tumour biology of the oncogenic herpesvirus KSHV. At the Sanger Institute the Kellam laboratory continues its host and virus interaction research and further investigates viral genome variation. At the Sanger we have developed methods and computational analysis for the next generation sequencing of diverse viruses such as HIV, influenza, bluetongue virus and human herpesviruses.  

Abstract

Next generation sequencing now forms a cornerstone in understanding how genetic changes in virus and host genomes influence the biological properties of viral pathogenesis, transmission and host susceptibility to infection. During 2009 and 2010, pandemic influenza swept around the world and whilst not as pathogenic as previous pandemics, influenza A H1N1/09 has caused in excess of 14000 deaths. Importantly, new infections of host populations that lack cross protective adaptive immunity allow the impact of virus and host genetic variation on virulence to be determined. Here I will describe our use of next generation sequencing and host genetic screening platforms to uncover the genetic variation of pandemic H1N1/09 over three waves of infection in the United Kingdom and determine the impact of genetic variation in human genes that control influenza infection in vivo.  In particular, I will show how IFITM3 is essential for defending the host against influenza A virus in vivo and how variant IFITM3 alleles are associated with individuals hospitalised with seasonal or pandemic influenza H1N1/09 viruses. IFITM3 is under positive selection and the evolution of IFITM3 in different animal species suggests that this family of intrinsic immune effectors are essential early barriers of diverse virus infections.

• Professor Sebastian Bonhoeffer, ETH Zurich, Switzerland
• Audio recording (mp3)

Biography

Biography is not avaliable 

Abstract

In my talk I will cover three recent projects from my group. First, I am going to present a phylogenetic analysis of the transmission structure of the HIV epidemic in Switzerland. In particular, I will show that the phylogenetic analysis suggests that there are two subepidemics that are largely independent of each other. One subepidemic spreads among the risk group of men having sex with men, the other spreads in the heterosexual and injecting drug user risk group. The phylogenetic analysis also indicates that the impact of intravenous drug users on this epidemic has declined recently presumably as a consequence of needle exchange programs. The second part of my talk will deal with a new method that allows to infer the contact structure among HIV infected individuals from phylogenetic analysis. The method is applied to data from Switzerland and documents that there is evidence for heterogeneity in contact structure even within risk groups. Finally, I present a new phylogenetic method based on birth death processes in structured populations that allows to quantify the rates of transmission between different risk groups. The application of the developed method to data from the Latvian HIV epidemic shows among other things that the intravenous drug users transmit at a higher rate to heterosexuals then vice versa and that there  is evidence for superspreaders among the risk group of men having sex with men.

• Dr Cecile Viboud, Fogarty International Center, NIH, USA
• Audio recording (mp3)

Biography

Cecile Viboud is a native of France where she received an engineer degree in biomedical technologies from Lyon University in 1998, a Master of Public Health in 1999 and a PhD in Biomathematics in 2003 from the University of Paris. Her research focuses on the transmission dynamics and health burden of influenza and other acute viral infections. She is working at the interface between mathematical modeling, epidemiology, evolutionary genetics, and public health. She has studied the epidemiology of historical pandemics in Europe, Asia and the Americas, characterized the spatial and temporal transmission dynamics of epidemic and pandemic influenza, quantified the health burden of influenza in developed and developing countries, and evaluated the benefits of control strategies. She is also interested in the epidemiology and transmission dynamics of other acute viral infections including rotavirus and respiratory syncytial virus.

Abstract

A key question in disease dynamics is how infections spread in space and time. Here we will contrast models for the spatial spread of acute viral infections in the USA, with a specific focus on epidemic and pandemic influenza, respiratory syncytial virus, and rotavirus. We will assess the role of local climatic drivers, socio-demographic factors, population movements and school cycles on the spatial patterns of these viral diseases at different spatial scales.

• Professor Sunetra Gupta, Oxford University, UK
• Audio recording (mp3)

Biography

Sunetra Gupta is Professor of Theoretical Epidemiology in the Department of Zoology at the University of Oxford, and a Royal Society Wolfson Research Fellow.  She holds a bachelor's degree from Princeton University and a Ph.D. from the University of London.  Her main area of interest is the evolution of diversity in pathogens, with particular reference to the infectious disease agents that are responsible for malaria, influenza and bacterial meningitis.  She has been awarded the Scientific Medal of the Zoological Society of London, the Royal Society Rosalind Franklin Award for her scientific research. 

Abstract

It is commonly believed that the degree of variability exhibited by an antigen is strongly correlated with its role in protective immunity.  This dogma has recently been challenged by a theoretical study on influenza [1] which implies that epitopes of moderate variability play a crucial role.  This model contrasts with the conventional “antigenic drift” hypothesis in that, because of functional constraints on the defining epitopes, the virus population is characterized by a limited set of antigenic types, all of which may be continuously generated by mutation from preexisting strains.  Within this framework, influenza outbreaks arise as a consequence of host immune selection in a manner that is independent of the mode and tempo of viral mutation.  I will discuss how serological data and phylogenetic studies may be used to discriminate between these two paradigms, and the implications for vaccine design.

• Professor Christophe Fraser, Imperial College London, UK

Biography

Biography is not avaliable

• Dr Maciej Boni, Oxford University Clinical Research Unit in Viet Nam, Vietnam
• Audio recording (mp3)

Biography

Maciej Boni received his PhD in Ecology and Evolution in 2006, his doctoral work focusing on the evolutionary epidemiology of influenza as well as general patterns of drug-resistance evolution.  In 2007, Maciej began a joint postdoc across economics and epidemiology departments to develop mathematical models of antimalarial treatment strategies in the context of drug resistance evolution, increased drug access and costs, and falling malaria prevalence.  In 2008, Maciej moved to the Wellcome Trust Oxford unit in Ho Chi Minh City, Vietnam, where he has initiated influenza field studies to accompany his mathematical modeling research.  He is currently looking at basic epidemiological questions surrounding tropical influenza, continuing his modeling work on antimalarial treatment strategies, and advising on aspects of dengue vaccination modeling that will be relevant for Southeast Asia.

Abstract

The epidemic dynamics and evolution of influenza A virus occur on a global scale.  Influenza epidemics in temperate zones are seasonal and more predictable than transmission dynamics in tropical and sub-tropical areas, but the dynamics of these two climatic zones are closely linked, with East and Southeast (E/SE) Asia likely playing a major role in driving global influenza circulation.  Influenza evolution affects the dynamics of influenza epidemics globally, but we do not know which human populations or which epidemiological conditions drive antigenic evolution in influenza.  To answer this question would would need genetic and epidemiological data from regions of the world that are suspected to play a large role in global influenza dynamics.  I will describe several such studies initiated in Vietnam that are aimed at understanding the circulation of human influenza viruses in Southeast Asia, as well as some of the new analytical methods we are developing to analyze the incoming data.  Understanding Vietnam’s role in global influenza circulation will help us determine how important of a role E/SE Asia play in global flu dynamics, and it will help us identify which components of the Vietnam data would allow for similar analyses to be done in other Asian countries.

• Professor William Hanage, Harvard School of Public Health, USA
• Audio recording (mp3)

Biography

Bill Hanage studies the evolution and epidemiology of (mainly) bacterial pathogens. His PhD at Imperial College London was followed by postdoctoral work at Imperial College London and the University of Oxford. In 2010 he joined the faculty at Harvard School of Public Health. He is especially interested in subjects that combine clinical importance with fundamental biological questions, such as how pathogens respond to novel selective pressures in the form of antimicrobials and vaccines, or the link between transmission and virulence. He has also worked extensively on the phenomenon of homologous recombination in bacteria, studying how it can be detected and its consequences for how things respond to selection, and indeed the very notion of species. Increasingly he is involved with population genomic analyses of large numbers of very closely related pathogen isolates, to probe in detail their patterns of transmission and diversification.  

Abstract

The pneumococcus (Streptococcus pneumoniae) is a pathogen of global significance, for which effective vaccines are available against some serotypes. Molecular epidemiologic data, both genetic and genomic, have demonstrated that pneumococci experience a relatively high rate of recombination, which shuffles loci including resistance determinants among lineages and has generated vaccine escape genotypes. Effectively identifying those regions that have undergone recombination is a crucial step in the analysis of genomic data, such that genealogies may be constructed that are not distorted by horizontal gene transfer. It is essential that methods for identifying recombination work with emerging large genomic datasets, and ad hoc methods may be preferred in this context. The results also indicate that, as previously hypothesized, some pneumococcal lineages have experienced more recombination than others.

• Dr Simon Frost, University of Cambridge, UK
• Audio recording (mp3)

Biography

I am a mathematical biologist interested in all aspects of infectious diseases, ranging from within-host dynamics of infection, to the between host dynamics of disease transmission. I studied Natural Sciences (Zoology) in Cambridge, moving on to Oxford to study the within-host dynamics of HIV for my D.Phil. After completing postdoctoral posts in Princeton, Oxford, and Edinburgh, I moved to the University of California, San Diego. In 2008, I was awarded a Royal Society Wolfson Research Merit Award, and took up a Senior Lectureship in the Department of Veterinary Medicine, University of Cambridge. My current research focuses on on infectious disease dynamics in a range of host-parasite systems, and I am actively involved in developing computational and statistical methodology. 

Abstract

Human immunodeficiency virus type 1 (HIV-1) is perhaps the most widely studied organism in viral phylodynamic studies, which aim to combine the epidemiology of viral transmission with the evolution of the virus, and for good reason. Not only is HIV-1 infection a significant public health issue, but a vast amount of sequence data has been generated over a period of decades, which when combined with the clock-like nature of HIV-1 evolution, allows fairly accurate reconstruction of past transmission events. Insights that have been gained by HIV-1 sequence analysis include identifying the timing of origin of HIV-1 epidemics, identifying period of exponential epidemic growth, and identification of 'transmission clusters' of infection. To date, rather simple models underlie the analysis of viral sequence data, which consider neither the detailed natural history of viral infection, nor the biased way in which sequence data is typically collected. Using HIV as an example of a model phylodynamic system, I will consider the importance of heterogeneity in geographic location, risk group, duration of infection, and age at infection in determining the structure of viral phylogenetic trees. I will also highlight how non-uniform sampling is an important confounding factor. [Joint work with Erik Volz].

• Professor Katia Koelle, Duke University, USA
• Audio recording (mp3)

Biography

I am a mathematical disease ecologist interested in understanding the population dynamics and evolutionary dynamics of infectious diseases. I earned my PhD in 2005 from the University of Michigan- Ann Arbor (PhD advisor Mercedes Pascual), where I studied the effects of climate forcing and strain interactions on cholera dynamics. As a post-doctoral researcher with Bryan Grenfell at Penn State’s Center for Infectious Disease Dynamics from 2006 to 2007, I continued to spend time focusing on strain interactions, with a heavier focus on rapidly evolving viral pathogens. Since starting a faculty position at Duke University in 2007, I have been working on the design of mathematical models to better understand the phylodynamics of RNA viral diseases, including influenza, dengue, and norovirus. I have also been working on the development of statistical approaches to fit epidemiological models to time series data and viral sequence data, and the application of these approaches to address questions of interest to disease ecologists.

• Professor Simon Hay, University of Oxford, UK
• Audio recording (mp3)

Biography

Professor  Simon Hay obtained his doctorate in 1996 from the University of Oxford where he is now a Professor of Epidemiology. He is funded by a Wellcome Trust Senior Research Fellowship and has published over 140 peer-reviewed contributions. He serves on many committees and expert advisory panels of the numerous public health initiatives for malaria control and elimination. He is also an editor of Advances in Parasitology. He was awarded the Scientific Medal of the Zoological Society of London in 2008 and the Back Award, of the Royal Geographical Society in 2012, for research contributing to public health policy.

• Professor Brian Spratt CBE FRS, Imperial College London, UK

Biography

Biography not available at this time

• Dr Larry Brilliant, Skoll Global Threats Fund, USA
• Audio recording (mp3)

Biography

Larry Brilliant is the President and CEO of the Skoll Global Threats Fund and Senior Advisor to Jeff Skoll. He heads a team whose mission is to confront global threats imperiling humanity by seeking solutions, strengthening alliances and spurring actions needed to safeguard the future. Prior to joining Skoll, Larry was Vice President at Google and Executive Director of Google.org. Larry is an M.D. and M.P.H. and board certified in preventive medicine and public health. He is a co-founder of the Well, a pioneering digital community as well as founder of The Seva Foundation, an international NGO whose programs have given back sight to more than 3 million blind people in 20 countries. Larry lived in India for more than a decade while working as a United Nations medical officer where he helped run the successful World Health Organization (WHO) smallpox eradication program. He recently worked for the WHO polio eradication effort as well. He was Associate Professor of epidemiology, global health planning and economic development at the University of Michigan. He was chairman of the National Biosurveillance Advisory Committee, created by Presidential Directive, was a “first responder” for CDC’s bio-terrorism response effort, and volunteered in Sri Lanka for tsunami relief. His recent awards include the “TED Prize”, Time Magazine’s “100 Most Influential People”, “International Public Health Hero” and two honorary doctorates. He is the author of two books and dozens of articles on infectious diseases, blindness and international health policy. 

Abstract

We review the history of efforts to innovate early warning of new diseases and routine reports of disease incidence and prevalence.   Special attention is paid to innovations from eradication programs..  The first use of "surveillance and containment" as a program strategy led to the eradication of smallpox.   The use of genomic sequencing (as in the polio eradication program) permitted assumption of sequencing of outbreaks detected by a surveillance system.   "Prioxies" like chickenpox for smallpox and acute flaccid paralysis for polio allowed surveillance efforts to continue even after the target disease was eliminated.   Changes in the international health regulations allowed innovations in non-governmental suveillance and case detection systems to flourish.   GOARN, CORDS, Google Flu Trends, GPHIN, Health Map, ProMed and others are discussed.  More recently, syndromic surveillance systems over mobile phones and self-reporting systems like Flu Near You open a new category of digital surveillance systems.  From handwritten case reports, to national and WHO surveillance systems, to nongovernmental digital systems, the past has been prologue as the next century will see cloud based systems and social media like Twitter and Facebook become integrated into national and nongovernmental disease surveillance systems, with the possible result that disease detection times will plummet.   Between the 1990’s and 2009, the average detection time, from outbreak start to detection, has fallen from 167 days to 20 days.  Cloud based systems, social media, mobile phones, and other innovations raise the exciting possibility that it may not be long before new diseases can be detected within a short enough time to dramatically reduce the risk of pandemics, and routine disease surveillance may move from national surveillance systems to digital voluntary reporting on a large scale.

• Professor Sharon Peacock, Health Protection Agency & University of Cambridge, UK
• Audio recording (mp3)

Biography

Professor Peacock is a clinical microbiologist based within the Departments of Medicine and Pathology, is an honorary consultant clinical microbiologist with the Health Protection Agency and Cambridge University Hospitals NHS Trust, and is an honorary faculty member of the Wellcome Trust Sanger Institute. She is particularly interested in translation of sequence-based technologies in diagnostic and public health microbiology. She is funded by a UKCRC Translational Infection Research Initiative grant to develop tools for transmission tracking and outbreak investigation of MRSA. Professor Peacock chairs the Cambridge Infectious Diseases Initiative; is a member of the Medical Research Council Infection and Immunity Board; and is a member of the Medical Technologies Advisory Committee, National Institute for Health and Clinical Excellence (NICE).

Abstract

Whole genome sequencing (WGS) provides the ultimate discrimination between closely related bacterial isolates, and the rapidly falling cost and turnaround time means that this could become a viable technology in diagnostic and reference microbiology laboratories in the near future. An obvious application for WGS is epidemiological typing to define transmission pathways of pathogens and support outbreak investigations. This talk will provide a brief outline on the potential utility of WGS for diagnostic and public health microbiology, and will then focus on the application of WGS to methicillin-resistant Staphylococcus aureus (MRSA). Data will be presented on the application of this technology to define global and local MRSA transmission, together with the results of studies in which a benchtop sequencer has been used to investigate putative MRSA outbreaks in a UK hospital.