Stochastic Models of the Spread of Disease and Information on Networks

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Stochastic Models of the Spread of Disease and Information on Networks

 04 - 08 Jul 2016
 ICMS, 15 South College Street Edinburgh

Scientific Organisers:

  • Rick Durrett, Duke University

  • Thomas House, University of Manchester

  • Malwina Luczak, Queen Mary University of London

  • Pieter Trapman, Stockholm University

Despite major advances due to vaccination, hygiene and pharmaceutical interventions, infectious diseases continue to pose a serious threat to public health. Notable examples of epidemics during recent decades include the HIV epidemic, the SARS outbreak in 2002-04, the 2009 H1N1 influenza pandemic, and more recently Ebola. It is of utmost importance to understand how infectious diseases spread through populations, how the population structure influences the spread, and what disease control measures are effective.

The main themes were:

  • Spread of epidemics on dynamic networks

  • Near-critical epidemics

  • Persistence of epidemics

  • Spread of information and opinions

  • Connecting mathematical models to real-life epidemics through data fitting

Mathematically, models of disease and information spread have a wealth of interesting features, and understanding them better will advance the field. Currently, health systems in developed nations are struggling under pressure caused by ageing populations and resource limitations. It is therefore imperative to reduce the economic and human burden of infectious diseases as efficiently as possible, and modelling can play a key role in this optimisation.

Speakers:

  • Frank Ball, University of Nottingham - Inference for Emerging Epidemics on Networks with Household Structure

  • Philip O'Neill, University of Nottingham - Bayesian Inference for Epidemic Models via Likelihood Approximation 

  • Peter Neal, Lancaster University - A Household SIR Epidemic Model Incorporating Time of Day Effects

  • Rosalind Eggo, London School of Hygiene & Tropical Medicine - Epidemic Size and the Role of Population Immune History in Influenza

  • Pierre-Andre Maugis, University College London - Network Analysis and Non-Parametric Statistics

  • David Sirl, University of Nottingham - Vaccine Allocation in Network Epidemic Models

  • Tom Britton, Stockholm University - Inferring R_0 in Emerging Epidemics - the Effect of Common Population Structure is Small 

  • Viet Chi Tran, Université Lille 1 - Nonparametric Adaptive Estimation of Order 1 Sobol Indices in Stochastic Models, with an Application to Epidemiology

  • Mick Roberts, Massey University - An Epidemic Model with Noisy Parameters

  • Odo Diekmann, University of Utrecht - The Renewal Equation for the Volz Variable

  • Joel Miller, Institute for Disease Modeling - Modeling Disease Spread with Birth, Death and Concurrency

  • Elizabeth Buckingham-Jeffrey, University of Warwick - Gaussian Process Approximations of the Stochastic SIR Model

  • TJ McKinley, University of Exeter - Combining Gaussian Processes and ABC for Inference in Complex Infectious Disease Models: with Application to HIV in Uganda

  • Nakul Chitnis, Swiss Tropical and Public Health Institute - Modelling Rabies Elimination in an African City

  • Mirjam Kretzschmar, University Medical Centre Utrecht - Use of Network Models for Assessing the Impact of Interventions for Chlamydia Infections

  • Ian Hall, Public Health England - Developing an Emerging Disease Analysis Toolbox

  • Iain Barrass, Public Health England - Modelling to Support a UK Pandemic Influenza Exercise

  • David Aldous, University of California - A General SI Epidemic and a Framework for Imperfectly Observed Networks

  • Fabio Lopes, Universidad de Chile - Extinction Time for the Weaker of Two Competing SIS Epidemics

  • Damien Clancy, Heriot-Watt University - Approximating the Time to Endemic Fade-Out

  • Graham Brightwell, London School of Economics - The SIS Logistic Epidemic

  • Ayalvaid Ganesh, University of Bristol - Optimal Control of a Contact Process

  • Christel Kamp, Paul-Ehrlich-Institut - Epidemic Spread on Weighted Networks

  • Tobias Mueller, University of Utrecht - A Hyperbolic Model of Complex Networks

  • Joshua Ross, University of Adelaide - Characterising Pandemic Impact from Data Collected During First Few Hundred Studies

  • Istvan Kiss, University of Sussex - Generation and Analysis of Networks with a Prescribed Degree Sequence and Subgraph Family: Higher-Order Structure Matters

  • Kieran Sharkey, University of Liverpool - Defining Prevalence and Invasion Probability for SIS Dynamics on Finite Networks

  • Edward Hill, University of Warwick - Spreading of Healthy Mood in Adolescent Friendship Networks 

  • Nicolas Rivera, King's College London - The Linear Voting Model

  • Eric Foxall, Arizona State University - Dynamics of the Naming Game on the Complete Graph

  • Denis Mollison, Heriot-Watt University - Challenges in Representing Spatial Structure

  • Tatyana Turova, Lund University - Random Geometric Graphs

Participants

Name
Institution
David, AldousUniversity of California, Berkeley
Frank, BallUniversity of Nottingham
Iain, BarrassPublic Health England
Graham, BrightwellLondon School of Economics
Tom, BrittonStockholm University
Elizabeth, Buckingham-JefferyUniversity of Warwick
Stephen, CatterallBiomathematics and Statistics Scotland
Nakul, ChitnisSwiss Tropical and Public Health Institute
Damian, ClancyHeriot-Watt University
Odo, DiekmannUniversity of Utrecht
Louise, DysonUniversity of Warwick
Rosalind, EggoLondon School of Hygiene & Tropical Medicine
Eric, FoxallArizona State University
Ayalvadi, GaneshUniversity of Bristol
Ian, HallPublic Health England
Edward, HillUniversity of Warwick
Joseph, HiltonUniversity of Warwick
Deirdre, HollingsworthUniversity of Warwick
Thomas, HouseUniversity of Manchester
Valerie, IshamUniversity College London
Hannah, JonesHeriot-Watt University
Christel, KampPaul-Ehrlich-Institut
Timothy Muiruri, KinyanjuiUniversity of Manchester
Istvan, KissUniversity of Sussex
Janis, KlaiseThe University of Warwick
Mirjam, KretzschmarUniversity Medical Centre Utrecht
Abid Ali, LashariStockholm University
Ka Yin, LeungUniversity of Utrecht
Fabio, LopesUniversidad de Chile
Malwina, LuczakQueen Mary University of London
Anders, Martin-LöfStockholm University
Pierre-Andre, MaugisUniversity College London
TJ, McKinleyUniversity of Exeter
Joel, MillerInstitute for Disease Modeling
Denis, MollisonHeriot-Watt University
Tobias, MuellerUniversity of Utrecht
Peter, NealLancaster University
Philip, O'NeillUniversity of Nottingham
Lorenzo, PellisUniversity of Warwick
Nicolás, RiveraKing's College London
Mick, RobertsMassey University
Sebastian, RosengrenStockholms universitet
Joshua, RossUniversity of Adelaide
Kieran, SharkeyUniversity of Liverpool
David, SirlUniversity of Nottingham
Eleanor, TannerMIGSAA
Viet Chi, TranUniversité Lille 1
Pieter, TrapmanStockholm University
Tatyana, Turova SchmelingLund University
Andy, WhiteHeriot-Watt University