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Seminars (IDP)

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Event When Speaker Title Presentation Material
IDPW01 11th May 2020
18:00 to 19:00
Graham Medley PLENARY TALK - Transmission dynamic models for COVID-19:policy and beyond
I will discuss the role of modelling in providing advice to HMG during the current COVID-19 epidemic. There are some model structures that we are missing, and some processes for providing real time estimates that we need to develop.  




IDPW01 12th May 2020
11:30 to 12:30
Ben Cowling Epidemiology and control in Hong Kong
IDPW01 14th May 2020
15:00 to 16:00
Marc Lipsitch
IDPW02 18th May 2020
14:10 to 14:45
Adam Kucharski LSHTM - COVID19 modelling and open outbreak science
IDPW02 18th May 2020
14:45 to 15:00
Lorenzo Pellis - Manchester
IDPW02 18th May 2020
16:30 to 17:30
PLENARY TALK - Computational Epidemiology at the time of COVID 19 - Alessandro Vespingani (Northeastern)
IDPW02 19th May 2020
10:30 to 11:00
Peter Challenor Uncertainty Quantification
IDPW02 19th May 2020
11:15 to 11:45
Steven Riley Socio-spatial networks
IDPW02 20th May 2020
10:00 to 10:30
Vittoria Colizza ( INSERM) - Infection control in facilities
IDPW02 20th May 2020
14:00 to 14:30
Sam Jenness (Emory) - Statistical approaches to modelling epidemics across contact networks
IDPW02 20th May 2020
15:00 to 15:30
Simon Frost (Microsoft) - Phylodynamics of SARS - Cov2
IDPW02 21st May 2020
09:30 to 10:00
Pavel Krivitsky Statistical models for bipartite contact networks: methods and data
IDPW02 21st May 2020
10:00 to 10:30
Ian Hall Developing monitoring indicators and models for disease outbreaks in care homes
IDPW02 21st May 2020
10:45 to 11:15
Niel Hens - a modelling perspective on the Covid 19 coronavirus outbreak in Belgium
IDPW02 22nd May 2020
14:00 to 14:30
Ira Longini Vaccine development
IDPW02 22nd May 2020
14:30 to 15:00
Bobby Reiner (HME) - IHME covid19 model
IDPW02 22nd May 2020
16:30 to 17:30
Daniela De Angelis PLENARY LECTURE - Nowcasting and Forecasting of COVID -19 pandemic in England
IDP 1st June 2020
11:00 to 12:30
Contact Tracing – Learning from Other Diseases
IDP 5th June 2020
14:30 to 15:00
Talk on PyRossGeo - Ronojoy Adhikari
IDP 5th June 2020
15:00 to 15:30
Denis Mollison Five Challenges for Spatial Epidemic Models
IDP 5th June 2020
15:30 to 15:45
Break
IDP 5th June 2020
15:45 to 16:15
Discussions
IDP 8th June 2020
13:30 to 17:00
Modelling Contact Tracing
IDP 10th June 2020
14:00 to 14:05
EXPERT JUDGEMENT - Welcome from David Abrahams (INI Director)
IDP 10th June 2020
14:05 to 14:35
Willy Aspinall (Bristol) - Expert elicitation of scientific uncertainties using Cooke's Classical Model: applicability to COVID-19 risk assessments

Abstract: Many COVID-19 research projects have elements of forecasting, planning and urgent decision-making that must be executed before solid data are available.  Some approaches, which neglect formal uncertainty quantification, can compromise estimates of low-probability/high-consequence outcomes: this could be a critical flaw when evaluating complex COVID-19 risks.  Adopting a structured elicitation procedure can reduce risk assessment weaknesses associated with inappropriate and sometimes misleading parameter and modelling assumptions. Several varieties of expert elicitation are practised, often categorised as 'behavioural aggregation' or 'mathematical aggregation'.  Cooke's Classical Model is of the latter class and we have used it extensively to provide scientific support for critical public safety decisions during volcanic eruptions. The method has garnered a track record for formalising the determination of input variable or parameter uncertainty distributions for risk modelling when conventional data do not exist or are undependable, e.g. with the adaptive Bayes Belief Net formalism for combining disparate strands of uncertain scientific evidence.  The underpinning algorithm provides empirical control on expert performance scoring and weighting for combining experts’ judgments into an auditable, rational consensus.  While it has become an established and validated elicitation procedure in many disciplines, this approach has not found widespread use in epidemiological modelling, even though it is well-suited to risk issues relating to emergent zoonoses.  We briefly summarise the principles of the method and how it is applied to real-world critical decision problems, mentioning a few case studies closely analogous to the present coronavirus problem.   Resources: The best link to materials relevant to my talk is Roger Cooke’s website: <rogermcooke.net> It has a lot of relevant stuff, and includes a link to a video of a 1-hour talk on the Classical Model for Structured Expert Judgment, which I gave at CDC Atlanta in May 2107.  



 

IDP 10th June 2020
14:35 to 15:05
Kevin Wilson (Newcastle) - Uncertainty elicitation and quantification from experts

Abstract: The incorporation of uncertainty in assessments and predictions from mathematical models is critical, especially if the models are to be used to support real-world decisions. In fast moving situations such as a global pandemic of an infectious disease, then data to parameterise models are typically patchy and incomplete, and sufficient suitable data may not exist for many parameters in model runs of possible future scenarios. In such cases expert judgements can play an important role, both to specify uncertainty distributions for parameters with no available data and to supplement data where they are available (via Bayes Theorem, or more informally). In this talk I will discuss the elicitation of uncertainty distributions for individual unknowns from a single expert, the combination of the opinions of multiple experts on an unknown into a single uncertainty distribution and the elicitation of graphical models, with an emphasis on Bayesian networks, to produce suitable model structures from experts over multiple dependent unknowns. I will emphasise a behavioural aggregation approach, the SHeffield Elicitation Framework (SHELF), for the combination of the opinions of multiple experts, which will complement the talk from Prof Aspinall on a mathematical aggregation approach, the Classical Method. A running example on the development of a diagnostic test will be used to illustrate the ideas, and I will try to bring out particular issues surrounding infectious disease modelling.   Resources: ·       A probabilistic judgements e-learning course, aimed at explaining elicitation generally and the Sheffield ELicitation Framework specifically: http://www.tonyohagan.co.uk/shelf/ecourse.htm ·       A textbook providing comprehensive coverage of elicitation: O'Hagan et al (2006). Uncertain Judgements: Eliciting Experts' Probabilities, Wiley. ·       Resources to conduct an elicitation using SHELF including slide sets, advice and document templates:http://www.tonyohagan.co.uk/shelf/ ·       A series of short videos for an online course on Structured Expert Judgment provided by TU Delft (links are near the top of the page): http://rogermcooke.net/ ·       A textbook discussing the elicitation of probabilistic models:  J. Q. Smith (2010). Bayesian decision analysis: principles and practice. Cambridge University Press.  



 

IDP 10th June 2020
15:05 to 15:35
Katriona Shea (Penn State) - Harnessing multiple models for outbreak management

Abstract: The coronavirus disease 2019 (COVID-19) pandemic has triggered efforts by multiple modeling groups to forecast disease trajectory, assess interventions, and improve understanding of the pathogen. Such models can often differ substantially in their projections and recommendations, reflecting different policy assumptions and objectives, as well as scientific, logistical, and other uncertainty about biological and management processes. Disparate predictions during any outbreak can hinder intervention planning and response by policy-makers, who may instead choose to rely on single trusted sources of advice, or on consensus where it appears. Thus, valuable insights and information from other models may be overlooked, limiting the opportunity for decision-makers to account for risk and uncertainty and resulting in more lives lost or resources used than necessary. We advocate a more systematic approach, by merging two well-established research fields. The first element involves formal expert elicitation methods applied to multiple models to deliberately generate, retain, and synthesize valuable individual model ideas and share important insights during group discussions, while minimizing various cognitive biases. The second element uses a decision-theoretic framework to capture and account for within- and between-model uncertainty as we evaluate actions in a timely manner to achieve management objectives.   Resources: ·         Bjørnstad, O., Shea, K., Krzywinski, M. & Altman, N. (2020) Modelling Infectious Epidemics. Nature Methods (2020). https://doi.org/10.1038/s41592-020-0822-z ·         Associated shiny app: https://github.com/martinkrz/posepi1. ·         Outreach seminar “Disease outbreak control: Harnessing the power of multiple models to work smarter, not harder”: https://science.psu.edu/frontiers 

https://science.sciencemag.org/content/368/6491/577.summary


 

IDP 10th June 2020
15:35 to 16:05
Marissa McBride (Imperial) - Lessons from structured expert elicitation using the IDEA protocol

Abstract:  Expert judgment can support policy decision-making in situations where data are scarce, knowledge is incomplete and decisions are imminent. Research has demonstrated both the potential value and the potential dangers of expert judgments, and established the benefit of using systematic, structured procedures to elicit judgments from experts which anticipate and correct for the most severe and predictable limitations of expert opinion. In this presentation I outline the origins and development of the IDEA protocol, a Delphi-style structured elicitation procedure that combines psychologically robust interactions among experts with mathematical aggregation of individual estimates and structured question formats to improve the accuracy of elicited judgments. I discuss examples and emerging insights from its use to support decision-making across a range of applications including biosecurity, natural resource management and real-time geopolitical forecasting. Drawing from these experiences I reflect on the challenges presented by COVID-19 and how structured elicitation procedures might best support epidemiological modelling and simulation efforts in providing timely public health policy advice.   Resources: IDEA protocol for structured expert elicitation – key reference 1. Hemming, Victoria, et al. "A practical guide to structured expert elicitation using the IDEA protocol." Methods in Ecology and Evolution 9.1 (2018): 169-180. [This article provides a practical step-by-step guide to carrying out a structured elicitation using the IDEA protocol. The supplementary information includes ready-made templates and resources for planning and implementing a structured elicitation using IDEA] An excellent introductory blog post discussing this article and the need for structured expert elicitation is available here: https://methodsblog.com/2018/03/27/idea-protocol-2/ Expert elicitation references – introductory & overview 2. Morgan, M. Granger. "Use (and abuse) of expert elicitation in support of decision making for public policy." Proceedings of the National academy of Sciences 111.20 (2014): 7176-7184. [Excellent overview article for using expert judgment that is accessible for most audiences, and with an excellent reference list for further reading] 3.  Alahmadi, Amani, et al. "Influencing public health policy with data-informed mathematical models of infectious diseases: Recent developments and new challenges." Epidemics (2020): 100393. [Includes coverage of the role and challenges for expert elicitation from the perspective of modelling infectious diseases]   Cognitive Biases 4. Cognitive biases infographic. Structured elicitation protocols include steps that attempt to reduce the impacts of many of these biases on the judgments elicited from experts.   https://www.visualcapitalist.com/every-single-cognitive-bias/ A more complete version of the cognitive biases infographic that includes definitions of each of the biases is also available here



 

IDP 10th June 2020
16:05 to 17:00
Panel Discussion (questions submitted via slido and asked by chair)
IDP 10th June 2020
17:00 to 17:30
Break
IDP 10th June 2020
17:30 to 18:30
PLENARY TALK - Robin Hanson (George Mason University & Oxford) - Pay Experts for Results, Not Prestige

Abstract:  Doctors, lawyers, priests, teachers, politicians, fund managers, researchers, and more - how can we get experts to serve us? We have five main ways: pay for results, require procedures, or pick based on track records, prestige, or loyalty. Picking on prestige is most common. But paying for results seems most robust, though for cash-paid experts it requires that customers prevent expert coordination, or wait long to pay. For experts who forecast, paying for results can often be achieved via prediction markets, which have great untapped potential.


Resources: http://hanson.gmu.edu/expert.pdf http://hanson.gmu.edu/futarchy.html http://www.overcomingbias.com/2019/07/radical-pay-for-results.html http://www.overcomingbias.com/2020/05/five-ways-to-rate.html http://www.overcomingbias.com/2020/06/science-2-0.html  

 

IDP 11th June 2020
10:00 to 10:30
Whole-cost economic modelling of pandemics - Peter van Manen, Clement O'Rourke (Frazer-Nash)
Topic – Complex Models




IDP 11th June 2020
11:00 to 11:10
Control theory in relation to epidemic interventions - Brian Neve (Spiro) Control
Topic – Complex Models




IDP 11th June 2020
14:00 to 16:00
Contact Tracing follow-up discussions
Topic – Dynamics of Transmission
IDP 12th June 2020
15:30 to 15:45
General Discussions - CHAIR Philip Dawid
IDP 12th June 2020
15:30 to 17:00
OPEN ZOOM MEETING - session 3 follow up dicussions
IDP 15th June 2020
09:00 to 10:30
OPEN ZOOM MEETING - session 3 follow up dicussions - Chair William Probert
IDP 22nd June 2020
08:30 to 09:50
Modelling for SARS-CoV2 - what can we learn from China? Speakers: Jun Yan, Tie-Yan Liu, Jinzhi Lei, Juanzi Li
IDP 22nd June 2020
09:50 to 10:00
Modelling for SARS-CoV2 - what can we learn from China? Questions for Speakers: Jun Yan, Tie-Yan Liu, Jinzhi Lei, Juanzi Li
IDP 22nd June 2020
10:00 to 10:40
Modelling for SARS-CoV2 - what can we learn from China? - speakers: Adam Kucharski, Louise Dyson, Steven Riley, Christophe Fraser
IDP 22nd June 2020
10:40 to 11:00
Modelling for SARS-CoV2 - what can we learn from China? Questions and discussions
IDPW03 23rd June 2020
13:30 to 13:50
Jane Heffernan - York University Toronto
IDPW03 23rd June 2020
13:50 to 14:00
Robin Thompson (EpiEstim)
IDPW03 23rd June 2020
14:00 to 14:20
Eben Kenah - Ohio State University
IDPW03 23rd June 2020
14:20 to 14:40
Sam Abbott - London School of Hygiene and Tropical Medicine
IDPW03 23rd June 2020
14:40 to 15:00
Discussion
IDPW03 23rd June 2020
15:00 to 15:20
Katie Gostic - University of Chicago
IDPW03 23rd June 2020
15:20 to 15:30
Discussion
IDPW03 25th June 2020
09:30 to 09:50
Frank Ball - University of Nottingham
IDPW03 25th June 2020
09:50 to 10:10
Lorenzo Pellis - University of Manchester
IDPW03 25th June 2020
10:10 to 10:30
TBC
IDPW03 25th June 2020
10:30 to 11:00
Discussion
IDP 1st July 2020
17:00 to 18:00
Paul Linden PLENARY TALK - COVID-19: RAMP Task 7. Environmental and aerosol transmission
The Royal Society initiative to provide Rapid Assistance in Modelling the Pandemic (RAMP) has garnered a large number of scientists across the UK working voluntarily in a wide range of issues associated with the current pandemic. In this talk I will describe the outputs of the fifty odd scientists with expertise, broadly speaking, in fluid mechanics who have been considering aspects of the airborne transmission of the virus. Post lockdown major risks of infection are associated with occupancy of public buildings such as restaurants, schools, and other places where people congregate indoors, and in public transportation. I will describe what we have learnt over the past couple of months about the impact of building ventilation, the deposition of droplets, modes of exhalation and inhalation and other factors such as the effects of occupancy levels and the movement of people in these indoor environments, and what seem to be the key outstanding questions.




IDP 2nd July 2020
09:30 to 11:30
Uncertainty Quantification
Chair:
Peter Challenor Why do uncertainty quantification
Speakers;
Evan Baker (Exeter) Emulating Stochastic Models
Building emulators for complex models typically involves Gaussian processes. For stochastic models, the flexibility of a Gaussian process is a nice feature, but modifications are needed to account for the noisiness of simulations. In this talk I will summarise some key attributes of stochastic models and how these can change the emulation methodology. Additionally, I will briefly talk about the simulation design issues that arise for stochastic models.
Jeremy Oakley (Sheffield)  - Introduction to Probabilistic Sensitivity Analysis
Mathematical models of infectious diseases invariably have uncertainty about the correct values of some of their model inputs/parameters. This induces uncertainty in the model outputs. In some situations, it may be desirable to reduce this uncertainty, by collecting more data about uncertain model inputs, before using the model outputs to inform decisions. However, it is unlikely that all inputs are 'equally important': some will contribute to output uncertainty more than others. I will discuss how probabilistic sensitivity analysis can be used to identify which uncertain inputs are most influential, and describe simple computational tools that can be used for implementing the analysis, based on a random sample of model runs.








IDP 3rd July 2020
17:00 to 18:00
Adam Kucharski PLENARY TALK - Reproduction numbers and superspreading – how to measure disease transmission
During a pandemic like COVID-19, there is an urgent need to understand how easily the infection is spreading. Values like the reproduction number R, which measure transmission in a population, have therefore become prominent terms. But how are these numbers estimated? What are their limitations? And what can they tell us about how to control epidemics?




IDPW04 7th July 2020
14:00 to 16:00
Raluca Eftimie, Grant Lythe, Farzad Fatehi Chenar Session 1

 


IDPW04 7th July 2020
14:05 to 14:30
Grant Lythe Stochastic dynamics of Francisella Tularensis infection
Jonty Carruthers, Martin Lopez-Garcia, Grant Lythe, Carmen Molina-Paris (Leeds). Joseph Gillard, Thomas R Laws, Roman Lukaszewski
(Dstl)
With a mouse infection model, agent-based computation and mathematical analysis, we study the pathogenesis of Francisella Tularensis
infection. A small initial number of bacteria enter host cells and proliferate inside them, eventually destroying the host cell and releasing numerous copies that infect other cells.  Our analysis of disease progression is based on a stochastic model of a population of infectious agents inside one host cell, extending the birth-and-death process by the occurrence of catastrophes: cell rupture events that affect all bacteria in a cell simultaneously.  We compare our analysis with the results of agent-based computation and, via Approximate Bayesian Computation, with experimental measurements carried out after of murine aerosol infection with the virulent SCHU S4 strain of the bacterium.
If I have time, I will also talk about Ebola, still a significant risk to humankind. Synthetic virology has been used to clone and manufacture two deletion defective genomes. These genomes were tested with Ebola virus using in vitro cell culture and shown to inhibit viral replication.  From in vitro experimental data, we identify parameters in a mathematical model of the infection. We examine the time an infected cell spends in the eclipse phase (the period between infection and the start of virus production), as well as the rate at which infectious virions lose infectivity.


IDPW04 7th July 2020
14:30 to 15:00
Raluca Eftimie TBA
IDPW04 7th July 2020
15:00 to 15:30
Farzad Fatehi Chenar Multiscale within-host modelling of SARS-CoV-2 infection reveals benefits and risks of early Remdesivir treatment
The SARS-CoV-2 outbreak has infected over ten million, and killed over 500,000, individuals worldwide, making the development of antiviral treatments against this virus a priority. Recent studies have identified Remdesivir as an effective antiviral treatment option for COVID-19. I will present a new stochastic agent based model for the intracellular dynamics of a SARS-CoV-2 infection that includes details on all essential steps of a viral life cycle, from viral entry to virion release. Using this model, I evaluate the effect of Remdesivir on the production of new virions. In a next step, I propose an intercellular model to study the viral dynamics within the body of an infected patient. The intercellular model is fitted to data recording the progress of viral load in 12 patients with COVID-19, showing how differing strengths of immune response can explain the variety of infection spans seen in patients. Coupling the intra- and intercellular models allows for a comparative analysis of Remdesivir therapy for patients with different types of immune response.




IDPW04 7th July 2020
15:30 to 16:00
Discussion
IDP 8th July 2020
12:00 to 13:00
Session 2 - PLENARY TALK by Ruth Bowness - University of St. Andrews - Modelling within-host tuberculosis infection using a hybrid multiscale individual-based model
IDP 10th July 2020
09:30 to 13:00
Urban Analytics
Chair: Mark Birkin

9:30 - 11:30 - Session One:Urban Analytics
9:30 - 9:50 Introduction and overview, Mark Birkin
9:50 - 10:10 Microsimulation, Nik Lomax, Karyn Morrissey and Jamil Nur 
10:10 - 10:30 Modelling behaviour, Adam Dennett, Richard Milton, Ying Jin and Mike Batty 
10:30 - 10:50 Epidemic simulation and scenario planning: Gavin Shaddick, Nick Malleson

10:50 - 11:30 Discussion

11:30-12:00 - Break
12:00 - 13:00 - Session Two:Small spaces 
12:00 - 12:40 - Introduction to key projects: Mike Batty, Gerry Casey, Ed Galea & others

12:40 - 13:00 - Discussion

University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons