EPSRC Centre for Mathematics of Precision Healthcare

Lead Research Organisation: Imperial College London
Department Name: Dept of Mathematics

Abstract

Medicine is undergoing a simultaneous shift at the levels of the individual and the population: we have unprecedented tools for precision monitoring and intervention in individual health and we also have high-resolution behavioural and social data. Precision medicine seeks to deploy therapies that are sensitive to the particular genetic, lifestyle and environmental circumstances of each patient: understanding how best to use these numerous features about each patient is a profound mathematical challenge. We propose to build upon the mathematical, computational and biomedical strengths at Imperial to create a Centre for the Mathematics of Precision Healthcare revolving around the theme of multiscale networks for data-rich precision healthcare and public health. Our Centre proposes to use mathematics to unify individual-level precision medicine with public health by placing high-dimensional individual data and refined interventions in their social network context. Individual health cannot be separated from its behavioural and social context; for instance, highly targeted interventions against a cancer can be undermined by metabolic diseases caused by a dietary behaviour which co-varies with social network structure. Whether we want to tackle chronic disease or the diseases of later life, we must simultaneously consider the joint substrates of the individual together with their social network for transmission of behaviour and disease. We propose to tackle the associated mathematical challenges under the proposed Centre bringing to bear particular strengths of Imperial's mathematical research in networks and dynamics, stochastic processes and analysis, control and optimisation, inference and data representation, to the formulation and analysis of mathematical questions at the interface of individual-level personalised medicine and public health, and specifically to the data-rich characterisation of disease progression and transmission, controlled intervention and healthcare provision, placing precision interventions in their wider context.
The programme will be initiated and sustained on core research projects and will expand its portfolio of themes and researchers through open calls for co-funded projects and pump-priming initiatives.
Our initial set of projects will engage healthcare and clinical resources at Imperial including: (i) patient journeys for disease states in cancer and their successive hospital admissions; multi-omics data and imaging characterisations of (ii) cardiomyopathies and (iii) dementia and co-morbidities; (iv) national population dynamics for epidemiological and epidemics simulation data from Public Health; social networks and (v) health beliefs and (vi) health policy debate. The initial core projects will build upon embedded computational capabilities and data expertise, and will thus concentrate on the development of mathematical methodologies including: sparse state-space methods for the characterisation of disease progression in high-dimensional data using transition graphs in discrete spaces; time-varying networks and control for epidemics data; geometrical similarity graphs to link imaging and omics data for disease progression; stochastic processes and community detection from NHS patient data wedding behavioural and social network data with personal health indicators; statistical learning for the analysis of stratified medicine. The mathematical techniques used to address these requirements will need to combine, among others, ingredients from dynamical and stochastic systems with graph-theoretical notions, sparse statistical learning, inference and optimisation. The Centre will be led by Mathematics but researchers in the Centre span mathematical, biomedical, clinical and computational expertise.

Planned Impact

The societal impact of the proposed research will be very broad as the Centre will be actively integrated with NHS bodies (including the 5 hospitals in the Imperial Healthcare Trust) Dementia UK and Public Health England. Our centre is explicitly targeted at the challenges these organisations face: large streaming, incomplete networked datasets which have to be used as a basis for both patient interventions and wider public health strategy. By proposing control strategies for both infectious and chronic disease we hope to move us towards an optimised use of resources in the health service.
The connections of the Centre with the Institute for Global Health Innovation and the eHealth Unit adds another axis of impact towards influencing policy making. An example is the analysis of patients according to their temporal patterns of NHS usage, which could be used to improve patient segmentation leading to improved resource allocation and patient satisfaction. We expect that the British and International public will be beneficiaries of this research through better decision making at the NHS, identification and intervention for complex diseases as well as social aspects of health.
In addition, we have specific interfaces with two third sector representatives: Cancer Research UK and the British Heart Foundation. In both cases precision data is being acquired at the individual level (omics, imaging) but the need is to distill from this data clinical categories, appropriate interventions and optimal symptom management. Our methods would help to bridge this gap and we will actively explore these possibilities with the clinical branches of CRUK and BHF associated with NHS Imperial hospitals. Prime examples of such applications are showcased by existing collaborations of Prof Rueckert with Prof Matthews and Prof Cook on therapeutic applications of medical image analysis.
We will also pursue the potential impact of our research on social network analysis, as a means of obtaining relevant information for healthcare provision and of influencing opinion formation. There are further connections with The Governance Lab at NYU and an NHS-funded project on the use of social networks to find relevant expertise for particular needs. We thus expect that our research can have an impact on social scientists as well as clinicians working on issues related to healthcare provision.
Another axis of impact is through industrial connections. We expect to have an impact on the computational side through the development of novel algorithms for Big Data approaches, imaging analyses, and specific sparse coding approaches for signal processing. Similarly, pharma companies and broad-based companies (such as Syngenta) will benefit from the characterisation of experimental processes where high-dimensional data is collected and from the development of detection markers.
Our work will impact other areas of basic research (specifically data science, network analysis, and systems and synthetic biology) and we will ensure that the impact is maximised by our extensive programme of workshops and challenge-led activities together with a visitor programme with high-profile speakers.
The researchers who will work in this Centre will be uniquely trained, acquiring expertise in mathematical tools coupled to big data as well as healthcare applications. Such expertise is in high demand and the researchers will be able to become national and indeed international leaders themselves in an area where there is a clear shortage of expertise, thus contribution to the UK knowledge base.
Finally the Applied Mathematics community will benefit by the recognition that excellent mathematics and computational skills can be brought together to help solve problems relevant to a broad section of society.

Publications

10 25 50
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Aceves-Sanchez P (2021) A new model for the emergence of blood capillary networks in Networks & Heterogeneous Media

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Amad A (2020) Plastic Adaptation to Pathology in Psychiatry: Are Patients with Psychiatric Disorders Pathological Experts? in The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry

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Arnaudon A (2018) Structure preserving noise and dissipation in the Toda lattice in Journal of Physics A: Mathematical and Theoretical

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Arnaudon A (2018) A Geometric Framework for Stochastic Shape Analysis in Foundations of Computational Mathematics

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Arnaudon A (2018) String Methods for Stochastic Image and Shape Matching in Journal of Mathematical Imaging and Vision

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Arnaudon A (2022) Diffusion Bridges for Stochastic Hamiltonian Systems and Shape Evolutions in SIAM Journal on Imaging Sciences

 
Description The findings are extensive and can be found in the publications and online at http://www.imperial.ac.uk/mathematics-precision-healthcare/

A summary of findings include:

* Use of social network analysis for the study of the debate on Twitter following the announcement of the release by the NHS of the care.data scheme identified the main players in the debate; the relative lack of response/influence of some of the official accounts related to the NHS and Department of Health; the identification of topics of conversation and communities of users with different interests and motivation; the different roles of users in the debate. This was done in collaboration with the Big Data Analysis Unit of the Institute of Global Health Innovation.
* Analysis of Twitter activity around the hashtag 'diabetes' over 1 year (several million tweets) was used to characterise the topics, users and communities surrounding the topic. This was done using a mixed-methods approach combining social science expertise and mathematical analysis of the networks and data. The analysis revealed a mixed landscape of users with heavy influence of commercial organisations and interests, and individual accounts (not institutional) which have gained considerable influence. These groups are sometimes non-profit organisations, many of which are locally organised. The influence of large public health bodies is not as widespread as expected. Commercial organisations also pass as authorities in the debate. The use of humour is also a constant in the debate. This has been done in collaboration with the Oxford School of Anthropology.
* Analysis of beliefs related to vaccine acceptance across the world. It has revealed the widespread differences in beliefs held with respect to vaccines across the world. Widely publicised outcomes in the press.
* Methods to infer pathways of trait acquisition from observational data have been developed and applied to malaria data collected in Equatorial Africa, as well as for the analysis of task completion on online courses by students at Imperial
* Unsupervised clustering of documents has been applied to NHS incident records from NHS Trusts associated with Imperial to establish the severity and types of incidents recorded online as an aid to monitor events
* Community detection algorithms have been used to detect the sharing of patterns across hospitals using 2 million of NHS patient records as a way to establish the interdependence of different hospitals and sharing of practice.
* Analysis of a text messaging system for mental health (Shout) was done in collaboration with Mental Health Innovations merging different techniques in NLP and machine learning with the aim to improve service and help volunteers and users to develop more helpful conversations online.
* Application of network analysis techniques to healthcare-acquired infections (in hospitals) applied to COVID-19 and antimicrobial-resistant bacteria --- This was done in collaboration with NHS Trusts as well as hospitals in Switzerland and Singapore.
* Analysis of the Twitter network of followers of schools in London and Newcastle to quantify the online effect of social hazards
* Development of a tool to analyse protein structures using graph theory that allows state-of-the-art prediction of allosteric sites --- online and available to the research community. It has been used to identify druggable spots in RSK4 with applications to cancer resistance.
* Characterisation of temporal features of time series of patients suffering essential tremor that allows the identification of their responsiveness to extra-cranial stimulation to reduce tremor.
* Development of a tool (SC3) for the analysis and clustering of single-cell RNA-seq data widely used in labs across the world --- available on Bioconductor with tens of thousands of downloads.
* Develop methodologies that extend the use of graph convolutional networks by introducing graph diffusion operators and geometric graph construction into that machine learning paradigm and improved performance in several tasks.
* Application of graph methods has led to new methods for laser networks with controllable outputs in collaboration with experimentailsts
Exploitation Route See the description above. It has led to extensive collaborations with biomedical scientists, clinicians, NHS workers, computer scientists, chemists, physicists, bioinformaticians working in diverse areas of healthcare, e.g., under CRUK, BHF, Dementia Research UK, MRC, pharma
Sectors Creative Economy,Digital/Communication/Information Technologies (including Software),Education,Healthcare,Government, Democracy and Justice,Pharmaceuticals and Medical Biotechnology

URL http://www.imperial.ac.uk/mathematics-precision-healthcare/
 
Description * Computational methods have been used by Sinnia Inc (Mexico) for data analytics * Astrazeneca and GSK have both given funds to pursue exploration of applications related to drug discovery through protein interactions * Methods for time series analysis of network usage have been used to analyse online behaviours of students taking courses at Imperial College. This has been funded by the educational programme at Imperial with an extra RA for two years and is being explored by a start up EdX. * Analysis of patient-sharing networks in NHS hospitals in England has been applied to find optimised sharing of information * Network analytics tools have been deployed to analyse infection spread in hospitals for COVID-19 as well as antibiotic resistant bacteria. * Community detection algorithms for graphs have been applied to the analysis of patient patterns in the NHS to guide the design of catchment areas * Social network inference has been applied to the analysis of vaccine hesitancy across the world
First Year Of Impact 2018
Sector Creative Economy,Digital/Communication/Information Technologies (including Software),Education,Healthcare,Government, Democracy and Justice,Pharmaceuticals and Medical Biotechnology
Impact Types Societal,Economic,Policy & public services

 
Description 'Good Work Monitor' report
Geographic Reach National 
Policy Influence Type Gave evidence to a government review
URL https://www.imperial.ac.uk/news/213753/report-the-good-work-monitor/
 
Description All-Party Parliamentary Group for Social Science and Policy: Prof Yaliraki has been invited to attend meetings of the All-Party Parliamentary Group for Social Science and Policy (previously known as All Party Parliamentary Group on Global Uncertainties) in the House of Commons. These meetings are open to all MPs and Lords, and their staff, plus leading policymakers and experts in fields of interest. They operate under the Chatham House Rule.
Geographic Reach National 
Policy Influence Type Gave evidence to a government review
 
Description Department of Health: Dr Greenbury, formerly an analyst at the Department of Health, is liaising with personnel there to use the methods developed within CMPH on ageing surveys
Geographic Reach National 
Policy Influence Type Influenced training of practitioners or researchers
Impact Dr Greenbury, formerly an analyst at the Department of Health, is liaising with personnel there to use the methods developed within CMPH on ageing surveys
 
Description Governmental Digital Services: Dr Expert acts as an academic consultant for the Data Science Team at the Governmental Digital Services, meeting regularly with team members;
Geographic Reach National 
Policy Influence Type Participation in a advisory committee
 
Description Prof Barahona has advised TheGovLab (Noveck) in issues related to Zika monitoring in the project Smarter Crowdsourcing for Zika with partners from Argentina, Brazil, Colombia, Panama and the Inter-American Development Bank.
Geographic Reach South America 
Policy Influence Type Participation in a advisory committee
 
Description Prof Oyarzun is heavily involved with the World Economic Forum (WEF), sitting in the WEF Global Future Council on Biotechnologies alongside select experts from academia and the private sector, including a Nobel laureate and opinion leaders. Oyarzún has attended two WEF Summits in Dubai and has been invited to join the Scientific Board of the Center for the Fourth Industrial Revolution to advise on governance frameworks for precision medicine globally. Oyarzún's recommendations on mathematics for precision healthcare and biotechnology have been published in high profile venues
Geographic Reach Multiple continents/international 
Policy Influence Type Participation in a advisory committee
 
Description Automation technologies: work and welfare through COVID-19
Amount £183,357,200 (GBP)
Funding ID SFS /FR-000022922 
Organisation Nuffield Foundation 
Sector Charity/Non Profit
Country United Kingdom
Start 04/2021 
End 05/2024
 
Description Care as a Complex System: Understanding the Network Dynamics of Healthcare Delivery
Amount £300,000 (GBP)
Funding ID 215938/Z/19/Z 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 09/2019 
End 09/2023
 
Description Children's places: how they can shape health and influence social and economic outcomes
Amount £312,191 (GBP)
Funding ID FR-000002348 
Organisation The Health Foundation 
Sector Charity/Non Profit
Country United Kingdom
Start 04/2020 
End 04/2022
 
Description Children's places: how they can shape health and influence social and economic outcomes
Amount £31,219,100 (GBP)
Funding ID FR-000002348 
Organisation The Health Foundation 
Sector Charity/Non Profit
Country United Kingdom
Start 04/2020 
End 04/2022
 
Description Control Engineering Inspired Design Tools for Synthetic Biology
Amount £429,418 (GBP)
Funding ID EP/I032223/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 12/2011 
End 06/2015
 
Description Crick-Turing Biomedical Data Science Award
Amount £44,780 (GBP)
Funding ID PO# 4807 
Organisation Alan Turing Institute 
Sector Academic/University
Country United Kingdom
Start 03/2020 
End 03/2021
 
Description Discover-NOW: The Health Data Research Hub for Real World Evidence
Amount £5,732,432 (GBP)
Funding ID MC_PC_19007 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 09/2019 
End 08/2022
 
Description Evidence based policy making - Call for Multi-Faculty Centres and Networks - Using network analysis to support local healthcare decision-making' Call for Multi-Faculty Centres and Networks
Amount £38,500 (GBP)
Organisation United Kingdom Research and Innovation 
Department Research England
Sector Public
Country United Kingdom
Start 01/2020 
End 03/2020
 
Description Future Leader Fellowship
Amount £1,390,676 (GBP)
Funding ID MR/T018429/1 
Organisation United Kingdom Research and Innovation 
Sector Public
Country United Kingdom
Start 03/2020 
End 03/2023
 
Description Health Data Research UK
Amount £1,353,838 (GBP)
Funding ID CAPL01 
Organisation Health Data Research UK 
Sector Private
Country United Kingdom
Start 03/2018 
End 03/2023
 
Description LOCOMOTION (long COVID multidisciplinary consortium: optimising treatments and services across the NHS) study.
Amount £3,400,000 (GBP)
Organisation National Institute for Health Research 
Sector Public
Country United Kingdom
Start 03/2021 
End 02/2024
 
Description Mental Health Innovations
Amount £40,000 (GBP)
Organisation Mental Health Innovation Network (MHIN) 
Sector Charity/Non Profit
Country Switzerland
Start 09/2019 
End 09/2020
 
Description Multi-level modeling interventions to reduce the burden of carbapenem-resistant organisms within and between hospitals
Amount £9,859 (GBP)
Funding ID 1842-01-IMP  
Organisation Centers for Disease Control and Prevention (CDC) 
Sector Public
Country United States
Start 07/2017 
End 05/2020
 
Description Pilot - AI for Translational Myelin Imaging
Amount £440,000 (GBP)
Organisation Biogen Idec 
Sector Private
Country United States
Start 12/2018 
End 03/2020
 
Description Semiconductor lasers on a graph
Amount £782,468 (GBP)
Funding ID EP/T027258/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 06/2020 
End 01/2023
 
Description Statistical physics of cognition
Amount £2,165,717 (GBP)
Funding ID EP/W024020/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 03/2022 
End 03/2025
 
Description Surveillance after Resection of Oesophageal Cancer (SAROC)
Amount £23,951 (GBP)
Organisation Cancer Research UK 
Sector Charity/Non Profit
Country United Kingdom
Start 09/2021 
End 03/2022
 
Description The control of mitochondrial populations
Amount £270,436 (GBP)
Organisation The Leverhulme Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 09/2019 
End 09/2022
 
Description UK DRI Pilot Studies Programme
Amount £43,814 (GBP)
Funding ID PILOT01 
Organisation UK Dementia Research Institute 
Sector Charity/Non Profit
Country United Kingdom
Start 05/2019 
End 06/2020
 
Description UKRI Centre for Doctoral Training in Artificial Intelligence for Healthcare
Amount £7,843,814 (GBP)
Funding ID EP/S023283/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 03/2019 
End 09/2027
 
Description UNIVERSITY OF CAMBRIDGE: Harrison Donation
Amount £59,018 (GBP)
Organisation University of Cambridge 
Sector Academic/University
Country United Kingdom
Start 09/2019 
End 09/2021
 
Description Understanding, monitoring and mitigating the impact of the pandemic on HCAI and antimicrobial resistance in in acute care, for both COVID-19 and non-COVID-19 patient populations
Amount £167,316 (GBP)
Funding ID 2020/1072715-1 
Organisation World Health Organization (WHO) 
Sector Public
Country Global
Start 11/2020 
End 02/2021
 
Description University of Oslo
Amount £12,675 (GBP)
Organisation University of Oslo 
Sector Academic/University
Country Norway
Start 09/2018 
End 01/2019
 
Description Alan 
Organisation Alan Turing Institute
Country United Kingdom 
Sector Academic/University 
PI Contribution The Crick-Turing Biomedical Data Science Awards (BDSA) provide funding to early career data science researchers to undertake a part-time 12-month pilot collaborative research project using data generated by Crick scientists. The projects apply data science approaches to challenges faced by biomedical investigators, under the leadership of a PI from Crick and a PI from the Turing. The aim of these pilot projects is to establish partnerships and develop results that could lead to larger funded collaborations. Asher Mullokandov is Crick-Turing Biomedical Data Science award holder and a postdoctoral associate in the Imperial College Mathematics Department, EPSRC Centre for Mathematics of Precision Healthcare. Project title: Integrating spatial relationships in single cell data analysis and visualisation with novel graph convolutional neural network architectures
Collaborator Contribution The projects apply data science approaches to challenges faced by biomedical investigators, under the leadership of a PI from Crick and a PI from the Turing. The aim of these pilot projects is to establish partnerships and develop results that could lead to larger funded collaborations.
Impact multi-disciplinary
Start Year 2019
 
Description Biogen 
Organisation Biogen
Country United Kingdom 
Sector Private 
PI Contribution Pilot - AI for Translational Myelin Imaging Biogen has discovered that advanced MRI measures from MTR or DTI imaging may stratify patients for response to an experimental remyelination treatment, but recognise that this imaging is not routinely available outside of a research setting. Building on data acquired in ongoing clinical trials using these measures in conjunction with routine imaging, we aim to develop analytical methods that can stratify patients for responsiveness to remyelination therapy based on conventional brain T1, T2 and T2-FLAIR MRI images able to be acquired in the clinic. We addressed three objectives in this research and development project: 1. We discovered whether these conventional brain MR images can be used as a binary classifier to stratify patients into groups that are more and less likely to respond to the experimental treatment. The performance criteria will be the relative extent to which this can be achieved currently with MTR or DTI imaging. 2. We characterised the image features or patterns that play the most important roles and thus contribute as image-based biomarkers for stratification to ensure that the basis of classifications is explainable. 3. We developed a software package implementing the optimal algorithm that is suitable for use at individual imaging sites or in a cloud based central processing platform.
Collaborator Contribution Pilot - AI for Translational Myelin Imaging Biogen has discovered that advanced MRI measures from MTR or DTI imaging may stratify patients for response to an experimental remyelination treatment, but recognise that this imaging is not routinely available outside of a research setting. Building on data acquired in ongoing clinical trials using these measures in conjunction with routine imaging, we aim to develop analytical methods that can stratify patients for responsiveness to remyelination therapy based on conventional brain T1, T2 and T2-FLAIR MRI images able to be acquired in the clinic. We addressed three objectives in this research and development project: 1. We discovered whether these conventional brain MR images can be used as a binary classifier to stratify patients into groups that are more and less likely to respond to the experimental treatment. The performance criteria will be the relative extent to which this can be achieved currently with MTR or DTI imaging. 2. We characterised the image features or patterns that play the most important roles and thus contribute as image-based biomarkers for stratification to ensure that the basis of classifications is explainable. 3. We developed a software package implementing the optimal algorithm that is suitable for use at individual imaging sites or in a cloud based central processing platform.
Impact Pilot - AI for Translational Myelin Imaging Biogen has discovered that advanced MRI measures from MTR or DTI imaging may stratify patients for response to an experimental remyelination treatment, but recognise that this imaging is not routinely available outside of a research setting. Building on data acquired in ongoing clinical trials using these measures in conjunction with routine imaging, we aim to develop analytical methods that can stratify patients for responsiveness to remyelination therapy based on conventional brain T1, T2 and T2-FLAIR MRI images able to be acquired in the clinic. We addressed three objectives in this research and development project: 1. We discovered whether these conventional brain MR images can be used as a binary classifier to stratify patients into groups that are more and less likely to respond to the experimental treatment. The performance criteria will be the relative extent to which this can be achieved currently with MTR or DTI imaging. 2. We characterised the image features or patterns that play the most important roles and thus contribute as image-based biomarkers for stratification to ensure that the basis of classifications is explainable. 3. We developed a software package implementing the optimal algorithm that is suitable for use at individual imaging sites or in a cloud based central processing platform.
Start Year 2018
 
Description CRUK 
Organisation Cancer Research UK
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution CRUK Imperial Centre Data Science Award
Collaborator Contribution CRUK Imperial Centre Data Science Award
Impact CRUK Imperial Centre Data Science Award
Start Year 2021
 
Description Center for Disease Dynamics,Economics & Policy 
Organisation The Center For Disease Dynamics, Economics & Policy
Country United States 
Sector Charity/Non Profit 
PI Contribution Multi-level modeling interventions to reduce the burden of carbapenem-resistant organisms within and between hospitals
Collaborator Contribution Financial contribution
Impact multi-disciplinary: mathematics and medicine
Start Year 2017
 
Description Edinburgh Parallel Computing Centre 
Organisation University of Edinburgh
Department Edinburgh Parallel Computing Centre (EPCC)
Country United Kingdom 
Sector Academic/University 
PI Contribution The Exascale Mesh Network - ELEMENT - addresses the high priority use case of meshing for the Exascale (i.e. ensuring that meshes are of sufficient quality to represent Exascale problems and can be partitioned efficiently to minimise load imbalance) as well as meshing at the Exascale (i.e. creating highly scalable solutions that will be able to exploit extreme levels of parallelism). The meshes required for Exascale simulations, under which we will aim to model problems with extreme geometric complexity and levels of refinement, will necessarily be very large with 10^9 cells and above, and contain cells that may differ in size by many orders of magnitude to faithfully resolve the underlying physics at their appropriate scales. Meshing and geometry management remain a significant bottleneck for complex applications on HPC platforms, posing a challenging obstacle that must be overcome to enable Exascale simulations. From a technical perspective, these issues include (but are not limited to) improved geometric handling, mesh adaptation and optimisation, intelligent meshing, automation and robustness, all within a large distributed environment that lies outside of our current capabilities. ELEMENT's objectives are threefold: building a community around meshing practice by establishing a collaborative network; undertaking proof of concept studies, with prototype implementations of two target challenges; and publishing a Vision Paper and strategic research agenda covering the full meshing workflow, from mesh generation to adaptation, partitioning and visualisation.
Collaborator Contribution The Exascale Mesh Network - ELEMENT - addresses the high priority use case of meshing for the Exascale (i.e. ensuring that meshes are of sufficient quality to represent Exascale problems and can be partitioned efficiently to minimise load imbalance) as well as meshing at the Exascale (i.e. creating highly scalable solutions that will be able to exploit extreme levels of parallelism). The meshes required for Exascale simulations, under which we will aim to model problems with extreme geometric complexity and levels of refinement, will necessarily be very large with 10^9 cells and above, and contain cells that may differ in size by many orders of magnitude to faithfully resolve the underlying physics at their appropriate scales. Meshing and geometry management remain a significant bottleneck for complex applications on HPC platforms, posing a challenging obstacle that must be overcome to enable Exascale simulations. From a technical perspective, these issues include (but are not limited to) improved geometric handling, mesh adaptation and optimisation, intelligent meshing, automation and robustness, all within a large distributed environment that lies outside of our current capabilities. ELEMENT's objectives are threefold: building a community around meshing practice by establishing a collaborative network; undertaking proof of concept studies, with prototype implementations of two target challenges; and publishing a Vision Paper and strategic research agenda covering the full meshing workflow, from mesh generation to adaptation, partitioning and visualisation.
Impact The Exascale Mesh Network - ELEMENT - addresses the high priority use case of meshing for the Exascale (i.e. ensuring that meshes are of sufficient quality to represent Exascale problems and can be partitioned efficiently to minimise load imbalance) as well as meshing at the Exascale (i.e. creating highly scalable solutions that will be able to exploit extreme levels of parallelism). The meshes required for Exascale simulations, under which we will aim to model problems with extreme geometric complexity and levels of refinement, will necessarily be very large with 10^9 cells and above, and contain cells that may differ in size by many orders of magnitude to faithfully resolve the underlying physics at their appropriate scales. Meshing and geometry management remain a significant bottleneck for complex applications on HPC platforms, posing a challenging obstacle that must be overcome to enable Exascale simulations. From a technical perspective, these issues include (but are not limited to) improved geometric handling, mesh adaptation and optimisation, intelligent meshing, automation and robustness, all within a large distributed environment that lies outside of our current capabilities. ELEMENT's objectives are threefold: building a community around meshing practice by establishing a collaborative network; undertaking proof of concept studies, with prototype implementations of two target challenges; and publishing a Vision Paper and strategic research agenda covering the full meshing workflow, from mesh generation to adaptation, partitioning and visualisation.
Start Year 2020
 
Description Great Britain Sasakawa Foundation 
Organisation The Great Britain Sasakawa Foundation
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution Pauls Expert grant by The Great Britain Sasakawa Foundation for a two weeks visit to Dr Takayuki Nozawa at the Tokyo Institute of Technology.
Collaborator Contribution Pauls Expert grant by The Great Britain Sasakawa Foundation for a two weeks visit to Dr Takayuki Nozawa at the Tokyo Institute of Technology.
Impact Pauls Expert grant by The Great Britain Sasakawa Foundation for a two weeks visit to Dr Takayuki Nozawa at the Tokyo Institute of Technology.
Start Year 2019
 
Description Health Foundation - SEVH 
Organisation Health Foundation
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution TBC
Collaborator Contribution TBC
Impact TBC
Start Year 2020
 
Description Mental Health Innovations 
Organisation Mental Health Innovation Network (MHIN)
Country Switzerland 
Sector Charity/Non Profit 
PI Contribution Contribution towards PDRA time
Collaborator Contribution Contribution towards PDRA time
Impact Multidisciplinary collaboration
Start Year 2019
 
Description National Institute for Health Research 
Organisation National Institute for Health Research
Country United Kingdom 
Sector Public 
PI Contribution LOCOMOTION (long COVID multidisciplinary consortium: optimising treatments and services across the NHS) study. Co-investigators on a £3.4 million grant (of which £600k comes to ICL spread between Maths and IGHI) from the NIHR to investigate the treatment of patients with Long COVID: https://www.nihr.ac.uk/news/196-million-awarded-to-new-research-studies-to-help-diagnose-and-treat-long-covid/28205 and https://www.imperial.ac.uk/news/226773/long-covid-research-receives-funding-boost/
Collaborator Contribution LOCOMOTION (long COVID multidisciplinary consortium: optimising treatments and services across the NHS) study. Co-investigators on a £3.4 million grant (of which £600k comes to ICL spread between Maths and IGHI) from the NIHR to investigate the treatment of patients with Long COVID: https://www.nihr.ac.uk/news/196-million-awarded-to-new-research-studies-to-help-diagnose-and-treat-long-covid/28205 and https://www.imperial.ac.uk/news/226773/long-covid-research-receives-funding-boost/
Impact OCOMOTION (long COVID multidisciplinary consortium: optimising treatments and services across the NHS) study. Co-investigators on a £3.4 million grant (of which £600k comes to ICL spread between Maths and IGHI) from the NIHR to investigate the treatment of patients with Long COVID: https://www.nihr.ac.uk/news/196-million-awarded-to-new-research-studies-to-help-diagnose-and-treat-long-covid/28205 and https://www.imperial.ac.uk/news/226773/long-covid-research-receives-funding-boost/
Start Year 2021
 
Description Nuffield Foundation 
Organisation Nuffield Foundation
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution The Future of Work and Well-being: The Pissarides Review. Co-investigators on a £1.8 million grant (of which £363k comes to ICL) from the Nuffield Foundation to the Institute for the Future of Work to investigate the relationship between automation of work and wellbeing: https://www.nuffieldfoundation.org/project/the-future-of-work-and-wellbeing-the-pissarides-ifow-review . Centre website: https://www.ifow.org
Collaborator Contribution . The Future of Work and Well-being: The Pissarides Review. Co-investigators on a £1.8 million grant (of which £363k comes to ICL) from the Nuffield Foundation to the Institute for the Future of Work to investigate the relationship between automation of work and wellbeing: https://www.nuffieldfoundation.org/project/the-future-of-work-and-wellbeing-the-pissarides-ifow-review . Centre website: https://www.ifow.org
Impact The Future of Work and Well-being: The Pissarides Review. Co-investigators on a £1.8 million grant (of which £363k comes to ICL) from the Nuffield Foundation to the Institute for the Future of Work to investigate the relationship between automation of work and wellbeing: https://www.nuffieldfoundation.org/project/the-future-of-work-and-wellbeing-the-pissarides-ifow-review . Centre website: https://www.ifow.org
Start Year 2021
 
Description University of Cambridge 
Organisation University of Cambridge
Country United Kingdom 
Sector Academic/University 
PI Contribution This project will develop new techniques to carefully link transcriptome and mtDNA sequencing data to stochastic models of mtDNA evolution. We will seek to link stochastic models for single-cell mitochondrial population genetics to single-cell transcriptome and single-cell mtDNA sequencing: the objective will be to understand, and design therapies for, mitochondrial genetic ageing.
Collaborator Contribution This project will develop new techniques to carefully link transcriptome and mtDNA sequencing data to stochastic models of mtDNA evolution. We will seek to link stochastic models for single-cell mitochondrial population genetics to single-cell transcriptome and single-cell mtDNA sequencing: the objective will be to understand, and design therapies for, mitochondrial genetic ageing.
Impact This project will develop new techniques to carefully link transcriptome and mtDNA sequencing data to stochastic models of mtDNA evolution. We will seek to link stochastic models for single-cell mitochondrial population genetics to single-cell transcriptome and single-cell mtDNA sequencing: the objective will be to understand, and design therapies for, mitochondrial genetic ageing.
Start Year 2019
 
Description University of Oslo 
Organisation University of Oslo
Country Norway 
Sector Academic/University 
PI Contribution The aim of the project was to improve the bioinformatics behind detecting variation in the short read data for this long-standing outbreak. We had access to the metadata from Public Health England and we well placed to apply new bioinformatics approaches to detect additional variation, and therefore enable us to resolve transmission where with standard bioinformatics (variant calling) pipelines this is not possible. We used two approaches: the first is to looked for short insertions and deletions, which are not seen by standard variant calling methods. The second was to capture count variation in repeat regions. Because these regions of the genome are repetitive, variant calling methods cannot usually reliably distinguish variation from sequencing error. However, new advances from human genetics now allow count numbers to be detected by other means. The project changed how TB transmission is estimated from WGS data in many other settings, as low variation was a problem for this field more broadly than in this particular outbreak.
Collaborator Contribution The aim of the project was to improve the bioinformatics behind detecting variation in the short read data for this long-standing outbreak. We had access to the metadata from Public Health England and we well placed to apply new bioinformatics approaches to detect additional variation, and therefore enable us to resolve transmission where with standard bioinformatics (variant calling) pipelines this is not possible. We used two approaches: the first is to looked for short insertions and deletions, which are not seen by standard variant calling methods. The second was to capture count variation in repeat regions. Because these regions of the genome are repetitive, variant calling methods cannot usually reliably distinguish variation from sequencing error. However, new advances from human genetics now allow count numbers to be detected by other means. The project changed how TB transmission is estimated from WGS data in many other settings, as low variation was a problem for this field more broadly than in this particular outbreak.
Impact The aim of the project was to improve the bioinformatics behind detecting variation in the short read data for this long-standing outbreak. We had access to the metadata from Public Health England and we well placed to apply new bioinformatics approaches to detect additional variation, and therefore enable us to resolve transmission where with standard bioinformatics (variant calling) pipelines this is not possible. We used two approaches: the first is to looked for short insertions and deletions, which are not seen by standard variant calling methods. The second was to capture count variation in repeat regions. Because these regions of the genome are repetitive, variant calling methods cannot usually reliably distinguish variation from sequencing error. However, new advances from human genetics now allow count numbers to be detected by other means. The project changed how TB transmission is estimated from WGS data in many other settings, as low variation was a problem for this field more broadly than in this particular outbreak.
Start Year 2018
 
Description Wellcome Trust 
Organisation Wellcome Trust
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution Sir Henry Wellcome Postdoctoral Fellowships: this scheme offers recently qualified postdoctoral researchers the opportunity to start independent research careers, working in some of the best research environments in the world.
Collaborator Contribution Sir Henry Wellcome Postdoctoral Fellowships: this scheme offers recently qualified postdoctoral researchers the opportunity to start independent research careers, working in some of the best research environments in the world.
Impact Sir Henry Wellcome Postdoctoral Fellowships: this scheme offers recently qualified postdoctoral researchers the opportunity to start independent research careers, working in some of the best research environments in the world.
Start Year 2019
 
Description World Health Organization: Understanding, monitoring and mitigating the impact of the pandemic on HCAI and antimicrobial 
Organisation World Health Organization (WHO)
Country Global 
Sector Public 
PI Contribution Understanding, monitoring and mitigating the impact of the pandemic on HCAI and antimicrobial resistance in in acute care, for both COVID-19 and non-COVID-19 patient populations
Collaborator Contribution Providing financial support for the purchase of equipment and supplies.
Impact Multi-disciplinary: Medicine and Mathematics
Start Year 2020
 
Title HCGA: Highly comparative graph analysis 
Description HCGA is a software package that computes a large, comprehensive collection of graph properties and uses them as features for the systematic, highly comparative analysis of graph datasets. Our toolbox makes it possible for researchers from diverse scientific fields to easily access an extensive set of graph-theoretical tools to generate interpretable and quantifiable insights into their data. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact Networks are widely used as mathematical models of complex systems across many scientific disciplines. Decades of work have produced a vast corpus of research characterizing the topological, combinatorial, statistical, and spectral properties of graphs. Each graph property can be thought of as a feature that captures important (and sometimes overlapping) characteristics of a network. In this paper, we introduce HCGA, a framework for highly comparative analysis of graph datasets that computes several thousands of graph features from any given network. HCGA also offers a suite of statistical learning and data analysis tools for automated identification and selection of important and interpretable features underpinning the characterization of graph datasets. We show that HCGA outperforms other methodologies on supervised classification tasks on benchmark datasets while retaining the interpretability of network features. We exemplify HCGA by predicting the charge transfer in organic semiconductors and clustering a dataset of neuronal morphology images. 
URL https://github.com/barahona-research-group/hcga
 
Description Achieving Impact in Healthcare: From Mathematics to Clinical Support Systems and Devices 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Background

With a rapidly ageing global population and challenges such as the growth of antibiotic resistance, there has been significant growth in the global incidence of chronic and infectious health conditions. Furthermore, the number of people living with two or more chronic health conditions is forecast to treble by 2030. In the light of this, EPSRC introduced a set of Grand Challenges for Healthcare Technologies and issued a strategic call in 2015 to set up a number of Centres for Mathematics in Healthcare within the UK, where the remit of the Centres is to develop and apply modern mathematical ideas to problems of potential impact to healthcare.

As a result of this call, five EPSRC Mathematics for Healthcare Centres, based at Cambridge, Exeter Glasgow, Imperial and Liverpool have been funded to a total of £10m. These Centres were established in 2016 and aim to establish an ongoing programme of research and impact activities in this area, beyond the lifetime of the initial funding period. In addition to their complementary research programmes, the Centres are nurturing a new generation of researchers able to bring advanced mathematical techniques to new areas of healthcare and medicine.


Aims and Objectives

This joint workshop of the five Centres focused on translating mathematical research into technological advances, as well as outreach and linkage with clinicians and end-user companies. It will present the opportunity to hear in detail about the project collaborations, research and outcomes from each Centre. The programme aimed not only to nurture the mathematical research associated with the Centres, but to engage end-users to ensure that best practice is spread as widely as possible.

This workshop aimed to coordinate and consolidate the research agenda within the Maths for Healthcare space for the subsequent five years and scope out a proposal for a six month Research Programme on the Mathematics of Healthcare to be held at the Isaac Newton Institute.

The workshop Programme featured talks from all five Centres. The themes of 'Clinical Support Systems', 'Achieving Impact' and 'Mathematical Challenges" were explored. Talks covered a range of topics, including cross-methodology challenges for specific disease groups, cross-disease challenges for specific methodologies and machine learning customised for medical imaging.

The event was of interest to researchers, clinicians and healthcare technologists from biomedical imaging, mathematics, engineering, computer science, biology and medicine and presents the opportunity for knowledge exchange and networking between senior scientists with relevant individuals from industry and government.
Year(s) Of Engagement Activity 2019
 
Description Assessing the Impacts of Public Health Policies using Computer Simulation Models 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact This one-day workshop was an opportunity for modellers across a wide-range of disciplines to come together with policy makers to discuss the latest advances and trends in modelling, how different disciplines approach common problems, and to learn from each other on how to successfully influence policy decisions using models. This workshop is co-sponsored by the Quantitative Sciences Research Institute (QSRI) and hosted by Prof. Franco Sassi, the Director of the Centre for Health Economics & Policy Innovation (CHEPI) at the Business School and Prof. Mauricio Barahona, the Director of the Centre for Mathematics of Precision Healthcare (CMPH) within the Maths department at Imperial College London.
Year(s) Of Engagement Activity 2020
 
Description CMPH and COXIC (Complexity OXford Imperial College) Workshop with Prof Cris Moore 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Postgraduate students
Results and Impact There is a deep analogy between statistical inference and statistical physics. Just as a block of iron suddenly loses its magnetic field when it reaches a critical temperature, data can suddenly become impossible to analyze if it becomes too noisy or too incomplete. The event focused on the case of finding communities in social and biological networks, and the "detectability transition" beyond which we cannot classify nodes better than chance, or even tell whether community structure really exists. The aim of the workshop was to show how physics both helps us locate these phase transitions, and gives us optimal algorithms that succeed all the way up to this point.
Biography:
Cristopher Moore received his B.A. in Physics, Mathematics, and Integrated Science from Northwestern University, and his Ph.D. in Physics from Cornell. From 2000 to 2012 he was a professor at the University of New Mexico, with joint appointments in Computer Science and Physics. Since 2012, Moore has been a resident professor at the Santa Fe Institute; he has also held visiting positions at École Normale Superieure, École Polytechnique, Université Paris 7, the Niels Bohr Institute, Northeastern University, and the University of Michigan. He has published over 150 papers at the boundary between physics and computer science, ranging from quantum computing, to phase transitions in NP-complete problems, to the theory of social networks and efficient algorithms for analyzing their structure. He is an elected Fellow of the American Physical Society, the American Mathematical Society, and the American Association for the Advancement of Science. With Stephan Mertens, he is the author of The Nature of Computation from Oxford University Press.
Agenda:
12:00-13:00 - Prof Cris Moore
13:00-14:00 - Lunch
14:00 - 15:00 - Contributed Talks
15:00-16:00 - Coffee
16:00-17:00 - Contributed talks
Year(s) Of Engagement Activity 2018
URL http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/naturalsciences/mathematicsofprecision...
 
Description COXIC - joint Oxford/Imperial workshops 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Professional Practitioners
Results and Impact COXIC (Complexity OXford Imperial College) is a series of biannual workshops to gather researchers from Oxford and Imperial College interested in Complexity. The COXIC events are oriented towards themes in networks and complex systems and are a venue for younger scientists and also allow the presentation of early-stage work
Year(s) Of Engagement Activity 2019
 
Description COXIC Seminar 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Study participants or study members
Results and Impact In December 2020, the CMPH run COXIC Seminar (joint Oxford/Imperial seminar) as a virtual event.
The COXIC events are oriented towards themes in networks and complex systems and are a venue for younger scientists and also allow the presentation of early-stage work.
Year(s) Of Engagement Activity 2020
URL https://www.imperial.ac.uk/events/124706/coxic-seminar/
 
Description Cancer + Maths 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Postgraduate students
Results and Impact This half day workshop was opened to interested researchers across Imperial College, not just maths and cancer.
Scientific organisers:Profs Charles Coombes (CRUK Imperial Centre and CRCE) and Mauricio Barahona (EPSRC Centre for Mathematics of Precision Healthcare), and Dr Marina Evangelou (Mathematics in Medicine)
Speakers included:
Prof Michael Seckl - Can novel mathematical analyses of a large clinical and imaging data set aid treatment stratification?
Prof Eric Aboagye - Getting more out of medical imaging - mathematical modelling and feature extraction
Dr Holger Auner - Simultaneous monitoring of multiple systems-level processes during proteotoxic stress recovery in cancer cells
Dr Luca Magnani - Measuring phenotypic plasticity in cancer cells
Dr Ed Curry - Modelling local density of genomic features
Drs Nichola Cooper & George Adams - Do cytokine alterations in untreated Immune thrombocytopenia (ITP) predict patient outcomes and response to treatment
Dr Biancastella Cereser - The association between pregnancy and breast cancer risk
Dr Nick Jones - Mitochondrial DNA mutation and Cancer
Dr Vahid Shahrezaei - Modelling and inference of stochastic gene expression using single cell data
Dr Matt Grech-Sollars - Imaging brain tumour growth using fractals and diffusion MRI
Dr Ed Cohen - Quantitative Bioimaging
Year(s) Of Engagement Activity 2017
URL http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/naturalsciences/mathematicsofprecision...
 
Description Contribution to 'Good Work Monitor' report 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Policymakers/politicians
Results and Impact The CMPH Dr Jonathan Clarke contributed to the recently published by the Institute for the Future of Work report.

Across England, the COVID-19 pandemic produced widespread disruption to employers and employees alike. Working from home has become the norm for many, while millions of people in employment were furloughed and others faced redundancy. While many of these changes may be temporary, the COVID-19 pandemic may lead to lasting changes in how work is done in England, by whom and where.

In the 'Good Work Monitor' report, the Institute for the Future of Work, in collaboration with Opinium, the UCL Centre for Global Health Economics and the Centre for Mathematics of Precision Healthcare (CMPH) in the Department of Mathematics at Imperial College London create the first single and holistic measure of the availability of good work in each local authority area of England outside London. Dr Jonathan Clarke, a Sir Henry Wellcome Postdoctoral Fellow in CMPH, is one of the co-authors of this report which was presented as to the House of Lords Select Committee on COVID-19 on 28th January 2021.

Before the COVID-19 pandemic, the availability of good work varied greatly across England, with the best performing local authorities being found in the high-technology hubs of the M4 corridor west of London, while towns and cities historically reliant on heavy industry in the North and Midlands have the least availability of good work nationally.

The report shows that it is the areas with the most available good work that have fared best during the pandemic, both economically and in the direct health-related impact of COVID-19 on their residents. Consequently, while the impact of COVID-19 has been felt across the entire country, its economic impact may widen extensive pre-existing disparities in the availability of good work.

Applying Markov Stability, an unsupervised graph-based clustering technique developed by the group of Prof Mauricio Barahona in the Department of Mathematics at Imperial, the report identifies four labour market archetypes based on the characteristics of employment making up the Good Work Monitor (as shown in Fig. 3 of the report). Through the application of this technique it was possible to characterise a complex socio-economic landscape into discrete populations whose relationships to good work are similar to one another, and may face similar economic challenges.

Purely based on socio-economic data, and without using prior geographic knowledge, the industrial towns of the North and Midlands emerge as collectively having low access to good work, higher levels of unemployment and low pay. In contrast, 'Good Work Winners' emerge around the conurbations of England, particularly in the Home Counties around London with access to higher paying, more secure employment, and is associated with a life expectancy five years higher than those in northern towns.

The application of Markov Stability to the study of labour markets in England has created an opportunity to characterise regional similarities and differences in a way that emphasises the need to develop tailored solutions to local problems while learning from the experiences of localities facing similar challenges.
Year(s) Of Engagement Activity 2021
URL https://www.ifow.org/resources/the-good-work-monitor
 
Description Contribution to Workshop on "Networks Approaches for Healthcare Applications" 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Study participants or study members
Results and Impact On 30th and 31st March, the EPSRC Centre for Predictive Modelling in Healthcare held a two day workshop entitled 'Networks Approaches for Healthcare Applications'. Originally, planned to be held at the Living Systems Institute of the University of Exeter, the workshop was instead held virtually due to COVID-19 restrictions. The workshop welcomed a total of 10 speakers, and was organised by Camille Poignard, Kerry Hope, Piotr Slowinski and Peter Ashwin of the University of Exeter. With the ongoing COVID-19 research effort, we were happy to host highly topical talks such as those of Julien Arino (University of Manitoba, Canada) and Jessica Enright (University of Glasgow, UK) that touched on some of the practicalities of interacting with healthcare policymakers and governing bodies.
The workshop brought together researchers from various areas who are interested in using and developing network theoretical tools to tackle healthcare-related problems, with the purpose of building or improving intervention and control strategies for treating human diseases and pathologies, notably in epidemiology, oncology and neurology. For instance, recent advances were presented on how to use networks tools to improve public health strategies focused on preventing and controlling the spread of infectious diseases. To tackle such problems, it is necessary to develop methods to reconstruct the structures of networks from real data, investigate dynamical processes based on these structures, and the dynamics of these structures themselves. Such a "networks" approach is essential to understand pathologies in their entirety.



Organiser, Camille Poignard, research fellow at the Centre for Predictive Modelling in Healthcare explains: "The workshop was due to take place at the University of Exeter but we did not hesitate to turn it into a virtual event. We are very happy with the outcome: going online definitely increased the international impact of our event by enabling live participation from researchers in Japan, Canada and the USA. This stimulated curiosity and interactivity among all of us, as could be seen in the fruitful discussions we had at the end of each talk".



Camille describes how the workshop went on line: "Under the current circumstances, we were happy that the majority of our presenters kindly accepted to give their talks as scheduled. We also managed to get some additional speakers on very topical issues. Clearly more workshops will take place online in the future, and all of us were definitely excited to interact virtually altogether."



The talks covered topics including epidemic spreading, brain networks, endocrinology, gene networks, protein interactions networks, temporal networks, time-delay dynamical systems and had good balance of theoretical and data-driven approaches. We welcomed a range of speakers and participants from across the globe including the UK, Ireland, Singapore, Austria, France, Germany, Switzerland, Luxembourg, Slovenia, Columbia, Canada, USA and Japan. This included participants from our fellow EPSRC Centres for Mathematics in Healthcare across the UK. A full list of speakers and program is available at the workshop webpage: http://nethealth2020.weebly.com. The workshop was supported by the EPSRC Centre for Predictive Modelling in Healthcare and through a Research Led Initiative of the University of Exeter Doctoral College.

Feedback from participants included:

"The talks were very informative and the Zoom interface was effective with screen sharing and ability to ask questions when necessary."



"The scope of speakers was very good - a variety of different background, but working on similar types of applied maths problems."

We thank the speakers and participants of workshop who made this an extremely worthwhile event, and look forward to cultivating further collaborations. Please follow the CPMH on Twitter to keep up-to-date on our future plans, events and opportunities.
Year(s) Of Engagement Activity 2020
URL https://emps.exeter.ac.uk/mathematics/research/pmh/events/
 
Description DOES PLACE-BASED CARE MATTER TO PRIMARY CARE IN THE POST-COVID-19 DIGITAL AGE? 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Policymakers/politicians
Results and Impact The blog article by Thomas Beaney (GP registrar, clinical fellow at ICL) and Jonny Clarke (Sir Henry Wellcome Postdoctoral Fellow at ICL).

For GPs to Engage effectively and proactively in population health we need to understand not only who the population is, but also where they live. In this blog, authors discuss their recent work exploring how upscaling GPs into Primary Care Networks (PCNs) can facilitate the provision of local place-based population healthcare.

The full article is available here: https://bjgplife.com/2020/09/10/does-place-based-care-matter-to-primary-care-in-the-post-covid-19-digital-age/
Year(s) Of Engagement Activity 2020
URL https://bjgplife.com/2020/09/10/does-place-based-care-matter-to-primary-care-in-the-post-covid-19-di...
 
Description Data Science Virtual Poster Competition 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Postgraduate students
Results and Impact Prof Yaliraki's Research Group won the first prize in the Virtual Data Science Poster Competition 2020.

The Faculty of Natural Sciences invited its PhD students, Postdocs, Early career researchers and research groups working on the area of Data Science theme to participate at this virtual poster competition. Posters were displayed here and Imperial staff and participated voting for their favourite poster ('Imperial popular choice award').

We are delighted to announce that Leonie Stroemich & Florian Song (Department of Chemistry) from Prof Yaliraki's Research Group were awarded with £500 for best poster: ProteinLens: a user-friendly web-based application to uncover allosteric signalling in structural data.

Prof Yaliraki's Research Group developed publicly available online tool for the analysis of protein structures. More information on this tool can be found here:
Year(s) Of Engagement Activity 2021
URL https://www.proteinlens.io/webserver/
 
Description Differential Geometry Applied to Monitoring of Brain States from EEG Signals - Joint Seminar: Centre for Neurotechnology/Biomathematics Group/EPSRC Centre for Mathematics of Precision Healthcare 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Professional Practitioners
Results and Impact Speaker: Dr Mario Chavez (The French National Centre for Scientific Research)

Title: Differential Geometry Applied to Monitoring of Brain States from EEG Signals

Abstract: Current neuroscience research attempts to understand how brain functions result from dynamic interactions in large-scale cortical networks, and to further identify how cognitive tasks or brain diseases contribute to reshape this organization. In this talk I'll present method based on differential (Riemannian) geometry to identify a cortical signature of breathing discomfort from EEG recordings of patients. I'll show how the characterization of spatio-temporal patterns on differential manifolds may provide much better performances than alternate methods currently used in brain computer interfaces. Further, I'll show the effective translation of our algorithm to an embedded device (portable, noninvasive, with few electrodes, and fast computation) that can be highly operable in clinical environments as well as in custom-designed systems.
Year(s) Of Engagement Activity 2019
URL https://www.imperial.ac.uk/events/97557/differential-geometry-applied-to-monitoring-of-brain-states-...
 
Description EPSRC Centre for Mathematics of Precision Healthcare Launch 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Precision healthcare seeks to deploy therapies that are sensitive to the particular genetic, lifestyle and environmental circumstances of each patient. Understanding how best to use these numerous features about each patient is a true mathematical challenge.
The EPSRC Centre for Mathematics of Precision Healthcare launch event brought together Imperial's mathematicians, engineers and computer scientists with medical scientists and clinicians to discuss such issues across different areas in healthcare. Our launch featured the following speakers: Professor Beth Simone Noveck, Director, GovLab and Professor Paul Matthews, Edmond and Lily Safra Chair and Head of Brain Sciences, Imperial College London
Year(s) Of Engagement Activity 2016
URL http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/naturalsciences/mathematicsofprecision...
 
Description Exploring Data-based and AI approaches to Healthcare 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact The Institute of Global Health Innovation (IGHI) collaborated with the EPSRC Centre for Mathematics of Precision Healthcare to discuss and learn about the latest advances in data-based and AI approaches in healthcare.
The first talk of the Forum was delivered by Dr Aldo Faisal, Director of the Behaviour Analytics Lab at the Data Science Institute, who provided a look into how AI has been harnessing millions of doctor-patient interaction. Following this, Erik Mayer from IGHI's Centre for Health Policy and Clinical Senior Lecturer at Imperial's Department of Surgery & Cancer, spoke about 'Patient safety data and data analytics within Imperial NHS Trusts'. Here he highlighted some of the work being done with AI at the Patient Safety Translational Research Centre and IGHI's Helix Centre.
The final presentation was given by Professor Mauricio Barahona, Director of EPSRC Centre for Maths of Precision Healthcare and Chair of Biomathematics. Following Professor Barahona's talk titled, 'From free text to clusters of content in health records: an unsupervised graph partitioning approach', the speakers were then asked questions by the audience
Year(s) Of Engagement Activity 2018
URL http://www.imperial.ac.uk/news/185413/exploring-data-based-ai-approaches-healthcare/
 
Description Five EPSRC Maths-Healthcare Centres Meeting, University of Glasgow, 19th-21st Sept. 2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Other audiences
Results and Impact FIVE EPSRC Maths-Healthcare Centres (Cambridge, Exeter, Imperial, Liverpool and SofTMech) gathered together from the 19th to the 21st September 2018 at the University of Glasgow to exchange success stories and share experiences, and more importantly to consider future funding. Kings College London, UCLouvain, the University of Lancaster, Terumo Aortic and The Sick Children's Hospital in Glasgow were also represented by speakers who had been invited by one of the centres. Each of the Centres had recently completed their Mid-Term Review. Two portfolio Managers from the EPSRC, who fund the five centres attended, giving the centres the perspective of the EPSRC, as they discussed the way forward.
This was the first of two workshops. The centres gave an overview of the work at their centre, in particular highlighting new and exciting work where collaboration with other UK expertise would form a stronger funding application. In addition to the external speakers each centre had a number of internal speakers who gave presentations on their research and how it fitted in with the overall theme of their Maths and Healthcare Centre.
Year(s) Of Engagement Activity 2018
URL http://www.softmech.org/events/headline_593316_en.html
 
Description Global Health Forum: Data-based and AI approaches to Healthcare 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Our monthly Global Health Forum brings together Imperial researchers, students, and staff from across all of the college's Faculties to highlight, discuss and disseminate findings on current global health research and innovations. The Forums encourage interdisciplinary discussions with the intention to foster inter-Faculty research initiatives and leverage the immense strengths of Imperial College to resolve global health priorities of the early 21st Century.

There is currently a surge of interest in the application and development of data-rich approaches in the healthcare sector for analytics, monitoring and decision-making. The range of applications extends from the patient level to organisational aspects of healthcare provision. This Forum highlighted some of the directions currently being pursued across academic departments at Imperial in close collaboration with Imperial NHS Trusts and Centres using healthcare data in conjunction with advanced computational and mathematical techniques.
The Forum was co-organised by the Institute for Global Health Innovation and the EPSRC Centre for Mathematics of Precision Healthcare and was followed by a Q&A answer highlighting ongoing research and opportunities.
Year(s) Of Engagement Activity 2018
URL http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/centres/globalhealth/eventssummary/eve...
 
Description Imperial Lates: Xmaths - Imperial Lates celebrate the latest in science and engineering at Imperial College London - bringing the public together with world leading minds in their respective fields, who not only love what they do, but also love sharing their work with new audiences. 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Imperial Lates celebrate the latest in science and engineering at Imperial College London - bringing the public together with world leading minds in their respective fields, who not only love what they do, but also love sharing their work with new audiences. In December 2018 the public had an opportunity to meet Imperila's world leading mathematicians to learn e.g. how they visualise the equations they mull over, why the idea of inherent maths genius is a myth, and how Maths is being applied to understand everything from black holes to how people behave in crowds.
Year(s) Of Engagement Activity 2018
URL http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/eventssummary/event_20-8-2018-16-14-44
 
Description International Conference on Complex Systems, Greece, September 2018. 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Paul Expert (CMPH PDRA since March 2017): Co-organised satellite at international Conference on Complex Systems, Greece, September 2018.
Year(s) Of Engagement Activity 2018
URL http://ccs2018.web.auth.gr/
 
Description LMS-Math mixer 3.0 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Postgraduate students
Results and Impact This event was organised by the MRC London Institute of Medical Sciences (MRC LMS), the Quantitative Sciences Research Institute (QSRI), The EPSRC Centre for
Mathematics of Precision Healthcare (CMPH) and Mathematics in Medicine.The event is coordinated by Samuel Marguerat (MRC LMS), Marina Evangelou (Statistics) and Vahid Shahrezaei (Biomathematics), and Almut Veraart (QSRI). The aim of the event was to engage with PG and UG students who had an opportunity to find out about the work that is carried out by members of LMS and the Department of Mathematics.
Year(s) Of Engagement Activity 2018
URL http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/naturalsciences/mathematicsofprecision...
 
Description London Chapter of Databeers 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Public/other audiences
Results and Impact Dr Expert (CMPH PDRA) is founding member and co-organiser of the London Chapter of Databeers. It is a free (roughly) bimonthly series of events aimed at a general audience where << data practioners >> present their work in short, 7 min, non technical talks, no equations/no code, to make it accessible to the greater number.Audience is composed of academics, civil servants and industry workers and we are now consistently at full capacity, 200+ attendance
Year(s) Of Engagement Activity 2016
URL https://databeersldn.tumblr.com/
 
Description MathsBioFest 2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Undergraduate students
Results and Impact MathBioFest 2018 took place at the Department of Mathematics, Imperial College London. The symposium celebrated the achievements of mathematics at the interface with life sciences in their broadest sense. The programme included an exciting mix of broad-audience talks and research presentations. The event showcased the pivotal role that mathematical reasoning plays in fields as diverse as molecular biology, animal behaviour and cancer biology.

The meeting was hosted by the EPSRC Centre for Mathematics of Precision Healthcare, as part of the Year of Mathematical Biology 2018 initiative, jointly run by the European Mathematical Society (EMS) and the European Society for Mathematical and Theoretical Biology (ESMTB).
Year(s) Of Engagement Activity 2018
URL http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/naturalsciences/mathematicsofprecision...
 
Description November's 2020 Imperial Lates event 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact The event was part of the ongoing series of evening showcases where Imperial's researchers share the wonder of their work with members of the public.

Our PhD student, Ashleigh Myall, was representing the CMPH during November's Imperial Lates. The event explored infections, deadly diseases, and our work to beat them. Equipped with Nerf guns I was featured on the colleges new website helping to run a stand which educates the public about the antibiotic arms race going. More than 1000 members of the general public attended, including students, children, from a variety of backgrounds. Many had little idea of the hidden dynamics which antimicrobial resistance is becoming so prominent through, it was great to have discussions with many keen and interested members of the public.
Year(s) Of Engagement Activity 2019
URL https://www.imperial.ac.uk/news/193992/college-gets-infectious-novembers-imperial-lates/
 
Description Pandemic mortality and prevention: News from the College 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact Imperial's Dr Jonathan Clarke, Professor Azeem Majeed and Dr Thomas Beaney published an editorial in the British Medical Journal about a study on excess mortality during the COVID-19 pandemic in 29 high-income countries.
Year(s) Of Engagement Activity 2021
URL https://www.imperial.ac.uk/news/222953/pandemic-mortality-prevention-news-from-college/
 
Description Panel debate: Big data and the future of social #TheNewNow 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Social media is changing rapidly. We are going from a world of simply tweeting about our cat and periscoping about our lives, to analysing that information to create more impactful and tailored messages. Social data provides a new, unsolicited, uncensored and real-time view into the minds of existing and potential customers. But does it hold the key to future success for brands looking to harness big data and understand their customers better? To answer this question and more, we hosted a panel discussion with some of the most authoritative experts on the topic of big data and the future of social. Our panel included Twitter's VP for Europe, and three leading academics actively involved in the analysis and visualisation of the big data associated with social media.

Our panellists included:
Bruce Daisley, Vice President, Twitter Europe
Bruce runs Twitter's business in Europe, was dubbed "one of the most talented people in advertising" by Campaign magazine and voted individual of the year at the Drum Social Buzz Awards.

Professor Ken Benoit, Quantitative Social Research Methods, London School of Economics
Professor Benoit's current interests focus on big data analysis and text mining, including in social media.

Professor Sophia Yaliraki, Theoretical Chemistry and Professor Maurico Barahona, Biomathematics - both from Imperial Collage Data Science Institute's Social and Cultural Analytics Lab. Professors Yalikari and Barahona have developed a series of methods that derive interest communities and roles in Twitter based on flows to understand who is talking about what and the various roles they play.
Year(s) Of Engagement Activity 2016
URL https://jaywing.com/news/panel-debate---big-data-and-the-future-of-social---thenewnow
 
Description Satellite @CCS (Conference on Computer and Communications Security) 2019 Singapore 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The Satellite span half a day on Wednesday October the 2nd (afternoon), and included 4 invited speakers and 5 contributed talks (10+2 mins).

New technology and integrated databases supply great amounts of data containing rich spatial and temporal information. Disentangling complex relationships to gain understanding of the structure of causations and interconnectedness represented by these large data sets at a fundamental level is a non-trivial task. Mapping this information onto networks is often convenient, but nodes and links still need to be defined in a relevant way, which is not necessarily obvious from the data. Oftentimes, nodes will naturally be identified with specific time series, say EEG electrodes, traded stock or individual geolocalised footprint. When this is the case the directed interdependence, or information theoretic causal structure between the nodes can then be established by use of various methodologies many of which has their origin in Granger's seminal work on causality, but the field is in constant evolution and a trove of methods have been developed or adapted to define nodes and their relationships from spatio-temporal data across a very wide range of fields, as reflected by the fields of interest of our invited speakers.

This satellite gathered leading experts from network theory together with data scientist to take stock at the state of the art of the field and to discuss issues such as the validity, specificities, limitations and most importantly the transferability of methods to extract and analyse networks from spatio-temporal data.
Year(s) Of Engagement Activity 2019
 
Description School outreach 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Schools
Results and Impact Prof Sophia Yaliraki was invited to speak at the Science Club at the North London Collegiate School.
On Wednesday, 06th November, Prof Yaliraki was speaking on "Unsupervised, multiscale machine learning: from proteins to precision healthcare".
North London Collegiate School an independent school for girls(https://www.nlcs.org.uk/). Science Café is school's in-house program of weekly after-school events, most of which involve invited scientists addressing the students on their work. Recent events have included speakers from Oxford, Cambridge, UCL, Imperial College and the University of Michigan in the USA, as well as research scientists from the ICR, MRC and Public Health England.
Year(s) Of Engagement Activity 2019
 
Description Shout's Crisis Volunteer Event 2019 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Prof Yaliraki and Dr Jonathan Clarke from the CMPH were invited to participate in Shout's Crisis Volunteer celebration event 2019. The event brought together people from across the UK who volunteer with Shout to support people in crisis and was in attendance of the Duke and Duchess of Cambridge. Through the partnership with Mental Health Innovations and Imperial's Institute of Global Health Innovation (IGHI), we will be working on the project that will support the Shout's operation
Year(s) Of Engagement Activity 2019
 
Description Single-cell data in space and time: mathematical and computational challenges 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact The workshop is co-organised by Vahid Shahrezaei (Mathematics, Imperial College London), Samuel Marguerat (MRC LMS, Imperial) and Mauricio Barahona (Mathematics, Imperial College London) with advice from Sarah Teichmann and Martin Hemberg (Sanger Institute, Cambridge).

The meeting brought together theoretical, computational and experimental groups to present recent advances in high-dimensional single-cell data acquisition, analysis, and integration, and to discuss in an open manner the leading challenges in this rapidly evolving area.
Year(s) Of Engagement Activity 2019