Synthesising behavioural and epidemiological models and their methodologies to simulate predictive spread of infectious diseases

The context of the research: In this study, I plan to synthesise and advance the methodologies guiding integrating behavioural and epidemiological models for human infectious diseases.
The aims and objectives of the research: In this study, I plan to synthesise the methodologies guiding integrating behavioural and epidemiological models for human infectious diseases. The core research questions I aim to address include: (i) which behavioural mechanistic models in the human psychology literature should be considered when modelling behaviour related to adherence of control strategies; (ii) which data are necessary to model human behaviour in the context of infectious disease outbreaks, noting that this may be disease and context specific; (iii) how can data collection be improved to meet the needs of disease modellers while not creating unrealistic resource expectations for stakeholders; and (iv) how incorporating behavioural mechanisms to infectious disease models affects the research findings and policy implications based on simulation studies.
The novelty of the research methodology (if any): I plan to create an updated framework for modelling behaviour in infectious disease outbreaks. This research will enhance our understanding of the usefulness of data flows from various research domains and ways to synthesise them.
The potential impact, applications, and benefits:
This proposed project will provide a structural framework and model to better predict the spread of infectious diseases through considering human behaviour, thus leading to potentially better-informed models and research findings to inform policy decisions in the event of infectious disease outbreaks. The project encourages interdisciplinary approaches whilst establishing methodologies that future researchers may replicate and improve upon.
How the research relates to the EPSRC remit:
The proposed project relates to the EPSRC remit according to its research goals in mathematical biology. Specifically, the research relates to their goal of advancing techniques to investigate biological processes and systems since I will be studying the role of human behaviour in infectious disease outbreaks and generating a novel, integrated epidemiological and behavioural model.

Into which EPSRC research areas does your research fall
Mathematical Sciences
Global uncertainties

External Partner - World Health Organization (WHO) - Jonathan Polonsky and Olivier le Polain of the WHO have agreed to support the project in the roles of external partners. They have agreed to provide data if relevant to the project and to provide their expertise as needed to support the project. However, data from the WHO is not required for the project to progress. Specifically, they have indicated that they have a dataset from the 2018-2020 Ebola outbreak in the Democratic Republic of the Congo that they would be willing to provide if needed. In addition to the WHO, the Warwick Data Science Lab is a relevant group that have studied predicting human actions based on social media data and would be an excellent source to reach out to.

In the 2018 Government Office for Science report, 'Computational Modelling: Technological Futures', Greg Clarke, the Secretary of State for Business Energy and Industrial Strategy, wrote "Computational modelling is essential to our future productivity and competitiveness, for businesses of all sizes and across all sectors of the economy". With its focus on computational models, the mathematics that underpin them, and their integration with complex data, the MathSys II CDT will generate diverse impacts beyond academia. This includes impacts on skills, on the economy, on policy and on society.

Impacts on skills.
MathSys II will produce a minimum of 50 PhD graduates to support the growing national demand for advanced mathematical modelling and data analysis skills. The CDT will provide each of them with broad core skills in the MSc, a deep knowledge of their chosen research specialisation in the PhD and a complementary qualification in transferable skills integrated throughout. Graduates will thus acquire the profiles needed to form the next generation of leaders in business, government and academia. They will be supported by an integrated pastoral support framework, including a diverse group of accessible leadership role models. The cohort based environment of the CDT provides a multiplier effect by encouraging cohorts to forge long-lasting professional networks whose value and influence will long outlast the CDT itself. MathSys II will seek to maximise the influence of these networks by providing topical training in Responsible Research and Innovation, by maintaining a robust Equality, Diversity & Inclusion policy, and by integration with Warwick's global network of international partnerships.

Economic impacts.
The research outputs from many MathSys II PhD projects will be of direct economic value to commercial, public sector and charitable external partners. Engagement with CDT partners will facilitate these impacts. This includes co-supervision of PhD and MSc projects, co-creation of Research Study Groups, and a strong commitment to provide placements/internships for CDT students. When commercial innovations or IP are generated, we will work with Warwick Ventures, the commercial arm of the University of Warwick, to commercialise/license IP where appropriate. Economic impact may also come from the creation of new companies by CDT graduates. MathSys II will present entrepreneurship as a viable career option to students. One external partner, Spectra Analytics, was founded by graduates of the preceding Complexity Science CDT, thus providing accessible role models. We will also provide in-house entrepreneurship training via Warwick Ventures and host events by external start-up accelerator Entrepreneur First.

Impacts on policy.
The CDT will influence policy at the national and international level by working with external partners operating in policy. UK examples include Department of Health, Public Health England and DEFRA. International examples include World Health Organisation (WHO) and the European Commission for the Control of Foot-and-mouth Disease (EuFMD). MathSys students will also utilise the recently announced UKRI policy internships scheme.

Impacts on society.
Public engagement will allow CDT students to promote the value of their research to society at large. Aside from social media, suitable local events include DataBeers, Cafe Scientifique, and the Big Bang Fair. MathSys will also promote a socially-oriented ethos of technology for the common good. Concretely, this includes the creation of open-source software, integration of software and data carpentry into our computational and data driven research training and championing open-access to research. We will also contribute to the 'innovation culture and science' strand of Coventry's 2021 City of Culture programme.