CO-produced Mathematical Modelling of Epidemics Together (COMMET): methods and tools for integrating public voices into epidemic response modelling
Lead Research Organisation:
UNIVERSITY COLLEGE LONDON
Department Name: Institute for Global Health
Abstract
We seek to develop methods and tools to support modellers, members of the public and key stakeholders to work together to co-produce epidemic infectious disease models. This is an essential piece of pandemic preparedness, and contributes more widely to ensure that the modelling tools used across many aspects of public life are made inclusively and can deliver positive change across diverse groups in society.
The effects of epidemics on societal health and wellbeing have been large and unequal. Models of infectious disease transmission have been increasingly used to inform policy-making in response to epidemics. Infectious disease models mathematically express relationships between complex biological, behavioural and social phenomena. Models can be used to explore 'what if' questions about possible epidemic trajectories and to assess the potential impacts of different intervention or policy choices. To do this, models necessarily rely upon assumptions about various uncertainties. Modellers strive to be transparent about the assumptions underlying findings, to fit models to observed data, and to inform them from the current state of evidence. However, to explore and challenge assumptions, these must first be recognised, and communication with people with lived experience and different disciplinary perspectives must be enabled. Meanwhile, the questions and comparative scenarios that are posed of models, are subject to potential value judgements and complex trade-offs by those involved in or directing the modelling.
We require methods to enable the co-development of models that reflect the priorities of communities affected by epidemic threats and the reality of the complex processes underlying disease transmission. This innovation requires sustained interdisciplinary working. Human centred design (HCD) prioritises understanding the needs, behaviours, and preferences of end-users, deploying tools and processes to create solutions that are effective, user-friendly, and tailored. Social science and humanities allow us to engage critically with the construction of scientific knowledge, to systematically reflect on our positionality as researchers, and to explore societal perceptions of phenomena such as mathematical models. In coproduction, researchers work in meaningful partnership with patients, public and key stakeholders as equal team members, to share decision making and co-produce research that is relevant and impactful. Formative and exploratory work has highlighted key challenges and opportunities of such approaches in mathematical modelling model development. Yet, there remains an absence of tailored guidance on co-production for infectious disease modelling, despite its potential for high impact in epidemic response.
The last half century has seen unprecedented ecological change and increasing global connectivity, with a rise in emerging and pandemic infections. Enabling co-production in infectious disease modelling (with public, patients, clinicians, researchers and policy makers) could be truly transformative. It could allow the field to better address recognised challenges in modelling such as the representation of behavioural responses to epidemic dynamics and their complex feedbacks, and incorporation of social and ethnic inequalities. This will lead to more robust models and better inform equitable decision-making about interventions.
This project aims to: understand the social and institutional context of modelling; explore requirements to enable modelling co-production; iteratively test guidance by which models can be appraised and assessed, working with demonstration projects and a large network of epidemiological modelling groups; and disseminate findings and tools and to embed learning across disciplinary and sectoral channels.
The effects of epidemics on societal health and wellbeing have been large and unequal. Models of infectious disease transmission have been increasingly used to inform policy-making in response to epidemics. Infectious disease models mathematically express relationships between complex biological, behavioural and social phenomena. Models can be used to explore 'what if' questions about possible epidemic trajectories and to assess the potential impacts of different intervention or policy choices. To do this, models necessarily rely upon assumptions about various uncertainties. Modellers strive to be transparent about the assumptions underlying findings, to fit models to observed data, and to inform them from the current state of evidence. However, to explore and challenge assumptions, these must first be recognised, and communication with people with lived experience and different disciplinary perspectives must be enabled. Meanwhile, the questions and comparative scenarios that are posed of models, are subject to potential value judgements and complex trade-offs by those involved in or directing the modelling.
We require methods to enable the co-development of models that reflect the priorities of communities affected by epidemic threats and the reality of the complex processes underlying disease transmission. This innovation requires sustained interdisciplinary working. Human centred design (HCD) prioritises understanding the needs, behaviours, and preferences of end-users, deploying tools and processes to create solutions that are effective, user-friendly, and tailored. Social science and humanities allow us to engage critically with the construction of scientific knowledge, to systematically reflect on our positionality as researchers, and to explore societal perceptions of phenomena such as mathematical models. In coproduction, researchers work in meaningful partnership with patients, public and key stakeholders as equal team members, to share decision making and co-produce research that is relevant and impactful. Formative and exploratory work has highlighted key challenges and opportunities of such approaches in mathematical modelling model development. Yet, there remains an absence of tailored guidance on co-production for infectious disease modelling, despite its potential for high impact in epidemic response.
The last half century has seen unprecedented ecological change and increasing global connectivity, with a rise in emerging and pandemic infections. Enabling co-production in infectious disease modelling (with public, patients, clinicians, researchers and policy makers) could be truly transformative. It could allow the field to better address recognised challenges in modelling such as the representation of behavioural responses to epidemic dynamics and their complex feedbacks, and incorporation of social and ethnic inequalities. This will lead to more robust models and better inform equitable decision-making about interventions.
This project aims to: understand the social and institutional context of modelling; explore requirements to enable modelling co-production; iteratively test guidance by which models can be appraised and assessed, working with demonstration projects and a large network of epidemiological modelling groups; and disseminate findings and tools and to embed learning across disciplinary and sectoral channels.
