New Paper: A dynamic microsimulation model for epidemics

GUI for the model

A dynamic microsimulation model for epidemics

We have just published a paper that presents a new microsimulation model that estmiates how covid spreads around a population. It is currently applied to Devon, UK, but is generalisable to other areas. The model suggests that starting the first UK lockdown earlier might have reduced the total number of infections by nearly 50% during the first outbreak.

Spooner, F., J.F. Abrams, K. Morrissey, G. Shaddick M. Batty, R. Milton, A. Dennett, N. Lomax, N. Malleson, N. Nelissen, A. Coleman, J. Nur, Y. Jin, R. Greig, C. Shenton, M. Birkin (2021) A dynamic microsimulation model for epidemics. Social Science & Medicine 291, 114461. DOI: 10.1016/j.socscimed.2021.114461

A large evidence base demonstrates that the outcomes of COVID-19 and national and local interventions are not distributed equally across different communities. The need to inform policies and mitigation measures aimed at reducing the spread of COVID-19 highlights the need to understand the complex links between our daily activities and COVID-19 transmission that reflect the characteristics of British society. As a result of a partnership between academic and private sector researchers, we introduce a novel data driven modelling framework together with a computationally efficient approach to running complex simulation models of this type. We demonstrate the power and spatial flexibility of the framework to assess the effects of different interventions in a case study where the effects of the first UK national lockdown are estimated for the county of Devon. Here we find that an earlier lockdown is estimated to result in a lower peak in COVID-19 cases and 47% fewer infections overall during the initial COVID-19 outbreak. The framework we outline here will be crucial in gaining a greater understanding of the effects of policy interventions in different areas and within different populations.