Spatial heterogeneity in transmission and the impact of interventions: a mathematical modelling approach

A new strain of Coronavirus appeared in China at the end of 2019 and is spreading
beyond Chinese borders. The purpose of this project is to minimise the number of serious
cases and deaths caused by the virus, following spread in the United Kingdom. We will
use the latest information about the UK population, the best biological information about
the virus to inform mathematical models that predict where and when the disease will
spread and in what numbers. This information, rapidly communicated to the NHS will
provide the best opportunity to manage care and allocate resources proactively, in
advance of the arrival of new cases of Coronavirus.

This COVID-19 Rapid Response award is jointly funded (50:50) between the Medical Research Council and the National Institute for Health Research. The figure displayed is the total award amount of the two funders combined, with each partner contributing equally towards the project.

Predicting the size and duration of potential COVID-19 outbreaks is an essential
component of public-health planning and preparedness. Mathematical models of disease
transmission are potentially powerful tools for predicting the course of an upcoming
epidemic and evaluating control and mitigation strategies. However, standard models of
disease transmission without population structure overestimate the speed of invasion of a
novel pathogen. We have developed a spatial metapopulation transmission model for the
UK that is grounded in demographic data which incorporates regular (commuter-like)
movements of individuals. In previous work, we demonstrated that regular, repeated
movements lead to slower epidemic spread. Adapting this model for COVID-19, we
estimated that an uncontrolled epidemic in England and Wales would peak ~4 months
following sustained person-to-person transmission, but that seasonality in transmission
could substantially alter the timing and magnitude of the peak burden.
Here, we propose to use this model to evaluate control and mitigation strategies for
COVID-19. Guided by the World Health Organization-identified research priorities and
PHE needs, we will estimate the impact of travel restrictions, border screening and
quarantine policies. We will also assess the effects of social distancing measures and
other non-pharmaceutical interventions on peak burden and epidemic timing and rank
measures by effectiveness. The model will also be adapted to assess and rank
pharmaceutical deployment strategies.
Our vision is to make the model adaptable and available to other countries and settings,
both with and without census and commuting data. Key challenges include modelling
commuting patterns, incorporating realistic age structure, adding an observation model to
capture morbidity and mortality and including behaviour change which could substantially
alter dynamics.