A COVID-19 Model for Local Authorities of the United Kingdom

We propose a new framework to model the COVID-19 epidemic of the United Kingdom at the level of local authorities. The model fits within a general framework for semi-mechanistic Bayesian models of the epidemic, with some important innovations: we model the proportion of infections that result in reported deaths and cases as random variables. This is in contrast to standard frameworks that model the latent infection as a deterministic function of time varying reproduction number, R _t . The model is tailored and designed to be updated daily based on publicly available data. We envisage the model to be useful for now-casting and short-term projections of the epidemic as well as estimating historical trends. The model fits are available on a public website, <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://imperialcollegelondon.github.io/covid19local">https://imperialcollegelondon.github.io/covid19local</ext-link> . The model is currently being used by the Scottish government in their decisions on interventions within Scotland [1, issue 24 to now].