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Title: Estimating the severity of SARS-CoV-2 in England Authors:  Anne Presanis - MRC Biostatistics Unit, University of Cambridge (United Kingdom) [presenting]
Abstract: The severity of the SARS-CoV-2 epidemic can be described by a number of different population-level measures summarising individual-level COVID-19 disease (clinical) severity and use of healthcare services, including the case-hospitalisation risk, hospitalised case-fatality risk, length of stay in hospital and infection-fatality risk amongst others. Some of these quantities are not directly measurable, due to the inherent inability to observe infections, rather than diagnoses, and are not straightforward to estimate, due to biases in observational data, reporting delays and other challenges. I will give an overview and examples of these challenges of estimating severity using a variety of survival, multi-state modelling and evidence synthesis approaches, including: jointly estimating the hospitalised case-fatality risk and length of stay in hospital; estimating the relative risk of hospital admission in Delta compared to Alpha cases; and combining evidence at different levels of severity to estimate the whole severity process, from infection to symptomatic infection to hospital admission to ICU admission to mortality.