For the COVID-19 pandemic, estimates of the infection- and case severity risks, i.e. the probabilities of experiencing severe events such as hospitalisations, admission to intensive care and death, are crucial to understand and predict the burden and impact on healthcare services.

No single dataset can provide enough information on its own to estimate severity, but estimation is feasible by synthesising multiple datasets. Work at the BSU is investigating use of both individual- and aggregate-level data, from clinical cohorts and population registries, and a combination of survival analysis techniques, to estimate severity as data accumulates over the course of the epidemic.

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Reports on Estimated case severity rates and length of stay in hospital and ICU – coming soon