activity
20172022
most citedValue of Information: Sensitivity Analysis and Research Design in Bayesian Evidence Synthesis

34 citations · 65 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ME2022★ 23 cited

A comparison of two frameworks for multi-state modelling, applied to outcomes after hospital admissions with COVID-19

Christopher Jackson, Brian Tom, Peter Kirwan +5

We compare two multi-state modelling frameworks that can be used to represent dates of events following hospital admission for people infected during an epidemic. The methods are a…

q-bio.PE2021

Quantifying efficiency gains of innovative designs of two-arm vaccine trials for COVID-19 using an epidemic simulation model

Rob Johnson, Chris Jackson, Anne Presanis +2

Clinical trials of a vaccine during an epidemic face particular challenges, such as the pressure to identify an effective vaccine quickly to control the epidemic, and the effect th…

stat.AP2021★ 6 cited

Trends in risks of severe events and lengths of stay for COVID-19 hospitalisations in England over the pre-vaccination era: results from the Public Health England SARI-Watch surveillance scheme

Peter D. Kirwan, Suzanne Elgohari, Christopher H. Jackson +4

Background: Trends in hospitalised case-fatality risk (HFR), risk of intensive care unit (ICU) admission and lengths of stay for patients hospitalised for COVID-19 in England over…

stat.AP2019★ 2 cited

Implications for HIV elimination by 2030 of recent trends in undiagnosed infection in England: an evidence synthesis

Anne M Presanis, Peter Kirwan, Ada Miltz +9

A target to eliminate Human Immuno-deficiency Virus (HIV) transmission in England by 2030 was set in early 2019. Estimates of recent trends in HIV prevalence, particularly the numb…

stat.AP2017★ 34 cited

Value of Information: Sensitivity Analysis and Research Design in Bayesian Evidence Synthesis

Christopher Jackson, Anne Presanis, Stefano Conti +1

Suppose we have a Bayesian model which combines evidence from several different sources. We want to know which model parameters most affect the estimate or decision from the model,…